MINERAL CARBONATION FOR SUBSURFACE CARBON STORAGE: … · mineral carbonation for subsurface carbon...

MINERAL CARBONATION FOR SUBSURFACE CARBON STORAGE:

AN EXPERIMENTAL INVESTIGATION OF OLIVINE ((Mg,Fe)2SiO4)

DISSOLUTION AND CARBONATION

A DISSERTATION SUBMITTED

TO THE DEPARTMENT OF CHEMICAL ENGINEERING

AND THE COMMITTEE ON GRADUATE STUDIES

OF STANFORD UNIVERSITY

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

DOCTOR OF PHILOSOPY

Natalie Caryl Johnson

August 2014

http://creativecommons.org/licenses/by-nc/3.0/us/

This dissertation is online at: http://purl.stanford.edu/wx406mf6583

© 2014 by Natalie Caryl Johnson. All Rights Reserved.

Re-distributed by Stanford University under license with the author.

This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.

ii



http://purl.stanford.edu/wx406mf6583

I certify that I have read this dissertation and that, in my opinion, it is fully adequatein scope and quality as a dissertation for the degree of Doctor of Philosophy.

Gordon Brown, Jr, Co-Adviser


Thomas Jaramillo, Co-Adviser


Katharine Maher


Robert J. Rosenbauer

Approved for the Stanford University Committee on Graduate Studies.

Patricia J. Gumport, Vice Provost for Graduate Education

This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file inUniversity Archives.

iii

v

Abstract

Concern about effects of climate change motivates the development of carbon

capture and storage (CCS) technologies that facilitate both the capture of carbon

dioxide (CO2) from point sources, such as power plants, and injection of CO2 into the

subsurface for long-term storage. Compared with other approaches to reduce CO2

emissions, the advantages of CCS technologies include the possibility of near-term,

large-scale implementation and reduction of CO2 emissions without major grid

infrastructure changes. However, ensuring the stability of CO2 in the subsurface for

hundreds to thousands of years is a major technological challenge. One approach for

improving the stability is to convert CO2 into a mineral via chemical reactions, a

process known as "mineral carbonation." Carbon dioxide reacts with divalent cations

(e.g., Mg) to form carbonate minerals (e.g., magnesite, MgCO3) that are stable and

negatively buoyant in the subsurface. Field studies have established that mineral

carbonation occurs in nature, but the kinetics of the reaction are not fully understood.

Of particular interest is the formation of a Si-rich surface layer that may passivate the

surface of the reacting minerals.

In order to investigate the reaction kinetics of mineral carbonation reactions at

conditions representative of geologic storage, we performed a series of batch reactions

at 60 °C and 100 bar pCO2 using Twin Sisters olivine ((Mg1.84Fe0.16)SiO4) as the

reactive silicate mineral. Results demonstrate that mineral carbonation is feasible at

subsurface storage conditions, with reaction extent reaching 7 mol% carbonated over

94 days. The reaction rate is strongly affected by silicic acid concentration, [H4SiO4],

and decreases two orders of magnitude as H4SiO4 approaches amorphous silica

(SiO2(am)) saturation, but remains constant for up to 94 days after that at a rate of 8±2

x 10-14

mol cm-2

s-1

. During the time frame of these experiments, the rate does not

depend strongly on pH.

We consistently observed that a Si-rich layer forms on reacted olivine grains in

less than 2 days, persists for 94+ days, and increases in thickness with reaction extent.

A high-resolution transmission electron microscopy (HR-TEM) study of mineral

cross-sections showed two distinct types of amorphous surface layers, both rich in Si

vi

(or depleted in Mg). Analysis of olivine reacted with a 29

Si isotopic tracer using a

Sensitive High Resolution Ion Microprobe Reverse Geometry (SHRIMP-RG) resulted

in strong evidence for the presence of a precipitated layer on olivine reacted for 19+

days but not on olivine reacted for 2 days.

Observations from the HR-TEM and SHRIMP-RG studies allowed us to

generate a new model for the formation of Si-rich layers on multi-oxide silicate

minerals. Previous studies have suggested either a leached surface layer or a

precipitated surface layer. In contrast, we have evidence that both types of surface

layers occur simultaneously. The leached or "active" layer forms in the first hours to

days of reaction and persists for 19+ days; the removal of Mg and Si from this layer

controls the bulk dissolution rate. The precipitated layer forms after the bulk solution

reaches saturation with respect to am-SiO2 and grows in thickness as the reaction

continues at a constant rate, suggesting that it is does not passivate the surface. New

knowledge linking the measured dissolution rate with surface dynamics is useful for

the design of an engineered system for subsurface (or ex situ) carbon storage. The

model presented here for Si-rich surface layer formation on olivine may be applicable

to other multi-oxide silicate minerals, providing a new framework for geochemical

models that include mineral dissolution.

vii

Acknowledgements

I begin by expressing my sincere gratitude to my primary dissertation advisor,

Professor Gordon E. Brown, Jr. for his guidance, advice, and support during my time

at Stanford. Gordon's combination of an astute attention to detail and impressive

ability to see "the big picture" greatly helped me achieve focus by both motivating me

to believe in my work and helping me to understand the importance of detail in

scientific work. I'm grateful that he took me in to his research group despite my

woeful lack of geological background and shared with me a piece of his incredible

breadth and depth of geochemical knowledge. Countless times I walked into his office

confused about my data thinking "this time I'm going to stump him for sure" and each

time, he was able to suggest a reference (sometimes quite obscure) to help me find my

way. I also owe a great amount of thanks to Professor Kate Maher, who was always

willing to listen to my ideas, answer my questions, and help me work through topics

that were new to me. Kate patiently walked me through a long list of calculations and

geochemical models and seemed to always have time to help me, even when her

schedule was clearly packed.

Dr. Robert Rosenbauer and Dr. Burt Thomas at the US Geological Survey

were invaluable in teaching me how to perform experimental work. Burt learned how

to operate the lab as a post-doctoral scholar at about the time I began graduate school,

and he helped me establish lab procedures that I would follow for the remainder of my

PhD work. Bob provided useful advice and tips for running successful experiments,

gleaned from decades of experience working in the "rocker" lab. I'm grateful to

Professor Dennis Bird for providing guidance on experimental conditions, as well as

for his many helpful consultations on both geochemical modeling and manuscript

drafts. Professor Tom Jaramillo was my co-advisor in Chemical Engineering, and

while I didn't have much contact with him during my PhD work, I'm grateful to him

for his assurance early in my graduate career that he would be my advocate within the

chemical engineering department, should I need it (thankfully I didn't). Finally, my

work at Stanford would not have been possible without a generous grant from the

Global Climate and Energy Program (GCEP) at Stanford, for which I am very

viii

appreciative.

While I have already mentioned all the members of my reading committee, I

would like to acknowledge them separately here. Thank you to Gordon, Kate, Bob,

and Tom for helping me put years of work into a cohesive story and for your ideas and

comments on this dissertation. I would also like to thank Professor Sally Benson for

serving as my committee chair, her years-long support of our project, and for the

conversations she and I have had at various GCEP events.

Without support from friends, my graduate career would have been much more

difficult. I'm grateful to members of my chemical engineering class, who provided

both emotional and intellectual support during our first year of classes, research

rotations, and the pre-qualification and qualification exams. The members, past and

present, of the Brown and Maher research groups have shared many ideas, hours in

lab, and beers with me over the years, for all of which I am thankful. Thank you also

to the various roommates I've had over the years--having a welcoming community at

home greatly helped sustain a social life, even when research consumed many hours

per day. I'm grateful especially for the time spent in the beautiful California wilderness

and the people who traveled there with me, from chemical engineering friends to

housemates to fellow instructors from the Outdoor Education Program at Stanford.

Finally, college friends who I've kept in touch with have been a wonderful extended

support system as well as a welcome connection with life outside of graduate school.

I also would like to thank my family for their unconditional love, and support.

My parents especially encouraged me to apply to graduate school then accept the offer

from Stanford, despite its distance from their home in Massachusetts. I'm grateful for

the many hours they have spent listening to me talk about the frustrations of research

as well as their enthusiasm in celebrating my successes. I'm also thankful that my

brother, as a fellow chemical engineer, is often willing and excited to "talk shop" with

me.

This section would be woefully incomplete without the inclusion of my fiancé,

Ariel. Ariel has been a major force in my life for most of my time at Stanford. He has

the uncanny ability to know when I need a hug versus when I need a push, and without

ix

his unwavering belief in me, my work would be much weaker than it is today.

Together we adopted a dog, named Bear, and I can't express how wonderful it is to

return home to a slobbery, furry monster who's love is totally ignorant of the

difficulties of experimental work. Ariel is my teammate, my coach, my loudest

supporter (sometimes all at once!) and I love him very much.

xi

Table of Contents

Abstract ....................................................................................................................... v

Acknowledgements ...................................................................................................vii

Table of Contents ....................................................................................................... xi

List of Tables .......................................................................................................... xiii

List of Figures .......................................................................................................... xiv

Chapter 1: Introduction to mineral carbonation as a subsurface carbon storage

mechanism .................................................................................................................. 1

1.1 Climate Change .................................................................................... 2

1.2 Carbon Capture and Sequestration (CCS) ............................................. 3

1.3 Mineral Carbonation ............................................................................. 7

1.4 Objectives .......................................................................................... 12

1.5 Summary of Chapters ......................................................................... 13

1.6 References .......................................................................................... 17

Chapter 2: Olivine dissolution and carbonation under conditions relevant for in situ

carbon storage ........................................................................................................... 23

Abstract...................................................................................................... 24

2.1 Introduction .......................................................................................... 25

2.2 Materials and Methods ......................................................................... 29

2.3 Results ................................................................................................. 35

2.4 Discussion ............................................................................................ 42

2.5 Conclusions .......................................................................................... 54

2.6 Acknowledgments ................................................................................ 56

2.7 References ............................................................................................ 57

Chapter 3: The role of the Si-rich surface layer in olivine dissolution 1: High-

resolution TEM study ................................................................................................ 63

Abstract...................................................................................................... 64

3.1 Introduction .......................................................................................... 65

3.2 Methods ............................................................................................... 68

3.3 Results ................................................................................................. 73

3.4 Discussion ............................................................................................ 77

3.5 Conclusions .......................................................................................... 90

3.6 Acknowledgments ................................................................................ 93

3.7 References ............................................................................................ 94

Chapter 4: The role of the Si-rich surface layer in olivine dissolution 3: Spatially and

temporally resolved ................................................................................................... 99

xii

incorporation of an isotopic tracer (29

Si).................................................................... 99

Abstract ................................................................................................... 100

4.1. Introduction ...................................................................................... 101

4.2. Methods ............................................................................................ 103

4.3. Results .............................................................................................. 109

4.4. Discussion ........................................................................................ 114

4.5. Conclusions ...................................................................................... 129

4.6 Acknowledgments ............................................................................. 131

4.7 References ......................................................................................... 132

Appendix 1: The role of the Si-rich surface layer in olivine dissolution 2: A spatially

resolved surface kinetic model ................................................................................ 137

Abstract ................................................................................................... 138

A1.1. Introduction.................................................................................... 140

A1.2. Methods ......................................................................................... 144

A1.3. Results ........................................................................................... 148

A1.4. Discussion ...................................................................................... 150

A1.5. Conclusions.................................................................................... 171

A1.6. Acknowledgments .......................................................................... 173

A1.7. References ..................................................................................... 174

Appendix 2: Experimental Protocols ....................................................................... 179

A2.1 Gold Bag Preparation ...................................................................... 179

A2.2 Repairing Gold Bags ....................................................................... 181

A2.3 Improving the seal between Au bag and Ti collar ............................ 182

A2.4 Assembling the reactor .................................................................... 184

A2.5 Sampling ......................................................................................... 194

A2.6 Taking down an experiment ............................................................ 196

A2.7 Other Procedures ............................................................................. 198

A2.7.1 Using the Furnace ..................................................................... 198

A2.7.2 Pressurization System ............................................................... 199

A2.7.3 Coulometer Operation ............................................................... 201

Appendix 3: Redox State of Reaction ...................................................................... 203

Appendix 4: Derivation of diffusion coefficient from Lasaga (1979). ...................... 205

xiii

List of Tables

Table 2.1: Experimental data for four experiments. .................................................. 34

Table 2.2: Experimental data for four experiments. .................................................. 37

Table 2.3: Geometric surface area-normalized reaction rates for four experiments, with

BET-normalized rates in parenthesis. ....................................................................... 41

Table 3.1: Conditions of four experiments. ............................................................... 69

Table 3.2: Solution data from four experiments ........................................................ 73

Table 3.3: Olivine dissolution rates from four experiments ....................................... 79

Table 4.1: Duration, degree of mixing, and additive concentrations for five

experiments. ........................................................................................................... 105

Table 4.2: Resin cleaning and Si purification procedure adapted from Georg et al.

(2006). ................................................................................................................... 105

Table 4.3: Steady-state dissolution and precipitation rates for 19-R and 19-S ......... 118

Table 4.4: Model parameters for 19-R and 19-S ..................................................... 125

Table A1.1: Summary of experiments from Chapters 2 and 3 used in model

development. .......................................................................................................... 144

Table A1.2: Mg isotope data for experimental olivine and experiment 3 from Chapter

2 along with average values for reference materials, where n is the number of times

the individual sample was analyzed to obtain the average value and standard deviation.

............................................................................................................................... 147

Table A1.3: Model parameters and values applied to experiments 1-4, 2R, 19S, 2S,

19S. ........................................................................................................................ 160

xiv

List of Figures

Figure 1.1: Mitigation cost increase over a base scenario when various technologies

are excluded from the mitigation portfolio for two target atmospheric CO2

concentration ranges. Scenarios without CCS are the most costly, followed by

bioenergy. Limiting solar and wind to 20% of the energy portfolio and ceasing to build

new nuclear power plants have the lest effect on mitigation cost. Adapted from

Edenhofer et al., 2014. ................................................................................................ 3

Figure 1.2: Diagram of four subsurface CO2 trapping mechanisms: physical, residual,

solubility, and mineral. Figure adapted from personal correspondence with Pablo

Garcia Del Real. ......................................................................................................... 7

Figure 2.1: X-ray diffraction patterns for unreacted and reacted olivine. Magnesite

peaks are visible in the reacted spectra . .................................................................... 31

Figure 2.2: X-ray photoelectron spectroscopy data for unreacted olivine, and olivine

reacted for 2, 4, and 74 days. The peak intensity of Mg decreases with increasing

reaction time relative to the Si peak, indicating that the mineral surface becomes more

Si-rich as the reaction progresses. ............................................................................. 32

Figure 2.3: Elemental concentrations versus time for magnesium (A), silicon (B), iron

(D), and alkalinity versus time (C) for four experiments. Insets show the same y-axis

for the initial 4 days of reaction. Experiments 1 and 2 contain 0.5 M NaCl;

Experiments 3 and 4 have 0 M NaCl. ........................................................................ 35

Figure 2.4: Images of unreacted (A, B) and reacted (C-F) olivine from Experiment 2.

Unreacted olivine grains are of uniform size. After reaction, the solids are dominated

by large (>100 µm) silica sheets (C) and many grains are partially coated with silica

(D). Magnesite nodules grow via a spiral growth pattern on the silica (coatings and

sheets) (D, F), which itself has a structure composed of fused spheres (E). EDS spectra

of magnesite nodules (F) and silica (E) are inset........................................................ 38

Figure 2.3: Saturation of magnesite (A), amorphous silica (B), and siderite (C) vs. time

as well as calculated pH vs. time (D). Data presented were calculated from

Experiments 1, 2 and 4. Saturation is presented as the logarithm of the reaction

quotient Q divided by the equilibrium constant K. Dashed lines in A-C represent

equilibrium between the solid phase and the reaction solution (logQ/K=0 at Q=K). .. 40

Figure 2.6: The rate of olivine dissolution, calculated from both Mg and Si data from

Experiment 3, decreases as the silica saturation state increases during the initial 3 days

of reaction. Non-stoichiometric dissolution occurs during the first time interval (due to

incongruent dissolution) and the last (presumably due to amorphous silica

precipitation). ........................................................................................................... 46

Figure 2.7: A: Experimental rate data (normalized to geometric surface area and

xv

calculated from Mg concentrations) as a function of pH. Deviation at the lowest pH

(first time point) is due to a combination of incongruent dissolution creating an

artificially high rate and dissolution of fine particles not removed by washing.

Experimental data, particularly from 1 and 2, do not show a pH-dependence at pH >

4.5. Horizontal uncertainty is defined by the pH values at the two data points used to

calculate each rate. For comparison, one data point from Wang and Giammar (2013) is

included. This rate was measured over 8 hours at 50 °C, 100 bars pCO2, and 0 M

NaCl; we corrected it by a factor of 40 to account for the lower forsterite concentration

in their experiments (0.5 g/L compared to our 20g/L). B: Long term (10-70 days)

dissolution rates compared to three published models for forsterite dissolution

(Pokrovsky and Schott, 2000b; Hanchen et al., 2006; Rimstidt et al., 2012). Rates

from experiments with 0.5M NaCl are consistent with the models, the rate from

Experiment 4 (no added electrolyte) is lower. All rates shown here were calculated

before Mg-carbonate precipitation occurred. ............................................................ 51

Figure 3.1: Steps of IFFT analysis. First, the TEM image is taken using the

microscope (A). The image is then transformed using a Fast Fourier Transform, which

yields a second image in the frequency domain (B). Bright spots on this image

represent periodicity, so those particular frequencies are selected and the rest are

masked (C). An Inverse Fast Fourier Transform is then applied to the masked

frequency domain image to recreate the original image showing only the regions of

periodicity (D). The periodicity in (D) is distorted due to aliasing (relatively low

resolution in the image results in a high frequency periodicity from the original image

(A) appearing to have a lower frequency). This IFFT image was then overlaid on the

original TEM image (E) and false color was added to show periodic regions and the

gold surface coating (F). ........................................................................................... 72

Figure 3.2: Mg (A) and Si (B) concentrations as a function of time for four

experiments. Amorphous silica saturation is indicated by the dashed line in (B). ...... 74

Figure 3.3: Representative TEM crystallinity maps of unreacted (A) and forsterite

from experiments 2-S (B), 2-R (C), 19-S (D) and 19-R (E). Green areas on the right of

each image are crystalline, yellow-colored regions on the left are a protective gold

layer deposited on the mineral surface (colored version online). Uncolored areas are

amorphous. The scale bar in (E) applies to all reacted forsterite (B-E). ..................... 75

Figure 3.4: TEM/EDS linescans showing Mg/Si ratio as a function of depth in

forsterite reacted without mixing (A) and with mixing (B). Forsterite from all four

experiments had a Si-rich (Mg-depleted) surface layer at least 20 nm thick. Linescans

showing Fe/Si ratios are also shown for the well-mixed experiments (C) and both have

a peak of Fe associated with the Si-rich layers. Ratios were calibrated using spectra

from deep in the mineral. .......................................................................................... 76

Figure 3.5: Forsterite dissolution rate as a function of Si-rich layer thickness. The rate

does not decrease with increasing layer thickness; in fact, within the two different data

sets (rocking vs. stationary), show that the rates increase with Si-rich layer thickness.

xvi

Error bars represent 2-sigma uncertainty due to the few (2-5) data points available for

each rate calculation. No correlation between rate and layer thickness is implied

beyond the data presented here.................................................................................. 78

Figure 3.6: Cross sectional diagram of the reacted mineral surface, specifically for

experiment 19-R. The three different Si-rich layers and their defining characteristics

are visible from top down: Precipitated layer, active layer, and Mg-depleted forsterite.

................................................................................................................................. 82

Figure 3.7: Simple diffusion model in which the diffusion coefficient, D*, is a

function of Mg concentration in addition to diffusivity of protons (DH) and of Mg

(DMg), plus a structural factor (α) (A). Decreasing from α 0 to -0.3 results in flattening

the profile, and reducing it further to -0.9 creates a minimum value of D* at c≈0.1.

Changing DMg results in a shift of the concentration gradient curve (B) and changing

DH affects both the steepness and depth of the curve (C). Data from the two 19 day

experiments can be fit with this model and different values of DH (D). Vertical bars

indicate the transition from amorphous to crystalline material, and the model was

shifted to the right to align with the “active” layer. .................................................... 88

Figure 4.1: Silicon concentrations and 29

Si/30

Si ratios as a function of time for 19-R

(A) and 19-S (B), with amorphous silica saturation plotted for comparison. Ratios of

Mg/Si vs . time (C) show that the fluid composition is elevated in Mg relative to the

mineral phase. ......................................................................................................... 110

Figure 4.2: Ratios of Mg/Si as a function of depth for 2,19-R (A) and 2,19-S(B). The

depth was calibrated using the SI-rich layer thickness as measured from TEM images

(65 nm (19-R), 40 nm (19-S), 25 nm (2-S), and 20 nm (2-R)). Isotopic ratios

(29Si/30Si) are also plotted as a function of depth for the rocking (C) and stationary

(D) experiments. Each data point is an average from at least three different forsterite

grains. ..................................................................................................................... 112

Figure 4.3: Comparison of isotopic composition of the aqueous and mineral phases for

four experiments. .................................................................................................... 113

Figure 4.4: Time-resolved Mg (A) and Si (B) concentrations for three experiments:

19-R (this study), Experiment 1 (Chapter 2), and catechol (this study). ................... 114

Figure 4.5: Dissolution rates for 19-R calculated using the isotope ratio method and

dMg/dt indicates that Mg and Si release are stoichiometric at t>5 days (A), and Si

removal rates (precipitation plus exchange) are the same within uncertainty as

dissolution rates at t> 5 days (B). The same calculations for 19-S reveal slower

dissolution and a longer transient stage (C) and precipitation begins later (D). Missing

data are either less than zero or have uncertainties that span positive and negative rates

(i.e. rates are zero within uncertainty). .................................................................... 117

Figure 4.6: Kinetic model fit to concentration data from rocking experiments (A),

xvii

stationary experiments (B), and isotope data from both experiments (C). ................ 127

Figure A1.1. Summary of previous experimental data from Chapter 2 in (A)-(C) and

Chapter 3 in (D)-(E). Vertical arrows in (A) and (D) indicate time when experiments

reached MgCO3 saturation, horizontal line with arrows indicates interval when

MgCO3 precipitation is thought to have occurred in experiment 2, based on the lack of

precipitates in experiment 1 at 74 days. Horizontal dashed lines in (B) and (E) indicate

saturation with respect to amorphous silica. Error bars represent 1 s.d. ................... 149

Figure A1.2. Magnesium isotope data for the short-term experiment 3 (no NaCl) over

3 days of reaction time. Error bars represent 1.s.d. ................................................. 149

Figure A1.3. Conceptual model for the surface kinetic model. (A) High resolution

TEM image shows the general features observed in the outer 100 nanometers of

olivine after reaction for 2 days (modified from Chapter 3), with the fluid-solid

interface to the left of the image. Average Mg/Si ratios measured by EDS are provided

for reference. The black arrows indicate the migration of the active layer into the

crystalline olivine over time, as determined by the rates of the individual reactions in

(B). (B) The conceptual model for the independent rates considered in the model and

the resulting mass balance constraints. The net rate (Rnet) is the Mg exchange rate plus

the net difference between the net <SiO2 dissolution rate and the net precipitation rate

of amorphous silica. Magnesium is removed from the active layer of volume VAL,

while >SiO2 can only be dissolved or added from the surface of the active layer. (C)

Representative HR-TEM EDS linescan of the Mg/Si ratio in reacted olivine from

experiment 19R from Chapter 3 with a Lowess curve fit (green line) compared to the

model representation (bold teal line). The grey shaded region (indicated (-)) shows the

Mg depletion relative to the assumed stoichiometric composition, while the green

shaded region (indicated (+)) shows the Mg-enrichment in the active layer relative to

model Mg/Si. To maintain mass balance the total Mg in the two zones must be equal.

............................................................................................................................... 152

Figure A1.4. Model fit to experiments 1-4. Magnesium (open symbols) and Si (closed

symbols) over the full experimental duration are shown in (A), and during the initial

incongruent dissolution phase in (B). The model fit to the combination of experiments

1 and 2 in (A) is considered the reference model. The same scheme is applied in (C)

and (D) where model results for experiments 3 and 4 are presented. The changes in

rate coefficients are indicated and the thickness of the active layer (AL, nm) is

indicated. For experiments 3 and 4, a sensitivity analysis showing variation in the AL

is provided. All experiments were conducted at 100 bar CO2 and 60˚C in the presence

of 0.5 M NaCl (Chapter 2) . .................................................................................... 162

Figure A1.5. Model fit to the combined experiments 2R and 19R (well mixed) are

shown over the full experimental duration (A), and during the initial incongruent

dissolution phase in (B). Model fit to experiments for 2S and 19S (not-well mixed)

over the same durations are shown in (B) and (C). The changes in rate coefficients

relative to the reference model are indicated. All experiments were conducted at 100

xviii

bar and 60˚C in the presence of 0.5 M NaCl (Chapter 3). ........................................ 163

Figure A1.6. Rate profiles as a function of (A) time; (B) pH; and (C) H4SiO4

concentrations for the reference model. The bar at top indicates the dominant

processes occurring from initial to steady-state dissolution. .................................... 165

Figure A1.7. Sensitivity of the steady-state dissolution rate to the individual rate

coefficients. Each rate coefficient was varied independently while the others were held

constant at the values determined for the reference model (see Table 4). The best fit to

experiments 1 and 2 is shown by the grey bar. ........................................................ 167

Figure A1.8. Model magnesium isotopic and surface layer Mg/Si evolution for

experiment 3. (A) The model change in the Mg/Si of the active layer (Mg/SiAL) is

shown in comparison to the 26

Mg of the active layer (AL) and the dissolved Mg. (B)

Comparison between model and measured 26

Mg of the aqueous Mg (uncertainties are

represented as 1 s.d.). The best fit to the data is between Mg-Fo = 0.9995 and 0.9990

and variations in Mg-Fo are shown for reference. ..................................................... 169

Figure A1.9. Model evaluation of Wimpenny et al. (2010) experimental series FO2 at

pH 3 and 25 ˚C. (A) Model fit for Mg and Si concentrations (see parameters in Table

4), (B) Comparison between measured 26

Mg to model prediction using Mg-Fo =

0.999....................................................................................................................... 170

Figure A2.1: Gold bag assembly. From left to right: gold bag with Ti collar, Au/Ti

filter in Ti head with attached sampling tube, washer, flanged compression cap

containing thrust bolts. ............................................................................................ 179

Figure A2.2: Stainless steel pressure vessel with steel head, gasket, and thrust bolts.

The gold reaction cell is contained in the vessel and surrounded by a pressure fluid (DI

water). .................................................................................................................... 186

Figure A2.3: Assembling the reactor vessel. A. Attaching the sampling valve (step 8).

B. Full assembled reactor. C. Completed support structure, top view. Potential leak

points are visible in B and C. If the leak is below the valve (B), tighten the bolt

connecting the valve to the tube. If the leak is visible from a top view (C), tighten

accessible bolts and retest. Disassembly may be required. ....................................... 188

Figure A2.4: View of 4 rocking furnaces (A) showing temperature controls and

variacs. Zoomed in image of temperature controls (B) shows the temperature read-out,

power switch, and fuse for each of the four furnaces. .............................................. 192

Figure A2.5: Sampling syringe with 3-way valve, attached to sampling port. The

sampling port consists of a stainless steel, 5/8" bolt with a teflon insert, and plastic

tubing connects the insert to the 3-way valve. ......................................................... 195

Figure A2.6: Pressurization system on the pressure bench. Valves across the front are

xix

labeled (left to right): Bleed, Pump, Reservoir, Rack 3, Rack 4, Workbench. Analogue

pressure gauge hangs above the valves. The Reservoir sits below the bench and has its

own gauge. ............................................................................................................. 200

Figure A2.7: Gas delivery system for the coulometer. Sample is injected at 3-way

valve. ..................................................................................................................... 201

Figure A3.1: Element concentration (A) and H2 pressure (B) as a function of time. 203

1

Chapter 1: Introduction to mineral carbonation as a subsurface carbon storage mechanism

Natalie C. Johnson

2

1.1 Climate Change

Recent reports from the Intergovernmental Panel on Climate Change

(Edenhofer et al., 2014) and the US Global Change Research Program (Melillo et al.,

2014) emphasize both the potential large-scale impacts of climate change and the

immediate need for implementation of technologies to mitigate such impacts. Climate

change is caused by high concentrations of so-called "greenhouse gases" such as CO2,

methane, and water in the atmosphere, which let sunlight pass through the atmosphere

but trap heat that would otherwise escape. Natural sources of greenhouse gases do

exist, but recent climate models suggest that the recent upward trend of global average

temperature cannot be explained by natural sources alone, the model must also include

anthropogenic sources (Huber and Knutti, 2012). Increasing levels of greenhouse

gases in the atmosphere are already affecting our climate; from rising sea levels to

melting ice sheets (Joughin et al., 2014), and rising temperatures to increasing

numbers of large storms (Melillo et al., 2014). Other consequences include increases

in U.S. summer time ozone concentrations of up to 70% by 2050 (Pfister et al., 2014)

and ocean acidification from increased dissolved CO2 (Melillo et al., 2014). Whereas

there are many unequivocal observations that our climate is already changing (e.g.

Melillo et al., 2014), reduction of emissions of CO2 and other greenhouse gases today

would reduce future changes.

Given the global scale of climate change, it's unlikely that any single

technology will have an impact large enough to sufficiently mitigate climate change

worldwide, where "mitigate" is defined as reducing the sources or improving the sinks

of CO2 and other greenhouse gases. Instead, a suite of technologies in a variety of

fields like power production, transportation, energy use, and land use will be needed.

In fact, a comparison of CO2 mitigation scenarios in which specific technologies are

excluded shows that carbon capture and storage (CCS) and bioenergy are perhaps the

most important technologies, because mitigation may cost up to 300% more than a

base scenario when one or both are not a part of the mitigation strategy (Fig. 1.1)

(Edenhofer et al., 2014). One reason that biofuels and CCS are so important is the

prediction that the carbon intensity of energy sources worldwide is expected to remain

3

constant for the next 100 years (Edenhofer et al., 2014). Thus, technologies that either

directly replace (e.g. biofuels in the transportation sector) or lower the greenhouse gas

emissions of carbon-intensive energy (e.g. CCS on carbon-based electricity generation

facilities) are essential to successful CO2 mitigation.

1.2 Carbon Capture and Sequestration (CCS)

One potential technology to mitigate climate change involves capturing carbon

dioxide from point sources (i.e. power plants, cement plants) and injecting it into the

subsurface. Storing CO2 in the subsurface rather than emitting it to the atmosphere

could substantially reduce the rate at which atmospheric CO2 concentrations are

increasing and thus reduce the probability of catastrophic climate change. Technology

Figure 1.1: Mitigation cost increase over a base scenario when various technologies are

excluded from the mitigation portfolio for two target atmospheric CO2 concentration

ranges. Scenarios without CCS are the most costly, followed by bioenergy. Limiting solar

and wind to 20% of the energy portfolio and ceasing to build new nuclear power plants

have the lest effect on mitigation cost. Adapted from Edenhofer et al., 2014.

4

for safe injection of CO2 into the subsurface already exists, and oil companies have

been using it to improve oil yields for decades as one component of enhanced oil

recovery (EOR). Currently, oil companies use CO2 extracted from the subsurface in

EOR processes, but the potential exists for waste CO2 to be used instead (Latil, 1980).

Also, CO2 could be injected into other types of rocks that do not host oil, such as

saline aquifers (sedimentary deposits) or igneous complexes (such as basalt).

The first step of CCS is the capture of CO2 from point sources such as power

plants. While much research regarding technologies for carbon capture is underway,

this document will not explicitly address the topic of capture. However, successful

carbon capture is essential to carbon sequestration, so it bears mention here.

After capture from a point source (e.g. coal or natural gas power plant), carbon

dioxide is injected as a compressed liquid (or co-injected with water to form a single,

aqueous phase (Gislason et al., 2010)) through cement-lined wells to depths of at least

800 m, but more often 1.2 to 2.5 km (Hosa et al., 2010), where the CO2 becomes a

supercritical fluid. In the case of co-injection, the carbonated water may be injected to

shallower depths, ranging from 400-700 meters (Oelkers et al., 2008). The rocks into

which CO2 is injected must be porous (or have induced permeability), and their pores

contain water, dissolved species such as NaCl, and possibly oil/natural gas if the

region is a depleted oil field. CO2 spreads from the injection point and fills the pores,

mobilizing the water (and oil, if present, which can then be removed from the

subsurface at extraction wells). Technological hurdles to large-scale implementation

of subsurface carbon storage remain, and center around long-term stability,

monitoring, induced seismicity, and water quality concerns. Other, non-technical

obstacles include the high cost of CCS, long-term liability disputes, and land rights

(Wilson et al., 2007).

The goal of CCS is to store CO2 in the subsurface for hundreds to thousands of

years, but supercritical CO2 is less dense than water and thus acts as a buoyant fluid.

Leakage to the atmosphere represents wasted effort and thus must be minimized. In

order to contain CO2 in the subsurface, one or more physical "caps" must be present

above the reservoir into which the CO2 is injected. However, leakage may still occur

5

through cracks in the caprock or old wells that were improperly retired (Wilson et al.,

2007). Site selection is very important to minimize the leakage potential, and several

levels of monitoring will be necessary to detect leaks and potential leaks early so that

they can be fixed before substantial volumes of CO2 are lost. CCS monitoring is

another area of current research, and potential technologies include gravity monitoring

(Alnes et al., 2011), surface monitoring (Madsen et al., 2009), and dissolved inorganic

carbon measurements of subsurface reservoirs (Romanak et al., 2012).

Other potential hazards caused by subsurface carbon storage include induced

seismicity with earthquakes up to magnitude 4.5 (Cappa and Rutqvist, 2011) and loss

of water quality (Little and Jackson, 2009). Both of these hazards can be prevented by

proper well construction and reservoir pressure monitoring. Induced seismicity occurs

when the pressure inside the reservoir exceeds a critical value, most likely causing

nearby faults to slip (Cappa and Rutqvist, 2011). A thorough understanding of the

horizontal and vertical stress applied to the caprock and avoidance of active faults plus

monitoring the reservoir pressure during injection will reduce the probability of large

seismic events. Water quality degradation is another potential effect of induced

seismicity, if a fault opens that connects the injection reservoir with a reservoir that

contains drinking water. Generally injection reservoirs are several thousand feet deep,

while drinking water reservoirs are only hundreds of feet deep, so the larger concern

with water quality relates to leakage through the well casings. In either case, leakage

of CO2 into drinking water may reduce the pH of the reservoir and induce

geochemical reactions which can result in increasing concentrations of heavy metals

such as arsenic (Little and Jackson, 2009). Regulations surrounding well construction

would reduce the risk of leakage through the wells themselves.

Non-technical challenges surrounding CCS center around cost, but also include

land rights and assignment of long-term liability (Wilson et al., 2007). First of all,

CCS is expensive, and as long as power plants can emit CO2 freely, they have no

economic incentive to invest in CCS. Research on new technologies may decrease the

cost of CCS, but regulation will almost certainly be necessary to make CCS

economically beneficial relative to releasing CO2 as a waste gas to the atmosphere.

6

Land rights are also a potential issue and the way that rights are assigned to the

subsurface varies by state (Klass and Wilson, 2009). However, subsurface land rights

issues have existed for many successful industries, from gold mining to oil extraction,

so they are not insurmountable. Finally, long-term liability is an unresolved issue.

Carbon Capture and Sequestration is ideally a very long-term project (hundreds to

thousands of years), and assigning liability to a company for that length of time is not

practical. It's possible that liability could rest with the injecting entity for some length

of time, then shift to the public (governmental agencies), but questions remain about

who would be responsible for the clean-up of a injection site that leaks hundreds of

years after injection (and likely after the injecting company no longer exists) (Wilson

et al., 2007). However, reducing the likelihood of leakage would make the liability

issue less prominent.

Once CO2 is in the subsurface, storage occurs via a variety of mechanisms

listed here from first (and least stable) to last (and most stable) and shown in Fig. 1.2.

Physically containing CO2 under an impermeable caprock is known as "physical

trapping" and is necessarily the first of four trapping mechanisms to occur. Thus, any

reservoir that is a candidate for subsurface storage must have several layers of

impermeable rock above the injection region in order to physically trap the buoyant

fluid. The second trapping mechanism begins to occur immediately, but becomes

increasingly important with time and is called "residual trapping." In this mechanism,

capillary forces trap CO2 in rock pores. "Solubility trapping" is the third mechanism

and describes the dissolution of CO2 into the aqueous phase, resulting in carbonic acid,

bicarbonate ions, carbonate ions, and protons. This will be discussed in detail later.

Finally, the last mechanism is "mineral trapping," which is the focus of this

dissertation. Mineral trapping occurs when dissolved CO2 reacts chemically with

dissolved cations, such as calcium, magnesium, and iron, to make carbonate minerals.

This last mechanism is the most stable over thousands to millions of years because the

CO2 is trapped as a non-buoyant solid. Under certain conditions (e.g. acidic fluids)

carbonate minerals do dissolve, but the probability of leakage is much lower if the

bulk of the CO2 injected is converted to minerals.

7

Thus, optimizing CO2 injection for mineral trapping by choosing rocks rich in

divalent cations (Ca, Mg, Fe) and with sufficient porosity and surface area may

minimize risks and costs associated with subsurface carbon sequestration. Successful

mineral trapping of CO2 may simplify liability issues, reduce public concern over the

safety of injection, and increase the effectiveness of long-term storage relative to

injection in rocks that are ill-suited for mineral trapping.

1.3 Mineral Carbonation

Mineral carbonation describes the series of chemical reactions that make up

"mineral trapping," the fourth and most stable trapping mechanism that occurs in

subsurface carbon storage. In short, host rocks dissolve in formation water, releasing

divalent cations (Ca, Mg, Fe) that react with dissolved CO2 (carbonate and bicarbonate

anions) to form solid carbonate minerals. Carbonate minerals are thermodynamically

stable; in fact, they are the most stable form of carbon. However, the kinetics of the

Figure 1.2: Diagram of four subsurface CO2 trapping mechanisms: physical,

residual, solubility, and mineral. Figure adapted from personal correspondence

with Pablo Garcia Del Real.

8

reaction are slow relative to industrial timescales. Other technical challenges involve a

large volume change of the reaction (the products are 92% larger in volume than the

reactants) and potentially passivating surface layers that form on the host minerals.

Each step of the process is described in detail in the following sections.

1.3.1 Olivine ((Mg,Fe)2SiO4) Dissolution

In order for mineral carbonation to occur, the host rocks must first release

divalent cations through a dissolution process. Silicate mineral dissolution has been

studied for many decades in order to understand surface weathering processes, but

only recently have researchers begun studying mineral dissolution at elevated

temperature and CO2 pressure, the conditions that define a subsurface storage

scenario. The dissolution rate of olivine (and multi-oxide silicate minerals in general)

increases with increasing temperature and decreasing pH (Blum and Lasaga, 1988;

Chen and Brantley, 2000; Giammar et al., 2005; Hänchen et al., 2006; Olsen and

Rimstidt, 2008; Pokrovsky and Schott, 2000a; Prigiobbe et al., 2009; Rimstidt et al.,

2012; Shirokova et al., 2012; Wang and Giammar, 2013; Welch and Banfield, 2002;

Wogelius and Walther, 1992, 1991). The addition of CO2 may enhance the reaction,

perhaps due to pH effects (Golubev et al., 2005; Wang and Giammar, 2013), though

others have found that bicarbonate ions directly enhance the rate of carbonation (Chen

et al., 2006). More data on olivine dissolution in the presence of CO2 must be

generated before the effect of CO2 can be accurately quantified.

During the dissolution of olivine (as well as other multi-oxide silicate

minerals), a Si-rich phase forms on the reacting mineral surface (Bearat et al., 2006;

Daval et al., 2011; King et al., 2010; Pokrovsky and Schott, 2000a; Sissmann et al.,

2013; Zakaznova-Herzog et al., 2008). There are two, competing theories for the

formation mechanism of this layer. The first theory is that it forms via a leaching

process, in other words, Mg (and other cations) are released preferentially and residual

silicon tetrahedra rearrange and polymerize to form the surface layer (Hellmann et al.,

1990; Pokrovsky and Schott, 2000b; Ruiz-Agudo et al., 2012; Zakaznova-Herzog et

al., 2008). Alternatively, the surface layer could be formed via a

dissolution/reprecipitation process, in which the mineral dissolves congruently but

9

local areas of high H4SiO4 result in precipitation of amorphous silica at the mineral

surface (Hellmann et al., 2013, 2012; King et al., 2011, 2010). There is also

disagreement about the extent to which the Si-rich layer passivates the olivine surface,

with some studies observing near complete termination of dissolution (Daval et al.,

2011, 2009; Hellmann et al., 2012) and others seeing continued dissolution even in the

presence of thick surface layers (King et al., 2010).

Finally, ferrous iron makes up 5-15% of the cation sites in the mineral olivine,

and may play an important role in olivine dissolution. For example, Fe2+

may oxidize

to Fe3+

during the reaction and then stabilize the Si-rich layer and slow the reaction

(Saldi et al., 2013; Sissmann et al., 2013). As the reaction progresses and conditions

become more reducing, the ferric iron may reduce back to ferrous iron, which is

associated with the rapid dissolution of the Fe-phase and resumption of olivine

dissolution (Sissmann et al., 2013).

1.3.2 Carbon Dioxide Dissolution and Dissociation

When carbon dioxide and water are in contact with each other, some CO2

dissolves into the aqueous phase and some water evaporates into the CO2 phase. At

equilibrium, the net concentrations of CO2 in water and water in CO2 remain constant,

though exchange continues to occur. The amount of dissolved CO2 depends on the

pressure and temperature of the system as well as the ionic strength of the aqueous

phase. The solubility increases with increasing pressure, but decreases with increasing

ionic strength (Duan and Sun, 2003). The solubility generally decreases with

increasing temperature, though at very high pressure (>200 bar), there exists a

solubility minimum at a temperature around 350 K and solubility increases at lower

and higher temperatures (Duan and Sun, 2003). When considering conditions relevant

for mineral carbonation, one can assume that CO2 solubility decreases with increasing

temperature.

After dissolving in water, CO2 molecules are hydrated to form carbonic acid,

H2CO3. Carbonic acid then dissociates to form protons (H+), bicarbonate ions

(HCO3-), and carbonate ions (CO3

-2). The relative concentrations of ions are

determined by equilibrium constants, which like the solubility, depend on temperature,

10

pressure, and ionic strength, though the relationships are not monotonic. The

equilibrium constants can be calculated using a model (Li and Duan, 2007) and then

used to calculate the equilibrium pH. The addition of CO2 to water causes the pH to

drop and the carbonate system acts as a pH buffer.

1.3.3 Secondary Phase Precipitation

Dissolution of silicate minerals can result in precipitation of several secondary

phases. If, as in the case of olivine, the mineral consists of only divalent cations and

silicon tetrahedra, the secondary phases are limited to metal-carbonate minerals and

silicon dioxide. If aluminum is present, clay minerals may precipitate instead of silica

and could incorporate reactive divalent cations. An advantage of performing

experiments with a relatively simple mineral such as olivine is that the complexity of

secondary phases is greatly reduced to only two phases: silicon dioxide and Mg-

carbonate. The Mg-carbonate could be present as hydrated minerals (e.g.

Hydromagnesite, Nesquehonite) or an anhydrous form (Magnesite). Silicon dioxide is

generally present as amorphous silica in low-temperature systems, where it's solubility

is low relative to other silicate minerals (Steefel and Van Cappellen, 1990) and

precipitation kinetics of less soluble SiO2 phases are prohibitively slow. Other possible

secondary phases include phyllosilicate minerals (Hellmann et al., 2013) such as

serpentine minerals (King et al., 2010; Lafay et al., 2014), especially at higher

temperatures (Sissmann et al., 2013).

Magnesite precipitation is slow at temperatures relevant for subsurface carbon

storage and has been hypothesized to limit the rate of conversion of olivine to

magnetite (Saldi et al., 2012). The rate increases with increasing temperature and

increasing saturation state and appears to be controlled by a spiral growth mechanism

(Saldi et al., 2012). However, conversion of Mg-silicates to magnesite has been

observed by several studies at a range of temperatures (Felmy et al., 2012; Giammar et

al., 2005), though at temperatures below 50 °C an intermediate, hydrated carbonate

mineral may form first and then transform to magnesite (Felmy et al., 2012;

Hopkinson et al., 2008).

11

1.3.4 Ex situ vs. in situ mineral carbonation

Mineral carbonation could be completed via an ex situ or an in situ process,

both processes have advantages and disadvantages. Ex situ mineral carbonation would

occur in an industrial facility and use an engineered process to achieve maximum

conversion of silicate minerals to carbonate minerals at an optimized cost and

conversion time. However, the silicate minerals would require extraction and transport

to the facility. The scale of the required mining operation is mammoth; an average

coal fired power plant that generates 4 MW of electricity per year would require 6.4

Mt of forsterite to mineralize all the CO2 produced (Oelkers et al., 2008). In addition,

large amounts of magnesite would be produced (2.4 Mt in the example above,

(Oelkers et al., 2008)), which would need to be disposed of and would likely contain

traces of heavy metals found in olivine, such as chromium and nickel. One result of

the mining and disposal needed for successful ex situ carbonation is an increased cost

in electricity by up to 370% (Giannoulakis et al., 2014). Life cycle assessments of ex

situ mineral carbonation repeatedly find that though it succeeds in reducing

greenhouse gas emissions, the net environmental effect is negative (Bodénan et al.,

2014; García-Gusano et al., 2013; Giannoulakis et al., 2014). The expected cost of an

optimized process for ex situ mineralization ranges from $54-$427 per ton of CO2,

depending on process considerations and the feedstock used (O’Connor et al., 2004).

Engineering an efficient ex situ mineral carbonation process is more feasible

than an in situ process because every step can be carefully controlled; however, the

negative outcomes associated with ex situ mineralization make it unappealing for large

scale CO2 storage. On the other hand, in situ mineralization has the potential to be less

expensive and have fewer negative impacts on the environment and human health

(Bodénan et al., 2014) because CO2 is transported to injection sites via pipelines and

injected directly into the subsurface. Site selection for in situ storage is critical, as the

subsurface must contain rocks with both divalent cations and sufficient permeability

for injection (Oelkers et al., 2008). Disadvantages of in situ storage surround a lack of

process control and difficulty predicting the fate of injected CO2 (e.g. time required for

complete mineralization, surface area requirements for successful reaction, etc.).

12

Site selection is key for successful in situ mineral carbonation. For example,

mineralization of 90 kg of carbonate per cubic meter of sandstone could take 100,000

years, though the rate depends heavily on the primary silicate minerals present in the

reservoir (Xu et al., 2005). On the other hand, mafic rocks such as basalt neutralize

carbonic acid and precipitate carbonate minerals more readily than sedimentary rocks

because of the relatively high concentration of divalent cations and low silica content

(Matter et al., 2007). Basalt, an igneous rock formed by rapidly cooled lava and

consisting of less than 20% quartz, makes up only 10% of the earth's surface but

accounts for 30-35% of CO2 uptake by natural weathering due to its reactivity (180 Mt

CO2/year) (Dessert et al., 2003). In summary, basalt is a highly reactive rock that is

very prevalent (it makes up much of the seafloor in addition to 10% of the continental

surface) and has the potential to mineralize large volumes of carbon dioxide.

In order to engineer an efficient, subsurface, in situ mineral carbonation

project, the kinetics of the reaction must be fully understood and the transport

considerations of the injection site must be well researched. Only then can knowledge

about transport and reaction kinetics be combined into reactive transport models,

which will allow for prediction of the fate of injected CO2 in potential storage

reservoirs.

1.4 Objectives

The major objective of this dissertation is to address questions surrounding

dissolution and carbonation rates of olivine under conditions relevant to subsurface

carbon storage; in particular, to quantify the reaction rates and improve our

understanding of the reaction mechanisms. This broad objective is divided into three

parts, each presented in a separate chapter.

1. Olivine dissolution and carbonation under conditions relevant for in

situ storage (Chapter 2)

Determine the dissolution and carbonation rates of olivine in batch

reactors over long times (3+ months), simulating a sub-surface storage

scenario. Establish experimental and analytical procedures that allow

13

for reproducible data.

2. Role of the Si-rich surface layer in olivine dissolution (Chapter 3)

Study the Si-rich surface layer that forms during olivine dissolution by

performing high-resolution transmission electron microscopy on cross-

sections of reacted mineral grains. Determine if surface layer passivates

the mineral surface and if the reaction rate is affected by mixing.

3. Formation mechanism(s) of Si-rich layer (Chapter 4)

Investigate the formation mechanism of the Si-rich layer using an

isotopic tracer. Calculate more precise dissolution and precipitation

rates using isotope dilution rates, which can be used to constrain a

novel kinetic model of olivine dissolution.

The work presented here has led to an improved understanding of the mechanisms that

control olivine dissolution and carbonation rates under subsurface storage conditions.

The rates measured as a part of this work are applicable to olivine only, which serves

as a model mineral for mafic and ultramafic rocks, but the mechanistic observations

may be generally applicable to multi-oxide silicate mineral dissolution.

1.5 Summary of Chapters

This dissertation is presented as a collection of chapters, each of which is a

manuscript that is either published, submitted, or in preparation for submission for

publication in a scientific journal. As such, each chapter has its own abstract,

introduction, methods, results, discussion, conclusions, and references section. I am

the first author on the three manuscripts and the work presented here was

predominantly completed by me, with contributions from coauthors appropriately

cited. This dissertation also includes four appendices, including a manuscript that

describes a model built on my experimental results (on which I am the second author)

and a detailed description of laboratory protocols developed during the process of

performing experimental work. The chapters and appendices are summarized below.

14

Chapter 2: Olivine dissolution and carbonation under conditions

relevant for in situ storage

Two, reproducible experiments performed at 60 °C, pCO2=100 bar, and

lasting 74-94 days yielded a long term, steady-state olivine dissolution

rate of 1.69±0.23 x 10-12

mol cm-2

s-1

(normalized by geometric surface

area) that is constant with slowly increasing pH (pH=4.5-5.5). The

dissolution rate is initially two orders of magnitude higher, but

decreases as the reaction solution approaches saturation with respect to

amorphous silica. Magnesite precipitation was observed in the 94 day

experiment but not the 74 day experiment; significant oversaturation of

that phase is required for precipitation at the reaction conditions.

Chapter 3: HR-TEM study of Si-rich layer formation during olivine

dissolution

A suite of four experiments designed to investigate the effect of mixing

on the dissolution rate and the effect of time on the Si-rich surface layer

was performed under the same conditions as in Chapter 2. Reacted

olivine cross sections were studied using high-resolution transmission

electron microscopy to quantify the chemistry and crystallinity of the

surface layer. Several different Si-rich layers were observed

simultaneously: a porous, amorphous, very Mg-depleted precipitated

layer up to 45 nm thick; an amorphous layer up to 25 nm thick with a

Mg/Si ratio that changes with depth; and a crystalline, Mg-depleted

region (only in the mixed experiments). Mixed experiments reacted 5

times faster than unmixed experiments, but the surface layers that

formed in both types of experiment were very similar.

Chapter 4: Spatially and temporally resolved incorporation of an

isotopic tracer (29

Si)

The same experiments discussed in Chapter 3 were reacted with a

solution containing an isotopic tracer (29

Si), which was tracked in both

the aqueous and solid phases to determine its fate. Precise calculations

15

of olivine dissolution and amorphous silica precipitation rates were

based on the dilution rate of the tracer by Si from the olivine. Uptake of

the tracer was greater in experiments that exceeded amorphous silica

saturation, leading to the conclusion that secondary phase precipitation

occurs only when the bulk fluid is saturated with respect to that phase.

Measured rates and other experimental parameters are used as inputs to

a novel kinetic model that describes multi-oxide silicate dissolution. A

complexing agent (Tiron, a catechol derivative) was added to one

experiment and improved the steady-state dissolution rate by a factor of

two.

Appendix 1: A spatially resolved kinetic model

New results on Mg isotope fractionation during olivine dissolution are

presented and data from chapters 2-4 were compiled in order to develop

a new model for silicate mineral dissolution. Constraints for the model

are provided by time-resolved Mg and Si concentration data from eight

experiments, TEM results, Mg isotope measurements, and Si isotope

measurements. The model describes the olivine surface as a series of

layers, and the dissolution rate is controlled by both the removal of Mg

from the "active" layer volume and the removal of Si from surface sites

at the "active" layer-precipitated layer interface. Fits of experimental

data show that the model reproduces experimental trajectories from a

range of experiments over both the short and long-term.

Appendix 2: Laboratory protocols

Experiments were performed at the United States Geological Survey in

Menlo Park, CA, in the Water-Rock Interaction Laboratory. The

primary experimental equipment used was the Dickson-style "Rocker

Bomb" and using and maintaining this equipment requires substantial

knowledge and effort. This appendix compiles all of the methods

developed for successfully performing experiments, from cleaning and

16

repairing gold reaction cells to troubleshooting leaks in the pressure

vessel.

Appendix 3: Constraints on redox state of reaction

Supercritical CO2 samples were analyzed for hydrogen concentration,

which can then be used to calculate the redox sate of the reaction and

the theoretical relative concentrations of Fe2+

and Fe3+

. This work

allows for the comparison with literature that suggests Fe3+

may

stabilize the Si-rich layer. This appendix contains preliminary data on

the reduction potential of experiments as a function of time.

Appendix 4: Derivation of Diffusion Coefficient from Lasaga (1979)

Lasaga (1979) describes diffusion coefficients for interdiffusion of

protons and monovalent cations (e.g. sodium) in glasses, and provides a

governing equation that can be applied to di- and trivalent cations. In

this section, I derive the expression for Mg2+

/ H+ interdiffusion.

17

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Guyot, F., Boukary, a., Tremosa, J., Lassin, a., Gaucher, E.C., Chiquet, P.,

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18

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23

Chapter 2: Olivine dissolution and carbonation under conditions relevant for in situ carbon storage

Natalie C. Johnsona,*

, Burt Thomasb, Kate Maher

c, Robert J. Rosenbauer

b,

Dennis Birdc, and Gordon E. Brown, Jr.

a,c,d

a. Department of Chemical Engineering, Stauffer III, 381 North-South Mall,

Stanford University, Stanford CA 94305, USA

b. U.S. Geological Survey, 345 Middlefield Rd, Menlo Park CA 94025, USA

c. Department of Geological and Environmental Sciences, 450 Serra Mall, Braun Hall

Building 320, Stanford University, Stanford CA 94305, USA

d. Department of Photon Science and Stanford Synchrotron Radiation Lightsource,

SLAC National Accelerator Laboratory, Menlo Park CA 94025, USA

Reprinted from Chemical Geology, 373, Johnson, N. C., Thomas, B., Maher, K.,

Rosenbauer, R. J., Bird, D., & Brown, G. E., Olivine dissolution and carbonation

under conditions relevant for in situ carbon storage, 93-105, Copyright 2014, with

permission from Elsevier.

24

Abstract

In order to evaluate the chemistry and kinetics of mineral carbonation reactions

under conditions relevant to subsurface injection and storage of CO2, olivine alteration

was studied at 60 °C and 100 bar CO2 pressure, including olivine dissolution and the

formation of carbonate minerals. Batch experiments were performed with olivine

(Fo92), water, CO2, and NaCl inside gold cells contained within rocking autoclaves.

Two reproducible experiments yielded an initial (1 hour) dissolution rate of 9.50±0.10

x 10-11

and a long-term (10-70 days) rate of 1.69±0.23 x 10-12

mol cm-2

s-1

. The long-

term rate is consistent with previously published rate laws at 4.5 < pH < 5.5. The

dissolution rates presented here are constant with increasing pH in the same range,

suggesting a pH-independent dissolution mechanism at elevated CO2(aq) and H4SiO4

at 60°C. A Si-rich surface layer forms on olivine grains within 2 days of reaction and

appears to slow dissolution by passivating the surface. The olivine dissolution rate

decreases by 2 orders of magnitude over 4 days as the system approaches amorphous

silica saturation but remains constant thereafter based on a linear increase in Mg

concentrations. Secondary phases consist of amorphous silica and magnesite, with up

to 7 mol% olivine converted to Mg-carbonate over 94 days of reaction. Magnesite

precipitation rates could not be precisely quantified due to experimental limitations.

However, our minimum estimate of 1.40 x 10-13

mol cm-2

s-1

suggests that the

precipitation rate is several orders of magnitude greater than predicted by previous

studies. Finally, the presence of 0.5 M NaCl resulted in a decrease in olivine

dissolution rate at reaction times of less than 4 days, but a significant enhancement of

the reaction rate at reaction times greater than 4 days relative to electrolyte-free

experiments. Our results suggest that geochemical models developed to predict the

behavior of subsurface CO2 storage systems in mafic and ultramafic rocks should

incorporate the effects of dissolved species, including SiO2 and NaCl.

25

2.1 Introduction

Increasing levels of atmospheric carbon dioxide (CO2) motivate the study of

carbon capture and storage (CCS) as an important component in a multinational

strategy to mitigate the risks of future climate change. Although many possible

solutions exist for carbon storage in the subsurface, the most thermodynamically

stable solution over geologic timescales is mineral carbonation, such as the chemical

reaction between CO2 and reactive silicate minerals (e.g., forsterite, Mg2SiO4) to form

carbonate minerals:

Mg2SiO4 + 2CO2 → 2MgCO3 + SiO2 (1)

Mineral carbonation occurs via a series of steps, and the overall reaction is

thermodynamically favored (ΔG = -47 kJ/mol with CO2 gas and amorphous silica as

the SiO2 phase at 60oC and pCO2 =100 bar) and occurs in nature. Mineral carbonation

steps are illustrated by reactions 2-7, although other steps may occur, such as

formation of metastable Mg-carbonate solids (e.g., hydromagnesite, nesquehonite)

(Hopkinson et al., 2008):

Mg2SiO4 + 4H+ → 2Mg

2+ + H4SiO4 (2)

H4SiO4 = SiO2(am) + 2H2O (3)

2CO2(g) = 2CO2(aq) (4)

2CO2(aq) + 2H2O = 2HCO3- + 2H

+ (5)

2HCO3- = 2CO32-

+ 2H+ (6)

2CO32-

+ 2Mg2+

→ 2MgCO3 (7)

________________________________

Mg2SiO4 + 2CO2(g)→ 2MgCO3 + SiO2(am) (8)

First, the silicate mineral dissolves and releases divalent cations, such as

magnesium, iron, and calcium, in addition to silica in the form of silicic acid (H4SiO4)

(reaction 2). The silicic acid then precipitates as (possibly hydrated) amorphous silica

(SiO2(am)) in low temperature systems (reaction 3), where quartz precipitation is

kinetically limited and amorphous silica solubility is low relative to olivine (and other

26

silicate minerals) solubility (Steefel and Van Cappellen, 1990). Carbon dioxide also

dissolves concurrently (reactions 4-5), producing carbonic acid, bicarbonate ions, and

carbonate ions whose relative quantities are pH dependent. The dissolved Mg ions

then react with bicarbonate and carbonate ions to produce carbonate minerals, which

precipitate at high saturation indices (reaction 7) (Saldi et al., 2012). Some examples

of natural mineral carbonation involving Mg-silicates, which are both abundant and

highly reactive (Matter and Kelemen, 2009), can be found in Oman (Kelemen and

Matter, 2008), Italy (Boschi et al., 2009), and California (Goff and Lackner, 1998).

Such natural analogues motivate a laboratory-based study of silicate carbonation from

the initial stages of olivine dissolution, and the attendant silica precipitation to

precipitation of a carbonate phase (reaction 7). To our knowledge, long-term

experiments covering the full sequence of reactions associated with Mg-silicate

carbonation have not been conducted previously.

Olivine ((Mg,Fe)2SiO4) is a common mineral in mafic and ultramafic rocks in

the subsurface, but due to its high solubility it weathers quickly under earth-surface

conditions (Goldich, 1938). Numerous studies of olivine weathering at surface and

near-surface conditions have shown that olivine dissolution rates increase with

increasing temperature and decreasing pH (Blum and Lasaga, 1988; Chen and

Brantley, 2000; Giammar et al., 2005; Hänchen et al., 2006; Pokrovsky and Schott,

2000b; Prigiobbe et al., 2009; Oelkers, 2001a; Olsen and Rimstidt, 2008; Shirokova et

al., 2012; Wang and Giammar, 2013; Welch and Banfield, 2002; Wogelius and

Walther, 1992, 1991). Recent studies of olivine dissolution in the presence of

dissolved CO2 have attributed decreases in the dissolution rate to changes in pH

(Golubev et al., 2005), although Chen et al. (2006) found olivine dissolution rate

enhancement in the presence of bicarbonate ions. Other work on silicate mineral

carbonation suggests that the carbonation reaction may occur in a hydrated

supercritical CO2 phase in addition to the aqueous phase (Felmy et al., 2012; Kwak et

al., 2011; Kwak et al., 2010; Loring et al., 2011). The formation of a Si-rich layer on

the olivine surface during dissolution has been observed using x-ray photoelectron

spectroscopy (XPS) (Zakaznova-Herzog et al., 2008), transmission electron

27

spectroscopy (TEM) (Bearat et al., 2006; Daval et al., 2011), and nuclear magnetic

resonance (NMR) spectroscopy (Kwak et al., 2011). The Si-rich layer may be formed

via a leaching process (Bearat et al., 2006; Daval et al., 2011; Pokrovsky and Schott,

2000a, 2000b; Oelkers, 2001b), a dissolution/reprecipitation process (Hellmann et al.,

2012; King et al., 2011), or a combination of both processes (Saldi et al., 2013). The

Si-rich layer may inhibit olivine dissolution. For example, both Daval et al. (2011) and

Pokrovsky and Schott (2000b) found that the rate of olivine dissolution decreases with

increasing SiO2(am) saturation. While many studies have examined the dissolution

behavior of olivine in aqueous solutions (e.g., Rimstidt et al. 2012 and references

therein), relatively few examined olivine dissolution in the presence of two fluid

phases (aqueous and supercritical CO2) and with high concentrations of dissolved

species, specifically H4SiO4.

Olivine dissolution is only the first step of the carbonation process. Effective

CO2 sequestration requires carbonate precipitation as well, and because the extent and

rate of carbonate precipitation will depend on the rate of olivine dissolution, these

processes are coupled. Reactions 2 through 7 show the interdependency of these steps

during olivine carbonation. In a closed system, CO2 and olivine must dissolve (and

alkalinity must increase) before Mg-carbonate can precipitate. Open systems allow for

chemical steps to occur at separate times and in different physical locations—olivine

may dissolve upstream creating a Mg-rich fluid, which later interacts with CO2 to

precipitate carbonate. Carbonation associated with an in situ storage scenario could

represent some combination of open and closed systems (Boschi et al., 2009; Kelemen

et al., 2011), thus it is important to study olivine carbonation both as a series of

coupled reactions and as distinct reaction steps. Ex-situ carbonation would likely be

engineered as an open system with each step carefully optimized for maximum

reaction and minimum cost. Several coupled olivine dissolution/magnesite

precipitation studies have been conducted, though all previous successful attempts at

precipitating magnesite from the irreversible dissolution of olivine in CO2-rich

solutions required additional chemicals, such as acids or sodium bicarbonate, and

relatively high temperatures (i.e., >80 ˚C) to enhance magnesite precipitation rates

28

(Bearat et al., 2006; Chen et al., 2006; Giammar et al., 2005; Hänchen et al., 2007;

King et al., 2010; Kwak et al., 2010). Such additives would increase the cost of

sequestration. In order to understand olivine carbonation under conditions relevant to

natural systems, longer-term studies at lower temperatures and without chemical

additives are required.

A better understanding of the dissolution pathways and kinetics is also

necessary to assess the efficacy of mineral carbonation for sequestering CO2.

Recently, Rimstidt et al. (2012) performed a systematic review of 25 independent

olivine dissolution studies and derived two equations that describe forsterite

dissolution rate as a function of pH and temperature. A 10% variance in dissolution

rates, not associated with pH or temperature, was attributed to variability in the

calculation of surface area as total surface area is less important than the number of

active sites on the mineral surface (Rimstidt et al. 2012). A key conclusion was that

insufficient data sets containing dissolved carbonate species exist to quantify the effect

of CO2 on forsterite dissolution rates (Rimstidt et al. 2012).

To address the need for additional experimental work on the influence of CO2

on forsterite dissolution (e.g., Rimstidt et al., 2012) and to provide additional

experimental insight into the consequences of the Si-rich layer, we have examined

long-term olivine carbonation kinetics under reaction conditions relevant to in-situ

storage by observing reaction progress over 94 days at 60 ˚C and 100 bars pCO2 in the

presence of water. In contrast to many dissolution studies that have used mixed-flow

reactors, we use a batch reactor to evaluate the range of reaction conditions associated

with olivine carbonation, from dissolution to saturation with respect to amorphous

silica and magnesite. Use of a batch reactor distinguishes this study from those using

mixed-flow experiments as it allows us to evaluate the reactions across a broad range

of conditions reflective of the geochemical evolution of natural systems.

By analyzing the entire carbonation reaction, from initial olivine dissolution to

secondary phase precipitation, we can evaluate the limiting step(s) in the carbonation

process. We present time-resolved elemental concentrations and detailed analysis of

reaction products, allowing us to carefully monitor the entire carbonation reaction,

29

from the dissolution of CO2 and olivine to carbonate precipitation. These data provide

new constraints on olivine dissolution rates at high pCO2 and suggest a weaker

dependence of dissolution rates on pH compared to previous studies. The data thus

contribute to the growing database of olivine dissolution rates in the presence of CO2.

We also observe that dissolved electrolytes have a complex and time-dependent effect

on the carbonation reaction. Importantly, our work indicates that dissolved SiO2 and

NaCl are important controls on the dissolution/carbonation rates of olivine, and thus

should be included in geochemical models of carbon storage in olivine-rich rocks.

We begin our analysis of olivine carbonation by confirming the production of

amorphous silica and magnesite as secondary phases and then by examining the

aqueous phase composition as a function of time in order to extract reaction rates and

thermodynamic saturation values. We finish with (1) a discussion of the effects of

amorphous silica saturation and NaCl concentration on the rate of olivine dissolution,

(2) a comparison of rates from this study with previously published rate laws, and (3)

the rate of magnesite precipitation.

2.2 Materials and Methods

2.2.1 Autoclave Reactor Experimental System

To minimize potential catalytic effects of the reaction cell surface and to allow

for the changing reactant volume throughout the experiment, we employed a flexible

and inert Au-bag reaction vessel design following the detailed description in

Rosenbauer et al. (1983) with modifications for sampling and analysis of CO2

(Rosenbauer et al., 2005). Briefly, most experiments were carried out in flexible Au-Ti

reaction cells with ~200 mL initial volume, equipped with a small bore (2.3 mm) ¼

inch OD, Ti capillary exit tube and sampling valve. Titanium parts were passivated

using a nitric acid bath followed by bake-out in air for 24 hrs at 450 ˚C. This

experimental set-up allows for serial sampling of cell contents while maintaining

constant cell pressure. The cell was contained within a steel autoclave in a cyclic

rotating furnace (Rosenbauer et al., 1983). Liquid CO2 was added to the reaction

vessel with high-pressure syringe pumps (ISCO Corp./Teledyne Inc., Model D100)

30

charged from a high purity CO2 gas cylinder (Matheson Gas Inc.) equipped with a

full-length eductor tube for liquid withdrawal. Prior to final assembly, reagent grade

chemicals were used to generate 0.5 M NaCl solutions that were combined with the

olivine. After the reactants were sealed inside the cell, the autoclave was pressurized

to ~100 bar by the annular water pressure, allowing the headspace gas to exit from the

cell and preventing oxygen dissolution during pressurization. The assembly was then

depressurized and heated to experimental temperature, after which it was pressurized

to 100 bar and a sample was taken in order to provide a baseline point. Then, CO2 was

injected into the reaction cell through the exit tube with a syringe pump at 100 bars

and 20 °C, the reaction time was started upon completion of CO2 injection.

Temperature was maintained by a proportional controller (Omega, Love™ Controls,

Model 49) and measured with a calibrated type K thermocouple. Pressure was

measured with dead-weight calibrated analog gauges.

Serial samples were obtained throughout the experiments. At the conclusion of

an experiment, CO2 was vented through the exit tube in concert with disassembly of

the stainless steel autoclave. The large heat capacity of the steel autoclave + pressure

fluid kept the reaction cell above 50 °C for the entire disassembly process. After the

autoclave and reaction cell were disassembled, the reacted solids were rinsed and

filtered under a vacuum through 2.5 m paper filters and dried overnight in air at

60 °C. The time from beginning depressurization of the reaction cell to filtration of the

products was 30 minutes or less. The pH of the filtrate ranged from 6 to 7.

2.2.2 Analytical and Sampling Procedures

Serial samples were obtained throughout each reaction via polypropylene

syringe and a three-way stopcock that allowed for an initial 0.5 mL withdrawal to

purge the exit tube. Samples were obtained for total CO2 analysis, cation analysis, and

alkalinity titration using the same 3-way stopcock. Total CO2 samples were analyzed

by coulometry with liquid injection into a phosphoric acid reaction vessel (UIC

Analytics). Total CO2 samples consisted of approximately 0.5 mL liquid sample and

10mL headspace. Sample masses were determined by high precision gravimetry of the

sampling syringe before and after sampling and injection. Alkalinity and cation

31

samples were obtained via polypropylene syringe, and filtered with a 0.45µm nylon

syringe filter into pre-weighed vials. Exact sample amounts were determined by

gravimetry. Alkalinity samples (~0.5 mL) were then diluted 10x in 15 mL serum vials

and analyzed via sulfuric acid titration to a pH endpoint of 4.2 with a calibrated pH

probe and autotitrator cartridge system (Hach Inc., USA). Cation samples (~0.5 mL)

were acidified with TM grade nitric acid to pH <2 and diluted for analysis via ICP-

AES on a Thermo Scientific ICAP6300 Duo View Spectrometer.

Reaction cell integrity was monitored by frequent refractometer salinity

analysis to ensure no mixing between the annular freshwater and the saline reaction

fluid. The reactions were run for a period of 4 to 94 days, with 7 to 10 fluid samples of

about 2 mL taken over the course of each experiment. The total volume of samples

removed was kept below 10% of the initial volume in order to maintain the water to

rock ratio, initially set at 50:1 by mass. The scCO2:water ratio was set at 1:10 by

volume at reaction temperature and pressure. A sufficient volume of CO2 was added to

Figure 2.1: X-ray diffraction patterns for unreacted and reacted olivine. Magnesite peaks are

visible in the reacted spectra .

32

the reaction vessel in order to saturate the aqueous phase (saturation = 0.93 mol/kg

with 0.5 M NaCl) and maintain a headspace equal to 1/10 the volume of the aqueous

phase at reaction conditions. The headspace allowed the reaction to maintain a

constant pressure of 100 bars.

2.2.3 Mineral and Mineral Surface Analyses

Initial and product mineral phases were analyzed using a series of techniques

before and after reaction to determine mineralogy, total carbon content, surface

chemical composition, and bulk chemical composition. Powder x-ray diffraction

(XRD) was performed on a Rigaku X-ray Diffractometer, model number CM2029

using monochromated Cu Kα radiation for 2-theta values between 10° and 70° to

determine the mineralogy of each sample. Total carbon content was determined by

coulometry using a phosphoric acid digestion and the UIC Analytics coulometer. X-

ray photoelectron spectroscopy (XPS) was performed on a PHI VersaProbe Scanning

XPS Microprobe and allowed for the study of the composition of mineral surfaces

(~10 nm deep). Bulk chemical composition was obtained by several methods:

digestion followed by ICP-AES, energy dispersive spectroscopy (on a FEI XL30

Figure 2.2: X-ray photoelectron spectroscopy data for unreacted olivine, and olivine reacted for 2,

4, and 74 days. The peak intensity of Mg decreases with increasing reaction time relative to the Si

peak, indicating that the mineral surface becomes more Si-rich as the reaction progresses.

33

Sirion SEM with FEG source with EDAX detector), and by electron microprobe

analysis (JEOLJXA-733A Superprobe). SEM images were taken with a Sirion SEM.

The composition of the olivine used in these experiments, as measured by

hydrofluoric acid digestion and ICP, is Mg1.84Fe0.16SiO4 (Fo92) and is from the Twin

Sisters Dunite, Washington. Rock powder used in our experiments contains <1%

magnetite and chromite as determined by electron microprobe analysis (neither phase

was visible in XRD patterns) (Onyeagocha, 1978). Unreacted olivine was

predominantly forsterite, with about 3% lizardite by mass. No other secondary phases

were identified by XRD (Fig. 2.1). Mineral samples were prepared by alternating

between methanol washes and sieving (3 times total) to obtain a grain size range of

38-75 μm. The grain size fraction 75-105 μm was also retained for use in other

experiments. XPS analysis of unreacted olivine indicated that washing with water

removed Mg from the olivine surface, and visual inspection of SEM images indicated

that water was also less effective at removing the fine and ultrafine particles.

Quantitative XPS analysis was used to determine that the unreacted olivine has a

stoichiometric surface composition (1.85±0.10:1 Mg:Si), and elements other than Mg,

Fe, Si, and O make up <1 mol% of the material (see Supplementary Material Fig. 2.2).

Geometric surface area was calculated from the grain diameters (38-75µm range)

using Equations 3 and 4 from the supplemental information of Rimstidt et al. (2012) to

be 342 cm2/g. The BET surface area was measured using an ASAP 2020

(Micromeritics Instrument Corporation) with a 7-point surface analysis and nitrogen

as the adsorbant. The BET area is 6410 cm2/g, which gives a roughness factor (BET

area divided by geometric area) of 18.74.

2.2.4 Experiments

Results of four experiments using the same starting material (Fo92 olivine),

temperature (60oC), CO2 pressure (100 bar), and water:rock ratio by mass (50:1) are

summarized in Table 2.1. Two experiments contained 0.5 M NaCl, whereas two had

no added electrolyte. Experimental duration ranged from 4 to 94 days. The shortest

experiments were conducted with higher sampling frequency to look at the initial

dissolution kinetics as silica saturation was approached.

34

2.2.5 Calculations and Modeling

Aqueous speciation and reaction affinity were calculated using PHREEQC

(Parkhurst and Appelo, 1999) and the included llnl.dat database, which is derived from

the EQ3/EQ6 database (Wolery et al., 1990) for each data point using measured

solution compositions. The pH was calculated from alkalinity and total inorganic

carbon measurements, using previously published CO2 solubility data from Li and

Duan (2007). Mineral saturation was calculated in the form of the log of the reaction

quotient, Q, divided by the equilibrium constant K. A mineral is at saturation if Q=K,

or log(Q/K)=0. Uncertainties in pH and saturation states were calculated using

uncertainties in experimental measurements. The largest source of uncertainty came

from the alkalinity measurements, which had a mass uncertainty of ±0.02 g and a

titration uncertainty of ±0.003 mL. We did not control or measure redox state, so Fe

speciation was calculated using total Fe only. Olivine dissolution rates were calculated

for each data point using the measured concentration and time differences between the

two points of interest. In some instances, the pH of the two data points used to

calculate instantaneous rates were different, so these rates are plotted showing the

range of pH for each calculated rate. Long-term rates (10-70 days) were calculated

using a linear regression of Mg concentration vs. time and the errors were calculated

based on the R2 value (square of the correlation coefficient), which was larger than the

5% concentration error on each data point. After the experiments were depressurized,

Mg concentrations and pH were re-measured in the solution and the total inorganic

carbon content of the solids was measured using a coulometer.

Table 2.1: Experimental data for four experiments.

Temperature

(oC)

Pressure

(bar)

Initial ionic

strength (M)

Aqueous

solution:CO2

ratio (mass)

Aqueous

solution:rock

ratio (mass)

Duration

(days)

1 60 100 0.5 34:1 50:1 74

2 60 100 0.5 34:1 50:1 94

3 60 100 0.0 34:1 50:1 4

4 60 100 0.0 34:1 50:1 98

35

2.3 Results

2.3.1 Solution Data

Elemental concentrations (Mg, Si, and Fe) and alkalinity as a function of time

are presented in Fig. 2.3 and Table 2.2 for the four experiments. Silicon (in the form

of H4SiO4) concentrations increased rapidly in all experiments over the initial 10 days.

Experiment 1 (0.5 M NaCl) displays significant variance of 30% in the measurements

from 10-74 days, Experiment 2 (0.5 M NaCl) shows a maximum H4SiO4 of 6 mM at

20 days followed by a decrease to steady-state at 45 days and 4 mM. Experiment 4 (0

Figure 2.3: Elemental concentrations versus time for magnesium (A), silicon (B), iron (D), and

alkalinity versus time (C) for four experiments. Insets show the same y-axis for the initial 4 days

of reaction. Experiments 1 and 2 contain 0.5 M NaCl; Experiments 3 and 4 have 0 M NaCl.

36

M NaCl) also shows a maximum of H4SiO4 (8 mM at 58 days). In all experiments, Mg

concentrations increased for the first 2 days, then remained constant for 2-5 days. Mg

concentrations again increased at a roughly constant rate for the remainder of

Experiments 1, 2, and 4. The Fe concentrations peaked at 20, 28, and 77 days for

Experiments 1, 2, and 4, respectively, followed by a decrease. The duration of

Experiment 3 (0 M NaCl) was short enough to expect no change in Fe concentrations

based on the trends from other experiments. Finally, the alkalinity data mirror the Mg

concentrations.

2.3.2 Mineral Products Analysis

X-ray diffraction confirmed the presence of magnesite in Experiments 1 and 2.

Phosphoric acid digestion and coulometry showed that 12±2 mol % of the olivine

converted to carbonate in Experiment 1, and 17±2 mol % in Experiment 2. These

conversions are artificially high because some carbonate precipitation occurred during

depressurization and the corresponding rise in pH. The amount of carbonate that

precipitated during depressurization was determined by measuring the Mg

concentration from samples before and after depressurization. The reduction in Mg

during depressurization was assumed to have been due to Mg-carbonate precipitation,

and this amount was subtracted from the coulometric results to yield carbonation

extent. We define carbonation extent as the mole percent of olivine converted to

magnesite during the experimental duration, before depressurization. The extent of

carbonation that occurred during the reaction was 0 % for Experiment 1 (74 days) (i.e.,

all carbonate precipitation occurred during depressurization) and 7±2 % for

Experiment 2 (94 days). No new phases other than magnesite were detected by X-ray

diffraction, and no broad SiO2(am) peak was detected (supplemental Fig. 2.1).

Fig. 2.4 shows SEM images of unreacted (Figs. 2.4A-B) and reacted (Figs.

2.4C-2F) olivine samples. Unreacted olivine grains are of uniform size and few fine

particles are visible. After reaction, amorphous silica is present both in large sheets

>100 µm across (Fig. 2.4C) and as irregular coatings on olivine grains (Fig. 2.4D).

The topography of the precipitated SiO2 phase (Fig. 2.4E) and the precipitated MgCO3

on the surface of the silica (Fig. 2.4F) are also evident. EDS scans of precipitated

37

silica (Fig. 2.4E) and magnesite (Fig. 2.4F) show that the precipitated silica contains

only silicon and oxygen, while the magnesite contains carbon, oxygen, magnesium,

and iron. A small silicon peak is also visible in the magnesite EDS spectrum, which

Table 2.2: Experimental data for four experiments.

time (days) [Mg] (mM) [Si] (mM) [Fe] (mM) alkalinity (meq) [CO2] (M)

Experiment 1 0.00 0.3 0.1 0.0 - -

60 °C, 100 bar 0.04 5.0 0.8 0.1 14.2 0.72

0.0 M NaCl 1.17 8.6 2.8 0.1 20.0 0.81

2.06 8.5 2.3 0.1 23.6 0.80

4.99 12.2 4.1 0.4 27.3 0.87

8.16 17.3 6.1 1.1 43.3 0.88

13.01 26.0 5.1 2.0 60.3 0.88

20.09 35.1 4.0 2.8 86.8 0.88

26.95 43.0 2.9 1.6 104.0 0.90

35.19 63.2 4.1 0.8 118.6 0.90

42.96 97.8 5.7 0.5 194.4 0.97

49.07 71.1 4.2 0.3 204.9 1.07

56.23 117.3 5.8 0.3 230.3 0.92

64.54 108.6 5.8 0.3 260.5 0.86

73.99 139.2 5.8 0.2 260.9 0.82

73.99 68.4 2.0 0.0 - -

Experiment 2 0.00 0.6 0.2 0.0 - -

60 °C, 100 bar 0.04 4.6 0.8 0.1 12.8 0.67

0.5 M NaCl 1.00 8.0 2.4 0.1 27.3 0.84

3.00 9.4 3.0 0.1 26.4 0.86

10.19 11.8 4.1 0.3 33.3 0.94

18.50 25.5 6.1 1.7 66.9 0.86

27.96 37.1 5.4 2.1 91.6 0.96

34.96 54.6 5.9 1.5 121.5 0.90

43.17 77.7 5.4 0.8 165.0 0.97

51.08 87.4 4.2 0.5 198.2 1.00

61.05 97.8 3.8 0.3 227.3 0.83

71.16 117.6 4.3 0.2 263.6 1.14

78.13 118.1 3.9 0.2 284.1 -

86.20 134.3 4.2 0.1 282.4 0.82

92.20 128.2 4.0 0.2 289.1 1.05

92.20 94.2 3.5 0.1 - -

Experiment 3 0.00 0.3 0.2 0.0 - -

60 °C, 100 bar 0.04 7.4 0.8 0.0 14.3 0.68

0.0 M NaCl 0.13 9.3 1.5 0.1 17.3 0.91

0.29 10.1 1.9 0.0 17.2 0.91

0.63 13.9 2.6 0.1 22.2 0.98

0.96 12.4 2.8 0.0 21.9 1.00

1.44 13.7 3.3 0.0 24.9 1.03

2.00 16.8 4.5 0.2 24.9 1.00

2.52 15.8 4.1 0.1 26.4 1.00

4.02 17.3 4.6 0.0 29.8 1.04

Experiment 4 0.00 1.7 1.1 0.5 - -

60 °C, 100 bar 0.04 7.8 1.5 0.2 12.12 0.92

0.0 M NaCl 1.00 10.9 3.1 0.2 18.64 1.06

3.09 14.5 4.2 0.3 22.37 0.93

7.25 17.8 5.1 0.3 24.38 1.06

14.08 16.0 4.5 0.0 29.83 1.2

23.04 22.0 6.1 0.1 28.47 0.99

36.15 22.3 6.3 0.3 30.57 0.99

58.27 32.1 8.0 1.1 44.74 0.95

66.40 34.5 7.3 1.3 62.14 1

77.15 38.6 6.9 1.6 48.68 1.02

91.18 44.4 6.7 1.5 68.25 1.08

93.38 48.3 7.4 1.2 76.15 1.07

98.17 47.1 6.8 0.9 84.13 1

38

we attribute to small amounts of silica precipitated on the surface of the magnesite

nodules (Fig. 2.4F). MgCO3 precipitated preferentially on silica (both coatings and

discreet particles) as opposed to olivine. No separate iron-rich phases were observed in

the reaction products of the experiments discussed here, though both EDS and XPS

showed that the Mg-carbonate phase contains iron. The BET surface area of unreacted

olivine was measured to be 6410 cm2/g. After 94 days of reaction, the BET surface

area was 13,920 cm2/g. Much of the increased surface area likely comes from

precipitated silica, which appears to hve high roughness from visual inpection of SEM

images (Fig. 2.4E).

XPS of the unreacted olivine surface showed a stoichiometric Mg:Si ratio

Figure 2.4: Images of unreacted (A, B) and reacted (C-F) olivine from Experiment

2. Unreacted olivine grains are of uniform size. After reaction, the solids are

dominated by large (>100 µm) silica sheets (C) and many grains are partially

coated with silica (D). Magnesite nodules grow via a spiral growth pattern on the

silica (coatings and sheets) (D, F), which itself has a structure composed of fused

spheres (E). EDS spectra of magnesite nodules (F) and silica (E) are inset.

39

(1.85±0.10:1) and olivine composition of Fo93±2 (supplemental Fig. 2.2). Within

uncertainty, the XPS measurement is equivalent to the ICP measurement (Fo92).

However, the ICP measurement is more precise and thus was used for all calculations.

After reaction periods as short as two days, the olivine surface region was depleted

with respect to Mg (and enriched with respect to Si) by 46±6 % (Mg:Si ratio of

1.0±0.1:1). After four days of reaction (Experiment 3), the surface was further

depleted in Mg and after 74 days of reaction (Experiment 1), Mg was not detected by

XPS (Fig. 2.2).

2.3.3 Thermodynamic Calculations

The calculated temporal evolution of magnesite, amorphous silica, and siderite

saturation states is shown in Figs. 2.5A-C for Experiments 1 and 2 (0.5 M NaCl), and

4 (0 M NaCl). All experiments were undersaturated with respect to forsterite by at

least 6 orders of magnitude (data not shown). Magnesite saturation was exceeded

between 17 and 20 days in Experiment 1, at 28 days in Experiment 2, and 91 days in

Experiment 4. Experiments reached amorphous silica saturation after only 5 days.

Siderite saturation was reached at 13 days and 28 days then dropped below saturation

in Experiments 1 and 2, respectively. Siderite saturation was not reached during

Experiment 4. Calculated pH versus time is presented Fig. 2.5D and shows a rise in

pH with time for the duration of all three experiments, though some variability is

visible for Experiment 2 after 60 days and is due to variance in the total CO2

measurements.

40

2.3.4 Rate Calculations

Olivine dissolution rates vary as a function of time, thus several rates for each

experiment are presented in Table 2.3. Initial dissolution rates were calculated using

the change in Mg concentration and the change in time between data points. Average

dissolution rates from 10-70 days were calculated with a linear regression of the data

points in that time range. Previous studies of olivine dissolution in aqueous solutions

have shown that forsterite dissolution rates are highly dependent on pH (e.g., Rimstidt

Figure 2.3: Saturation of magnesite (A), amorphous silica (B), and siderite (C) vs. time as well as

calculated pH vs. time (D). Data presented were calculated from Experiments 1, 2 and 4. Saturation

is presented as the logarithm of the reaction quotient Q divided by the equilibrium constant K.

Dashed lines in A-C represent equilibrium between the solid phase and the reaction solution

(logQ/K=0 at Q=K).

41

2012 and references therein), and thus one should avoid calculating rates when the pH

is changing, as it is in our experiments. However, although the pH is increasing

between 10 and 70 days we see no pH dependence of olivine dissolution rate as

evidenced by the linear relationship between Mg concentration and time.

The carbonation rate was calculated only for Experiment 2 because it was the

only experiment during which Mg-carbonate precipitated before depressurization, as

explained in section 3.2. Based on our experiments, we estimate the time at which

precipitation begins in an experiment with 0.5 M NaCl is between 74 and 94 days, as

an experiment lasting 74 days (Experiment 1) did not precipitate carbonate before

depressurization. Thus, assuming the observed precipitation occurred over 20 days, the

carbonation rate was calculated using the amount of carbonate formed before

depressurization and the initial geometric surface area of olivine, following Rimstidt et

al. (2012). The resulting carbonation rate is only a minimum magnesite precipitation

rate because we do not know precisely when carbonate precipitation began or the

actual surface area term. All rates presented in Table 2.3 are normalized with the

geometric surface area of unreacted olivine, with the BET-normalized rates given in

parenthesis. Experiment 4 (0 M NaCl) did not precipitate carbonate presumably

because of the lower overall olivine dissolution rate which resulted in a lower degree

of magnesite saturation compared to the experiments containing electrolyte (Fig.

2.5A).

Table 2.3: Geometric surface area-normalized reaction rates for four experiments, with

BET-normalized rates in parenthesis.

Initial dissolution rate

(first hour)

[mol olivine s-1cm-2]

Average dissolution rate

from 10-70 days

[mol olivine s-1cm-2]

Carbonation rate

[mol MgCO3 s-1cm-2]

Experiment 1 1.03 ± 0.10 x10-10

(5.50 x 10-12)

1.69 ± 0.15 x10-12

(9.02 x 10-14)

N/A (carbonate

precipitated during

depressurization)

Experiment 2 8.69 ± 0.96 x10-11

(4.63 x 10-12)

1.62 ± 0.08 x10-12

(8.64 x 10-14)

5.70 ± 0.68 x10-12

(3.04x10-13)

Experiment 3 1.61 ± 0.16 x10-10

(8.57 x 10-12) N/A N/A (no carbonate)

Experiment 4 1.35 ± 0.14 x10-10

(7.23 x 10-12)

3.26 ± 0.07 x10-13

(1.74 x 10-14) N/A (no carbonate)

42

2.4 Discussion

2.4.1 Solution Data and Secondary Phases

Solution composition data as a function of reaction time (Fig. 2.3) provide

insight into the dissolution and precipitation processes that occur during olivine

carbonation. The first day of reaction is characterized by a rapid, non-stoichiometric

release of ions into solution, particularly Mg2+

. Early in the reaction, Mg is

preferentially removed from the olivine surface, possibly by a direct exchange with

protons (Pokrovsky and Schott, 2000b). One result of preferential Mg removal is the

formation of a Si-rich (Mg-depleted) layer on the olivine surface (Bearat et al., 2006;

Daval et al. 2011; Pokrovsky and Schott, 2000b). This period of rapid release is

followed by a 3-5 day period during which olivine dissolution rate slows (as measured

by Mg, Si, or alkalinity). During this time period, dissolution is congruent with respect

to Mg and Si and the reaction fluid approaches saturation with respect to amorphous

silica. These first two periods (rapid Mg release followed by slowing dissolution) are

best illustrated by the results of Experiment 3 because more samples were obtained

during the first 4 days compared to the other three experiments. A similar change in

dissolution rate with time was also observed by Wang and Giammar (2013), although

dissolution in their experiment remained stoichiometric with respect to Mg and Si.

After 10 days, Mg concentrations again increased at a steady rate for the

remainder of Experiments 1 and 4 and until day 85 of Experiment 2 (Fig. 2.3A).

Calculations indicate that Experiment 2 was saturated with respect to amorphous silica

by day 10, although Si concentration continued to rise for several more days before

declining to saturation (Fig. 2.4B). The concentration maximum of Si is considered to

be due to kinetic limitation of silica precipitation. At 45 days and longer, the silica

precipitation rate is faster than the Si release rate and the concentration of Si in

solution remains constant. Experiment 1 showed significant variability in Si

concentration with time, which we attribute to an inconsistent sampling procedure

rather than any physical phenomenon in the reaction vessel. This effect occurs due to

the rapid temperature drop from 60 °C to room temperature (about 20 °C) which

43

occurs upon removing the sample for ICP analysis. The decrease in amorphous silica

solubility likely results in silica precipitation inside the sampling syringe in a matter of

minutes, such that a sample filtered after 5 minutes would have a lower Si

concentration than a sample filtered after 1 minute. We were able to experimentally

confirm this hypothesis after the experiments were completed, but do not have specific

data on sampling times for each data point presented here. Nevertheless, despite the

variability in Experiments 1 and 2, the trends in concentrations are consistent and the

maximum values are hence still a reliable indicator. We addressed this issue in

Experiments 3 and 4 by filtering the ICP samples within 60 seconds of withdrawing

them from the reactor.

At 10 days reaction time, the decrease in Fe concentrations followed a large

concentration maximum (both Experiments 1 and 2, Fig. 2.3D), which is indicative of

precipitation of a secondary phase; however, in this case the nature of that phase is not

clear. Saturation calculations illustrate that siderite is a possible secondary phase, but

it is slightly undersaturated for much of the experiment (>20 days). Calculations also

suggest the dissolved Fe is dominantly in the form of FeHCO3+. Based on the amount

of Fe released from olivine (and assuming stoichiometric Mg and Fe release), we

would expect to see up to 0.23 g of siderite in our reaction products. However, no

siderite was detected by either XRD or SEM (supplemental Fig. 2.1), which implies

that the Fe-rich phase is amorphous or possibly incorporated in the magnesite, similar

to other findings (Saldi et al. 2013). Analysis of the magnesite nodules with EDS

showed the presence of Fe, though the amount was not quantified due to the

complications associated with SEM/EDS quantification (Fig. 2.4F). We see no Fe in

the precipitated amorphous silica using EDS (Fig 2.4E). Another possibility is the

formation of a non-carbonate Fe phase, such as magnetite. However, no magnetite was

detected by XRD after reaction, suggesting that the majority of the Fe is incorporated

in magnesite and/or that any magnetite formed was beneath the detection limit of XRD

(1 wt. %).

Observations of secondary phases are consistent with the concept that silica

precipitation controls H4SiO4 concentration as the precipitated silica is present in large

44

(>100 m) sheets in Experiments 1, 2, and 4. (Fig. 2.4C). Amorphous silica also

formed a coating on the olivine grains visible in SEM (Fig. 2.4D), but there appears to

be space between the coating and the olivine, suggesting that the precipitated coating

did not prevent the interior olivine grain from continuing to dissolve and shrink in

size. Visual inspection of SEM images and the dramatic increase in BET surface area

(117% increase over 94 days in Experiment 2) indicate that amorphous silica formed

most of the available surface for secondary phase precipitation. The greater available

surface area of silica relative to olivine may explain why we observe the preferential

precipitation of magnesite on the silica surfaces rather than directly on the olivine.

Other possible explanations for preferential magnesite precipitation on silica as

opposed to olivine could include a lower interfacial energy between magnesite and

silica relative to magnesite and olivine (De Yoreo and Vekilov 2003), or a rougher

silica surface with more active sites for nucleation. For example, Fernandez-Martinez

et al. (2013) found that heterogeneous calcium carbonate nucleation on quartz is

favored relative to homogeneous nucleation due to the lower interfacial energy of

quartz.

In theory, one would expect Mg concentration to reach a constant value that

represents steady-state olivine dissolution and magnesite precipitation. None of the

experiments conducted in this study definitively show that behavior, though XRD and

coulometry analyses indicate that magnesite did precipitate in Experiment 2. Thus, the

rate of magnesite precipitation was likely slower than that of olivine dissolution.

Longer-duration experiments must be performed to examine the behavior of the

system over such time scales.

2.4.2 Initial Incongruent Dissolution

All experiments conducted as part of this study show initial incongruent

dissolution of olivine. Magnesium release is enhanced 3.5-4.5 times relative to Si over

the first hour of reaction, and by the seventh hour dissolution is congruent. Evidence

for initial incongruent dissolution includes solution composition as a function of

reaction time data (Fig. 2.3) and a comparison of olivine dissolution rates calculated

from Mg and Si (Fig. 2.6). Based on solution data, dissolution appears to be non-

45

stoichiometric again after several days of reaction, but this occurs only after

amorphous silica saturation is reached. Thus the deficiency of Si in solution in the late

experimental stages is more likely due to silica precipitation than a resumption of

incongruent dissolution. Dissolution rates calculated from Mg are higher than from Si

for the first 3 hours, at which point the rates become equal until silica precipitation

begins (Fig. 2.6). Initial incongruent dissolution is attributed to a rapid exchange

between Mg cations in the olivine and protons in solution (Pokrovsky and Schott,

2000a, 2000b; Oelkers et al., 2009), but it could also be due to localized saturation and

precipitation of a secondary, silicon-rich phase (Hellmann et al., 2012; King et al.,

2011). Using solution data from Experiment 3 and mass balance considerations, the

theoretical thickness of the Si-rich layer can be calculated. Residual Si is calculated by

subtracting the measured Si (at hour 7, when congruency is first observed) from the Si

expected based on released Mg. Using the geometric surface area of olivine and the

molar volume of amorphous SiO2 (29 cm3/mol), the theoretical layer thickness was

calculated to be 18 nm. This is an order of magnitude greater than estimates from

Pokrovsky and Schott (2000b), though their titrations were of a duration of only 1-8

minutes, and suggests the formation of a Si-rich, Mg-deficient surface layer occurs

rapidly and continues for at least several hours.

2.4.3 Dissolution Rate as a Function of SiO2(am) Saturation

The rate of olivine dissolution in Experiment 3 (no electrolyte) decreases

substantially as the reaction fluid approaches amorphous silica saturation (Fig. 2.6).

While the saturation index of amorphous silica increases from -1.4 to 0, the olivine

dissolution rate, as calculated from both Mg and Si release, decreases over two orders

of magnitude. This effect was also observed by Daval et al. (2011). Cations are

removed from the olivine surface, leaving behind a Si-rich layer (either leached or

precipitated) that passivates the surface. The Si-rich passivating layer grows in

thickness as more Mg is removed, and the resulting surface may be more silica-like

than olivine-like in its properties (Pokrovsky and Schott, 2000a). As the reacting fluid

reaches SiO2 saturation, the thermodynamic driving force for net dissolution of the Si-

rich layer approaches zero, and thus little to no dissolution of that layer occurs. As a

46

result, the overall dissolution rate of olivine drops significantly when calculated from

measured Mg release (some Mg likely still diffuses via interconnected pores through

the Si-rich layer, but at a slower rate) and approaches zero when calculated from the

measured Si release (because there is no net change of Si in solution). This trend is

observed in the data from all four experiments (Fig. 2.3).

2.4.4 Effect of Added Electrolyte on Olivine Dissolution

Two experiments presented here were conducted with 0.5 M NaCl background

electrolyte (Experiments 1 and 2) and two were conducted without any added

electrolyte (Experiments 3 and 4). The two groups show different behavior as a

function of time. The electrolyte-free experiments initially release Mg and Si at a

higher rate than the experiments with electrolyte, but over long times (>5 days), the

electrolyte-free experiments have a slower release of Mg and Si by a factor of 5

(Table 2.3). Slower Mg and Si release over long times (>5 days) suggests slower

kinetics in the electrolyte-free experiments, and consequently saturation with respect

to magnesite is attained much later in the experiments. The presence of 0.5 M NaCl

increases long-term rate of Mg release and thus the carbonation extent over the times

Figure 2.6: The rate of olivine dissolution, calculated from both Mg and Si data from

Experiment 3, decreases as the silica saturation state increases during the initial 3 days of

reaction. Non-stoichiometric dissolution occurs during the first time interval (due to

incongruent dissolution) and the last (presumably due to amorphous silica precipitation).

47

of our experiments (94 days). Also significant is the higher steady-state Si

concentration in Experiment 4 relative to Experiments 1 and 2. We note, however, that

while we reproduced the long-term behavior of olivine carbonation in experiments

with 0.5 M NaCl (Experiments 1 and 2), we present only one dataset showing the

long-term behavior of olivine carbonation in the absence of added electrolyte. Our

experience with reproducing both long-term behavior with NaCl and short-term

behavior with and without NaCl gives us confidence that the experiments are, in

general, reproducible.

In the absence of other factors, the experiments with 0.5 M NaCl should show

faster olivine dissolution because sodium is thought to enhance the reactivity of water

by modifying its nucleophilic properties (Icenhower and Dove, 2000). In the case of

olivine, which has a silica-like surface and a neutral to negative charge under our pH

conditions (pHIEP = 4.5, where pHIEP= isoelectric point, or the pH at which the surface

carries a net zero charge) (Pokrovsky and Schott, 2000a), cations such as Mg are

electrostatically attracted to the mineral surface. The addition of sodium may displace

Mg from the mineral-solution interface and disrupt the water-SiO2 network at the

mineral surface, thus enhancing the dissolution rate (Dove, 1999; Dove and Crerar,

1990; Dove and Nix, 1997; Icenhower and Dove, 2000). This hypothesis explains the

higher Mg release rate seen in Experiments 1 and 2 relative to Experiment 4 at longer

times, as well as previous work (i.e. Pokrovsky and Schott, 2000b). However, at short

(<4 days) times, olivine dissolution appears to be controlled by silica saturation state

(see section 4.3). Generally electrolytes such as NaCl increase the solubility of solid

phases because ion pairing reduces the activity of ions in solution, but experimental

evidence suggests the opposite is true in the case of amorphous silica and NaCl

solutions (Chen and Marshall, 1982). Solution data from the experiments presented in

this study support the conclusions of Chen and Marshall (1982), as electrolyte-free

Experiment 4 has higher steady-state Si concentrations relative to the NaCl

experiments. Depressed silica solubility in the experiments with added NaCl

(Experiments 1 and 2) correlates with lower initial Mg release, whereas the

experiments without NaCl (Experiments 3 and 4) had the fastest initial Mg release.

48

More specifically, at day 3, Experiment 2 (0.5 M NaCl) had lower concentrations of

Mg and Si (9.0 mM Mg and 3.0 mM Si) than salt-free Experiment 4 (14.5 mM Mg,

4.2 mM Si) (Table 2.4). We present the above argument as further evidence for the

direct and detrimental effect of silica saturation on the initial (0-4 days) dissolution

rate of olivine, but we also suggest that dissolved silica ceases to dominate the

dissolution kinetics at longer times (>4 days in our experiments). An important point

is that both dissolved silica and salt concentration have a large effect on the

dissolution rate of olivine, but neither is generally included in kinetic rate law

formulations.

2.4.5 Kinetics of Olivine Dissolution and Carbonation

Calculated olivine dissolution and carbonation rates based on our experiments

are presented in Table 2.3. The initial dissolution rate was calculated using d[Mg]/dt

for the first hour of reaction, which we have shown to be incongruent (Fig. 2.6).

Calculating these rates with d[Si]/dt yields a rate approximately one order of

magnitude lower. The initial rates were calculated over a short period of time (1 hour),

but the pH was changing over that time and thus we expect the rate also changed.

Thus, although each initial rate is a time-averaged rate, the time is short relative to the

duration of the experiment. Initial rates from Experiments 1 and 2 are consistent with

each other (within uncertainty); initial rates in Experiments 3 and 4 are also consistent

and approximately 50% higher than those from 1 and 2 (Table 2.3, Fig. 2.7A). We

suggest that Experiments 1 and 2 have lower initial dissolution rates because of higher

ionic strength solutions— the addition of NaCl in those experiments (0.5 M vs. 0 M in

Experiments 3 and 4) decreases the solubility of amorphous silica (Chen and Marshall

1982), and thus decreases the rate of olivine dissolution. Other researchers have found

olivine dissolution rates to increase with ionic strength (Pokrovsky and Schott,

2000b), but we consider the effect here to be related to silica solubility, which is

depressed by added NaCl (see section 4.2) (Chen and Marshall, 1982). Fig. 2.6

provides evidence that the rate of olivine dissolution depends strongly on the silica

saturation state, so decreasing the solubility of silica (by adding NaCl) would, by

extension, decrease the olivine dissolution rate under these experimental conditions. In

49

a flow-through experiment we would not expect to see the same effect, unless the fluid

residence time was substantial.

Consistent long-term (10-70 days) dissolution rates calculated from

Experiments 1 and 2 indicate high levels of experimental reproducibility (Fig. 2.7A).

These rates are about two orders of magnitude slower than the initial rates (Table

2.3.). The difference between long-term and initial rates may be due to the high levels

of dissolved SiO2 present in the reaction fluid at time >2 days, or could also be

explained by rapid fine particle dissolution and/or preferential release of Mg leading to

artificially high initial rates. Dissolution rates calculated from Experiment 4 are up to

an order of magnitude lower than those from Experiments 1 and 2 at pH > 4 (at 10-70

days). The pH range over which rates from Experiment 4 are calculated is smaller than

that of Experiments 1 and 2 because the reaction proceeded more slowly and thus less

olivine dissolved. For comparison, Fig. 2.7A also shows a data point from Wang and

Giammar (2013), who conducted experiments on olivine (Fo92) dissolution in the

presence of varying pressures of CO2, water, and varying NaCl concentrations. The

data point in Fig. 2.7A was measured at 50 °C, 100 bar pCO2, and 0 M NaCl. We

adjusted their rate by a factor of 40 to account for the higher mineral:solution ratio in

our experiments (1:50 in ours vs. 1:2000 in theirs). Their rate was calculated over a

longer time (8 hours) and thus a larger pH range (3.1-4.7) than ours. In addition, the

temperature is 10 ˚C lower, which may explain the slightly lower rate. We did not

apply a temperature correction because of uncertainty in the activation energy.

Long-term (10-70 days) olivine dissolution rates calculated for Experiments 1,

2, and 4 using the change in magnesium concentration over time and normalized by

initial geometric surface area are plotted against pH in Fig. 2.7B and compared with

three previously published pH-dependent rate laws from Hanchen et al. (2006),

Pokrovsky and Schott (2000b), and Rimstidt et al. (2012). Though the

mineral:solution ratio did change with time, the size and number of liquid samples

taken were minimized in order to maintain at least 90% of the original fluid volume,

and the surface area of the olivine was assumed to stay constant (i.e. any new surface

area that formed was considered to be due to secondary phase precipitation). Rimstidt

50

et al. (2012) carried out a systematic analysis of literature data (critical selection of

data followed by statistical analysis) and calculated the dissolution rate of olivine in

terms of pH and temperature (Equations 9 and 10, units are mol m-2

s-1

). Their analysis

combined all available data on olivine and forsterite dissolution, encompassing 0 ≤ pH

≥ 14 and 0 ≤ T ≥ 150 °C. The rate is expressed as a function of geometric surface area

(rgeo) in terms of pH and temperature (T) (Rimstidt et al. 2012).

)/T(pH....rgeo 633683200460220056log 5.6pHfor

(9)

)/T(pH...rgeo 139346502026038007.4log 5.6pHfor

(10)

Pokrovsky and Schott (2000b) developed a model based on experimental data

collected for experiments at 25 °C with variable pH (1 to 12), ionic strength (0.001 to

0.1M), CO2 (0 to 0.05M), aqueous Mg (10-6

to 0.05M), and aqueous Si (10-6

to

0.001M). They derived an olivine dissolution rate (rT) that is a function of the number

of reactive Si and Mg sites, which in turn are written as functions of adsorption and

exchange coefficients of participating aqueous species. In acidic and weakly alkaline

solutions the Si term (rSi) dominates, thus the Mg term is not included here (Equation

11). The Si component of the rate is proportional to the surface species concentration

({>Si2O-H+}) through the rate constant kSi. The surface species concentration is a

function of the activity of protons in solution (aH+), the activity of Mg in solution

(aMg2+), and two constants: Kads and Kex. Kads is the stability constant for the exchange

reaction between Mg2+

and 2H+ on the olivine surface and Kex is the stability constant

of H+ adsorption on the mineral surface. The Pokrovsky and Schott (2000b) rate was

computed using their formula, then adjusted for temperature using the activation

energy from Hanchen et al. (2006).

(11)

4

2

5.0

5.0

2

2

1

solutions acidicfor

Hex

Mg

Hads

Hads

SiSiSiT

aK

aaK

aKkHOSikrr

51

To the best of our knowledge, Rimstidt (2012) did not account for the effect of

temperature on measured pH, Hanchen et al. (2006) did calculate the pH at reaction

temperature using the ambient pH and EQ3/6 (Wolery et al. 1990). At 25 °C, a neutral

solution will have a pH of 7, but if the pH of that same neutral solution is measured at

an elevated temperature, it will be lower because log KW decreases with increasing

temperature. For example, in our experiments at 60 °C the neutral pH is 6.37. We also

do not correct the models (or our data) for the temperature dependence of pH, but

suggest that it may partially explain scatter in data obtained at different temperatures.

The models of Pokrovsky and Schott (2000b) and Rimstidt et al. (2012) both predict

that the dissolution rate will decrease by about an order of magnitude as pH increases

from 4 to 6. The slopes of the three models are similar, meaning the dependence on

the hydrogen ion activity is also similar.

Figure 2.7: A: Experimental rate data (normalized to geometric surface area and calculated from Mg

concentrations) as a function of pH. Deviation at the lowest pH (first time point) is due to a

combination of incongruent dissolution creating an artificially high rate and dissolution of fine particles

not removed by washing. Experimental data, particularly from 1 and 2, do not show a pH-dependence

at pH > 4.5. Horizontal uncertainty is defined by the pH values at the two data points used to calculate

each rate. For comparison, one data point from Wang and Giammar (2013) is included. This rate was

measured over 8 hours at 50 °C, 100 bars pCO2, and 0 M NaCl; we corrected it by a factor of 40 to

account for the lower forsterite concentration in their experiments (0.5 g/L compared to our 20g/L). B:

Long term (10-70 days) dissolution rates compared to three published models for forsterite dissolution

(Pokrovsky and Schott, 2000b; Hanchen et al., 2006; Rimstidt et al., 2012). Rates from experiments

with 0.5M NaCl are consistent with the models, the rate from Experiment 4 (no added electrolyte) is

lower. All rates shown here were calculated before Mg-carbonate precipitation occurred.

52

Data from the present study show a different pattern (Fig. 2.7A). The

dissolution rate for the first hour of reaction (3.1 < pH < 4.3) is an order of magnitude

greater than predicted by the models and may be artificially high due to incongruent

dissolution associated with the formation of the Si-rich layer and/or rapid dissolution

of fine particles. Calculating the same rate using Si instead of Mg gives an order of

magnitude lower rate (not shown). Rates measured at intermediate to long times (pH >

4.1) agree in magnitude with the model predictions, but do not show the expected pH

dependence (Fig. 2.7B). Rates derived from Experiment 4 are lower than those from 1

and 2 at pH>4.4 because these pH values are associated with longer reaction times,

when the background electrolyte increases the rate of reaction. Experiment 4 rates

appear to decrease monotonically with increasing pH in the same way as the models,

but as this experiment was slower overall, it covered a relatively short pH range.

Longer reaction time (and thus higher reaction extent) is necessary to investigate the

pH dependence of dissolution rates under salt-free reaction conditions.

The lack of pH dependence in our dissolution rate measurements (from

Experiments 1 and 2) has not to our knowledge been reported previously and likely

indicates that the experimental conditions here facilitated a different kinetically

limiting step than the one observed using flow-through reactors. There are two

primary factors that separate the experiments in this study from more traditional flow-

through kinetic studies: high CO2(aq) and high H4SiO4. Thus, we propose that one or

both of these species are responsible for the pH independence of the dissolution rates.

Other studies have suggested that carbonate species hinder olivine dissolution

(Pokrovsky and Schott, 2000b), which may be happening at pH<5, though this would

not explain the pH-independence unless carbonate species have a positive effect on

dissolution rate at pH>5. As pH increases, the balance of carbonate species shifts from

nearly all carbonic acid, H2CO3(aq), to several mol percent bicarbonate, HCO3-.

Bicarbonate ions may activate the dissolution reaction at mildly acidic pH, which

could partially explain the (relatively) enhanced rate of olivine carbonation in the

presence of sodium bicarbonate (Chen et al., 2006; Jarvis et al., 2009). In fact,

thermodynamic calculations indicate that up to 44% of the Mg in solution is

53

complexed by bicarbonate during the experiment (free Mg2+

is 50% or greater), which

lowers the activity of Mg in solution and possibly enhances olivine dissolution relative

to lower pH values where the carbonate species are predominantly carbonic acid.

While the presence of carbonate species may explain the pH independence, the more

likely cause is high dissolved SiO2. Amorphous silica dissolution rates are not pH

dependent at acidic to neutral pH, so we suggest that under our experimental

conditions (high H4SiO4 and pH 4-6), removal of silicon from the olivine structure is

rate limiting. Further study on this topic needs to be performed in order to verify or

refute our hypothesis.

The role of magnesite precipitation in our experiments is critical to the

discussion of carbonation kinetics, especially as a previous study suggests that the rate

of magnesite precipitation may limit overall carbonation kinetics (Saldi et al. 2012).

Although the work presented here was not specifically designed to quantify

precipitation rates, our results regarding precipitation provide useful information for

the design of future carbonation experiments. As we have no way of separating the

rates of olivine dissolution from that of magnesite precipitation in our current

experiments, the discussion above has assumed that all changes of Mg in solution in

the early phases of the experiments are due to olivine dissolution, an assumption that

we know to be true initially. However, Mg-carbonates in the reaction products indicate

that at 74 days and later, magnesite precipitation occurred concurrently with olivine

dissolution. The results of Experiments 1 and 2 allow us to bracket the time at which

carbonate precipitation begins in experiments containing 0.5 M NaCl (between 74 and

94 days). More specifically, Experiment 1 lasted 74 days and did not precipitate

carbonate before depressurization, but Experiment 2 lasted 94 days and precipitating

Mg-carbonate consumed 14 mol % Mg from the starting olivine. Thus, in the case of

Experiment 2, magnesite precipitation occurs over a maximum of 20 days. Further

complicating the calculation of magnesite precipitation is the lack of a known

available surface area for precipitation as the experiments were not seeded with

magnesite crystals. As an estimate of the surface area, we use the final BET surface

area, which accounts for both available olivine and silica surface areas. Taking the

54

above points into consideration, our magnesite precipitation rate is >1.40 x 10-13

mol

cm-2

s-1

, which is 5 orders of magnitude greater than predicted by Saldi et al. (2009).

For the comparison, we used the second-order rate expression from Saldi et al. (2009)

and assumed a surface area equal to the final BET area of 1.39 m2, a time of 20 days, a

saturation index of 2, and corrected the rate constant for temperature using an

Arrhenius-type relationship and an activation energy of 159 kJ/mol (from Saldi et al.

2009). In order to match our estimated precipitation rate with that predicted by

equation 5 from Saldi et al. (2009) for nucleation on pre-existing magnesite surfaces,

we would need to have a larger surface area available for magnesite precipitation

and/or lengthen the time over which the magnesite precipitated. A third possibility is

that the iron from olivine (Fo92) is incorporated into magnesite, which has been

shown to increase the rate of magnesite precipitation (Saldi et al., 2013) and is evident

in EDS data (Fig. 2.4E). An additional caveat regarding the comparison of our

estimated precipitation rate with that from Saldi et al. (2009) is that they measured

magnesite precipitation rates on magnesite crystal seeds, which have a different

surface energy than the phases in our experiments. We also acknowledge that the

factors that control crystal formation are nucleation and growth rates, neither of which

are measurable with our experiments as presented here. Nevertheless, the rates we

calculate represent a minimum bound on the rate of carbonate precipitation under

these experimental conditions, and suggest that carbonate precipitation may not limit

mineral carbonation in the long-term, once sufficient supersaturation is reached with

respect to the precipitating phase.

2.5 Conclusions

Experimental results demonstrate the temporal evolution of olivine carbonation

in a batch reactor where olivine dissolution (reaction 2), SiO2(am) precipitation

(reaction 3), CO2 dissolution/dissociation (reactions 4-6), and magnesite precipitation

(reaction 7) all occur simultaneously. Our results suggest that once a critical level of

magnesite supersaturation is achieved, magnesite precipitation occurs at a faster rate

than previously predicted (Saldi et al. 2009). In agreement with previous studies, a Si-

rich passivating layer forms on olivine surfaces initially and can persist for many days,

55

potentially limiting reaction rate (e.g., Daval et al. (2009)). In addition, we have

provided further evidence that olivine dissolution rate decreases with increasing

aqueous silica concentration as previously reported by Daval et al. (2011) and

Pokrovsky and Schott (2000b). Our rates are consistent with those predicted by

previous (CO2-free, low H4SiO4) models and studies, particularly at 4 < pH < 5 and

with 0.5 M added NaCl, but unlike the models, we do not see the rates decrease with

increasing pH. Combination of these observations suggests that either CO2 limits the

reaction at low pH but promotes dissolution at mildly acidic pH, or that the rate-

limiting step under high dissolved SiO2 conditions is the destruction of the Si-rich

layer, which is pH-independent.

Comparison of experiments with 0.5 M NaCl with those lacking NaCl in

distilled water suggests two different rate regimes, possibly governed by two different

dissolution mechanisms. The first regime extends from 0-5 days and is characterized

by rapidly slowing dissolution measured by Mg, Si, or alkalinity. In this regime, the

NaCl-free experiments show higher rates and achieve higher Mg, Si, and alkalinity

concentrations. The second regime begins at about day 10 (in experiments with

background electrolyte, later in the salt-free experiment) and is distinguished by a

constant dissolution rate (measured by Mg or alkalinity) and Si concentrations at or

above saturation with respect to SiO2(am). In this regime, the NaCl-free experiment

had a significantly slower dissolution rate than the experiments with NaCl. This effect

is not included in most commonly used rate laws for olivine dissolution.

Based on the results of this study, further work should be targeted on the

formation and destruction of the passivating Si-rich layer. Two models for formation

have been proposed: the first is a leaching model, in which Mg is preferentially

removed from the olivine surface leaving behind a polymerized network of SiO4

tetrahedra (Bearat et al., 2006; Daval et al., 2011; Oelkers, 2001b; Pokrovsky and

Schott, 2000a, 2000b); the second is a dissolution/reprecipitation model in which Mg

and Si leave the surface at the same rate, but SiO2 re-precipitates at the mineral-fluid

interface (Hellmann et al., 2012; King et al., 2011). We consider these two models to

be end members of a continuum rather than two discreet ideas, and that the layer

56

formation may be a result of a hybrid of the two. Our future work will more explicitly

address this point. Understanding the mechanism of formation of the silica-rich layer

is an important first step in developing a method to prevent its formation/encourage its

destruction and is essential for the development of accurate geochemical models

addressing carbon storage in mafic and ultramafic rocks.

2.6 Acknowledgments

We would like to acknowledge the Global Climate and Energy Project (GCEP-

48942) at Stanford University for funding this project, along with technical assistance

from Bob Jones and Guangchao Li. We also acknowledge the Stanford

Nanocharacterization Laboratory, where many of the analyses were performed.

57

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Wolery T. J., Jackson K. J., Bourcier W. L., Bruton, C. J., Viani B. E., Knauss

K. G. and Delany J. M. (1990) Current Status of the EQ3/6 Software Package for

Geochemical Modeling. In Chemical Modeling of Aqueous Systems II pp. 104–116.

Zakaznova-Herzog V. P., Nesbitt H. W., Bancroft G. M. and Tse J. S. (2008)

Characterization of leached layers on olivine and pyroxenes using high-resolution

XPS and density functional calculations. Geochimica et Cosmochimica Acta 72, 69–

86

63

.

Chapter 3: The role of the Si-rich surface layer in olivine dissolution 1: High-resolution TEM study

Natalie C. Johnsona,*

, Ariel Jacksonb, Burt Thomas

c, Robert J. Rosenbauer

c,

Dennis K. Birdd, Gordon E. Brown, Jr.

a,d,e, Kate Maher

d

a. Department of Chemical Engineering, Stauffer III, 381 North-South Mall, Stanford University, Stanford, CA 94305, USA

b. Department of Materials Science and Engineering, 496 Lomita Mall, Durand Building,

Stanford University, Stanford, CA 94305, USA

c. U.S. Geological Survey, 345 Middlefield Rd, Menlo Park, CA 94025, USA

d. Department of Geological & Environmental Sciences, 450 Serra Mall, Braun Hall Building 320,

Stanford University, Stanford, CA 94305-2115, USA

e. Department of Photon Science and Stanford Synchrotron Radiation Lightsource,

SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA

Submitted to Geochimica et Cosmochimica Acta, June 2014.

64

Abstract

Olivine (Mg2SiO4) is a reactive Mg-silicate mineral that could serve as a cation

source for subsurface carbon dioxide (CO2) mineralization as part of a global carbon

management strategy. However, olivine must dissolve in order to produce free Mg2+

,

and the dissolution process may be hindered by the formation of a Si-rich surface

layer. In order to assess the formation and evolution of the surface layer, olivine was

reacted with water and CO2 in the presence of an electrolyte at conditions relevant for

subsurface storage (60 °C, 100 bar pCO2). Parallel experiments, lasting up to 19 days,

were conducted under well-mixed and unmixed conditions. Dissolution proceeded 4

times faster in the mixed experiment relative to the unmixed after 19 days, suggesting

that the unmixed experiment was transport limited rather than surface-reaction

controlled. Transmission electron microscopy (TEM) cross sections were prepared

from reacted olivine grains after 2 and 19 days of reaction, and analyzed for

crystallinity and chemical composition as a function of depth. Several types of Si-rich

surface layers were observed: Mg-depleted olivine (crystalline, but enriched in Si), an

“active” layer (amorphous, Mg/Si changes with depth), and a newly precipitated layer

(amorphous, Mg/Si<0.3). Magnesium-depleted olivine was only present in the mixed

experiments, and the precipitated layer was only visible in experiments that exceeded

SiO2(am) saturation in the bulk fluid. The active layer was present on all reacted

olivine examined. Results suggest that the active layer forms first (in 2 days or less),

during the time that both incongruent dissolution and a decrease in dissolution rate are

observed, whereas the precipitated layer forms later and does not passivate the mineral

surface.

65

3.1 Introduction

The reaction of (Mg,Fe,Ca)-silicates with CO2-rich fluids to form stable

carbonate minerals provides a long-term storage option for anthropogenic CO2.

However, the slow reaction kinetics and the formation of a silica-rich layer on the Mg-

silicate surface may limit widespread industrial implementation of this approach

(Bearat et al., 2006; Daval et al., 2011; Oelkers et al., 2008; Chapter 2). Knowledge of

the underlying mechanisms that control olivine dissolution is required before

strategies to enhance the dissolution rate can be developed. In addition, improved

understanding of the processes associated with olivine dissolution may have

implications for other silicate minerals

Numerous studies of olivine dissolution in mixed-flow and plug-flow reactors

have demonstrated that olivine dissolution rates increase with increasing temperature,

and decrease with increasing pH (Hänchen et al., 2006; Mazzotti et al., 2010; Oelkers,

2001; Pokrovsky and Schott, 2000a; Prigiobbe et al., 2009; Wogelius and Walther,

1992, 1991). Wang and Giammar (2013) conducted batch experiments and also found

olivine dissolution rates to increase with increasing temperature, although they did not

examine rate as a function of pH. In another set of batch experiments, we observed

little effect of pH on dissolution rates at intermediate reaction times (10-70 days) and

mildly acidic pH (pH=4-6) (Chapter 2).

The differing results between experiments conducted in batch reactors and

flow through/mixed flow reactors may yield insights into the processes occurring at

the mineral surface. One important distinction is that flow reactors allow for the

careful control of the aqueous composition, whereas batch experiments allow the

aqueous phase to evolve throughout the duration of the experiment. Most flow

reactions are conducted far from equilibrium with respect to the primary phase

(olivine) and secondary phases (amorphous silica and magnesite); while batch

reactions may reach or exceed saturation with respect to multiple secondary phases.

For example, Oelkers (2001) studied the effect of dissolved Si and Mg on olivine

dissolution and found no effect on the rates in the range 0 < [Si] < 0.62 mmol/kg and 0

< [Mg] < 1.36 mmol/kg. However, these ranges do not extend to either silica

66

saturation (2 mmol/kg at 25 °C) or magnesite saturation (no carbonate species were

present), meaning the experiments were conducted far from equilibrium with respect

to likely secondary phases. In contrast, we found the olivine dissolution rate to depend

strongly on aqueous [Si] near amorphous silica saturation (Chapter 2) along with

Daval et al. (2011), and Sissmann et al. (2013),.

Understanding secondary phase formation is critical to understanding olivine

dissolution, as a Si-rich phase is known to form on olivine surfaces during dissolution

(Bearat et al., 2006; Daval et al., 2011; King et al., 2010; Pokrovsky and Schott,

2000b; Sissmann et al., 2013; Zakaznova-Herzog et al., 2008). Two hypotheses have

been proposed to explain the origin of this Si-rich surface coating. In the “leached

layer hypothesis,” the Si-rich surface layer forms via preferential removal of Mg from

the olivine surface, leaving behind a network of polymerized silica tetrahedra

(Hellmann et al., 1990; Pokrovsky and Schott, 2000a; Ruiz-Agudo et al., 2012;

Zakaznova-Herzog et al., 2008). The “precipitated layer hypothesis” describes local

areas of amorphous silica saturation near the olivine surface, resulting in a layer of

precipitated SiO2 (Hellmann et al., 2013, 2012; King et al., 2011, 2010). One line of

reasoning supporting the precipitated layer theory is that solid-state diffusion is quite

slow and leached layer formation requires the diffusion of cations through the layer,

which would limit the potential thickness of the surface layer (Hellmann et al., 2012).

To date, it is unclear whether the Si-rich layer passivates the olivine surface and

decreases the dissolution rate; some studies have shown that dissolution rates decrease

continually after the Si-rich layer develops (Daval et al., 2011, 2009; Hellmann et al.,

2012) while others have not observed a substantial effect (King et al., 2010). A

precipitated layer may be porous initially, but later secondary phases (i.e. carbonates,

phyllosilicates) may precipitate in the pores and reduce the permeability of the surface

layer (Hellmann et al. 2013). Recent work also suggests that Fe3+

may play an

important role in stabilizing the Si-rich layer and slowing olivine (Fo88) dissolution

(Saldi et al., 2013; Sissmann et al., 2013), at least until conditions become sufficiently

reducing to dissolve the Fe-phase, at which point dissolution resumes with a spike in

aqueous Fe concentration (Sissmann et al., 2013).

67

Several studies that have examined surface layer formation using high

resolution Transmission Electron Microscopy (TEM) have observed a Si-rich surface

layer, ranging from 1-1000 nm thick, on a variety of silicate minerals (Daval et al.,

2013, 2009; Hellmann et al., 2013, 2012; Sissmann et al., 2013). These surface layers

are generally observed to be amorphous, porous, and silica-rich with sharp, step-like

chemical gradients between the fresh mineral surfaces and surface layers. Transport

calculations suggest that cation diffusion through the surface layer is not the limiting

step in the overall reaction; rather, the rate is controlled by the surface reaction at the

fresh mineral-fluid interface (Daval et al., 2009; Hellmann et al., 2012). Conversely,

Schulze et al. (2004) studied surface layers that form during serpentine dissolution

using TEM and XPS, and based on their results, hypothesized that cation diffusion

through the surface layer is limiting. To our knowledge, there has been only one study

that explicitly compares dissolution rate with Si-rich layer thickness, and this study

focused on diopside (Daval et al., 2013). No such studies have yet been published for

olivine.

Although numerous studies of olivine dissolution exist in the literature, few

have been carried out in the presence of CO2. Further, many studies have observed the

formation of a Si-rich layer on the olivine surface during dissolution, but none to our

knowledge have probed the surface layer in depth in order to understand its

composition, formation mechanism, temporal evolution, and role in passivating

olivine surfaces. The objective of the present study is to use high-resolution,

nanometer-scale techniques to study the Si-rich layer that forms when olivine

dissolves in the presence of CO2 and H2O to understand both how such layers form

and how they participate in the dissolution reaction.

Our study is based on a series of four experiments designed to investigate the

effects of transport and reaction time on the Si-rich surface layer. Reaction progress in

each experiment is tracked using time-resolved solution compositions. We present

TEM data from reacted olivine cross-sections at two time intervals, which give insight

into the chemical composition, level of crystallinity, and formation mechanisms of the

observed surface layers. We finish with a simple diffusion model to show that

68

diffusion through the amorphous surface layer is sufficient to maintain the dissolution

rates we measure.

3.2 Methods

3.2.1 Autoclave reactor experimental system and sampling procedures

Experiments were carried out in a flexible, inert, Au reaction cell placed inside

a steel autoclave, as described in detail by Rosenbauer et al. (1983) with modifications

for sampling CO2 (Chapter 2; Rosenbauer et al., 2005). The Au cell was surrounded by

pressure fluid (DI water) and attached to a titanium sampling tube and valve. The

combination of a flexible reaction cell, pressure fluid, and sampling tube allows for the

removal of fluid samples from the reaction vessel without changing the pressure

inside. The reaction cell was cleaned with a progression of reagent grade acids (nitric

acid, HCl, and 1% HF in nitric acid), and then baked at 430 °C under air for at least 12

hours in order to build a thick, inert oxide layer on the titanium components. Reactants

were placed inside the Au cell (DI water, 75-105 um olivine at a 50:1 solution:rock

ratio by mass, 0.5 M NaCl), which was sealed and placed inside the steel autoclave

and the annular space filled with DI water. After sealing the vessel, the autoclave was

placed inside a rocking furnace and heated to 60 °C (Rosenbauer et al., 1983). Once

this temperature was achieved, the pressure was increased to 100 bar by injection of

liquid CO2. The volume of injected CO2 as calculated at reaction conditions (60 °C,

100 bar) was 1/10 the volume of the aqueous phase in addition to sufficient CO2 to

saturate the aqueous phase at reaction conditions (Duan et al., 2006). See Chapter 2 for

a more detailed description of the experimental system.

Four experiments comprised this study. All four were conducted at the same

temperature and pressure conditions with the same reactants. Two of the experiments

were rocked at a rate of 8 rotations/minute in the furnaces, ensuring that they were

well mixed. The other two experiments were held stationary, with run durations of 2

and 19 days (Table 3.1).

69

Aqueous samples were removed from the reactor at regular intervals

throughout the duration of each experiment and were analyzed for alkalinity,

elemental concentration, and dissolved CO2 concentration. Complete aqueous

sampling procedures are presented in Chapter 2. Briefly, fluid compositions were

measured by inductively coupled plasma optical emission spectroscopy (ICP-OES),

alkalinity measurements were made via titration with 0.16 N sulfuric acid, and

dissolved CO2 concentrations were measured using coulometry (phosphoric acid

digestion followed by electrochemical analysis of released CO2 gas). The uncertainty

of ICP measurements is ±10%. Speciation calculations were completed using the

software package PHREEQC (Parkhurst and Appelo, 1999), and the included llnl.dat

database, which is derived from the EQ3/EQ6 database (Wolery et al., 1990).

Hydrogen concentrations in the CO2 phase were also measured for one

experiment to better constrain the redox state. The scCO2 phase was sampled in the

same way as the aqueous phase (using a three-way stopcock that allowed for purging

the exit tube of water and isolation of the sample), and was drawn into a

polypropylene syringe. The three-way stopcock was removed from the reactor and

attached to a needle, which was used to puncture the rubber stopper of a 5 times

evacuated (then backfilled with He) glass vial. The glass vial containing the CO2 and

H2 was stored in a freezer until analysis. Analysis was completed on a Agilent 6890

Series Gas Chromatograph (GC) with a pulse discharge detector and He as the carrier

gas. Peak area integration was performed using Agilent ChemStation software, and

quantification was completed using a four-point calibration curve encompassing H2

concentrations from 100 to 800 ppm. Uncertainty from the calibration was

significantly lower than the standard error for each data point.

Table 3.1: Conditions of four experiments.

Experiment name Duration Well mixed?

2-S 2 days No

2-R 2 days Yes

19-S 19 days No

19-R 19 days yes

70

3.2.2 Sample Preparation

This study used olivine from the Twin Sisters Dunite in Washington, with a

composition of Mg1.84Fe0.16SiO4 (Fo92). For a detailed description of this material see

Chapter 2. The mineral powder was prepared by washing with methanol 3 times and

sieving to obtain the size fraction 75-105 µm. The BET surface area was measured

with an ASAP 2020 (Micromeritics Instrument Corporation) using a 7-point surface

analysis and nitrogen as the adsorbent and found to be 5735 ± 97 cm2/g. Dissolution

rates were calculated using the BET surface area and Mg concentrations as a function

of time.

3.2.3 Transmission electron microscopy sample preparation and analysis

Transmission electron microscopy (TEM) samples were prepared using a

Helios NanoLab 600i DualBeam FIB/SEM by FEI, equipped with a Ga+ ion beam in

addition to an electron beam. Reacted olivine samples were attached to SEM mounts

and plasma-coated with gold before placement inside the FIB. Once in the

microscope, a flat area of at least 4x10 µm was chosen from which to cut the cross

section, and the area of interest was coated with 200 nm of Pt or C using electro

deposition. An additional 1 µm thick coating of Pt or C was then deposited using the

Ga+ ion beam. The combination of electro deposition followed by ion deposition

successfully shielded the mineral surface from the destructive ion beam. Once the

surface was protected, two large rectangles of material were removed by ion milling

from the surface, leaving a 3-4 µm thick slice between them. The sample was then

rotated and ion milling was used to make a U-shaped cut on the sides and bottom of

the slice. An Omniprobe AutoProbe 200 in situ sample lift-out system was used to

remove the slice from the olivine grain and transfer it to a copper Pelco® FIB lift-out

half grid for TEM samples. The slice was welded to the grid using Pt ion deposition,

then polished with ion milling to < 100 nm thick. The ion beam was set to an

accelerating voltage of 30 kV for most of the process, but dropped to 3-5 kV for the

final polishing, which reduced the thickness of the amorphized surface layer caused by

the ion beam to about 5nm (such that a 100 nm thick slice would have 90 nm of

71

crystalline material and 5nm of amorphous material on each side).

TEM analysis was completed on an FEI Tecnai TEM at 200 kV and a FEI

Titan TEM with spherical aberration image correction at 300 kV. Energy Dispersive

Spectroscopy (EDS) line scans were collected in scanning TEM (STEM) mode using

either an EDAX SUTW or Oxford SSD EDS detector. O-K, Mg-K, Si-K, Fe-K,

and Au-L elemental peaks were detected and the EDS peak analysis was performed

using TIA (Tecnai Imaging Analysis). The bulk olivine phase at the base of each

sample was used as an internal standard to extract sensitivity factors (k-factors) for the

peaks (except for Au), allowing for quantitative analysis of the composition across the

line scan. At least two deep scans (>700 nm) were performed per sample in order to

determine sensitivity factors. The maximum achievable resolution was 2 nm between

spots and each analyzed spot had a radius of less than 1 nm. A higher spot density

resulted in artificially low Mg/Si due to beam damage, as the electron beam appeared

to evaporate the Mg without detecting it.

Cross sections were cut from two different reacted mineral grains from

experiments 2-S and 19-R to ensure that the data obtained were representative and

uniform. In all cases, multiple TEM images were taken of each cross section and

multiple EDS line scans were performed. Each TEM image shown is representative of

the olivine surface from that sample, and each EDS linescan is the average of three

linescans from the same sample. TEM images and EDS line scans were taken from the

same cross section but not from the same location on each cross section. Visual

inspection demonstrated a high level of uniformity across each 10 µm cross-section.

3.2.4 TEM image processing: IFFT analysis

Some TEM images of the olivine samples have visible crystal lattice fringes,

but at lower zoom levels those fringes are difficult to see with the naked eye. An

Inverse Fast Fourier Transform (IFFT) analysis was performed on these images to

clarify which regions were crystalline and which were amorphous using ImageJ

software (Rasband, 1997). The first step is to take a Fourier Transform of the image of

interest, which produces another image in the frequency domain. Bright spots in the

Fourier Transform image are representative of periodic regions in the original image.

72

The frequencies of the spots were selected to pass the filter, while all other frequencies

were masked, and an inverse Fourier transform was performed. The result of this

procedure is an image similar to the original, but showing only the periodic regions as

a series of regular stripes. The IFFT image was used to draw false color on the original

image to clearly show which regions are crystalline. This process is diagramed in Fig.

3.1.

Figure 3.1: Steps of IFFT analysis. First, the TEM image is taken using the microscope (A).

The image is then transformed using a Fast Fourier Transform, which yields a second image

in the frequency domain (B). Bright spots on this image represent periodicity, so those

particular frequencies are selected and the rest are masked (C). An Inverse Fast Fourier

Transform is then applied to the masked frequency domain image to recreate the original

image showing only the regions of periodicity (D). The periodicity in (D) is distorted due to

aliasing (relatively low resolution in the image results in a high frequency periodicity from

the original image (A) appearing to have a lower frequency). This IFFT image was then

overlaid on the original TEM image (E) and false color was added to show periodic regions

and the gold surface coating (F).

73

3.3 Results

3.3.1 Solution Composition

Solution compositions as a function of time are plotted for four experiments in

Fig. 3.2 and shown in Table 3.2. In all four experiments, Mg increased throughout the

duration of each experiment (Fig. 3.2A). Experiment 19-R released the most Mg, three

times more than experiment 19-S. Similarly, experiment 2-R released twice as much

Mg as experiment 2-S. Silicon also

increased in all four experiments,

though experiment 19-R reached a

maximum concentration at 6 days (Fig.

3.2B). The other three experiments

showed increasing Si for the duration of

each experiment. Experiments 19-R and

19-S exceed amorphous silica saturation

at 2 days and 14 days, respectively, but

2-R and 2-S do not reach saturation.

Silica saturation was calculated using

experimental conditions, PHREEQC

(Parkhurst and Appelo, 1999), and the

included llnl.dat database. The pH of

each experiment remained below 6, so

the saturation remains constant. All

experiments remained undersaturated

with respect to magnesite. Comparison

of solution data from experiments

conducted under identical conditions (2-

R with 19-R and 2-S with 19-S) shows

the reproducibility over two days.

Table 3.2: Solution data from four experiments

time

(days)

[Mg]

mM

[Si]

mM

2-S 0.00 0.02 0.00

0.04 2.86 0.59

1.04 5.55 1.28

2.04 5.43 1.35

2-R 0.00 0.43 0.09

0.04 6.25 1.13

0.13 7.43 1.62

0.25 9.01 2.36

0.50 10.25 2.92

1.00 9.33 2.61

1.33 10.17 2.84

2.00 11.03 3.10

19-S 0.00 0.01 0.45

0.04 2.28 0.37

1.13 5.54 1.19

4.29 8.80 2.44

6.06 9.22 2.72

14.15 13.19 4.29

18.96 14.51 4.56

18.96 13.97 4.70

19-R 0.00 3.31 1.06

0.04 7.69 1.88

1.14 10.81 3.83

2.76 13.06 5.21

6.07 22.09 7.01

14.14 32.30 4.62

18.82 51.43 6.31

18.86 49.05 5.77

74

3.3.2 IFFT Analysis: Mapping Crystallinity

IFFT analyses were performed on a TEM image of reacted olivine from each

experiment in order to distinguish crystalline domains from amorphous domains (Fig.

3.3). False color was added for clarity. All olivine cross sections were coated with

gold (after reaction) to protect the surface during imaging and cross-section

preparation; the gold is clearly visible as dark material on the left side of each TEM

image. Also visible are the amorphous regions (uncolored) and crystalline regions

(green). Unreacted olivine (Fig. 3.3A) does not show an amorphous region at the

Figure 3.2: Mg (A) and Si (B) concentrations as a function of time for four

experiments. Amorphous silica saturation is indicated by the dashed line in (B).

75

mineral surface. Olivine lattice fringes extend 10 nm into the gold coating, which may

be a result of uneven surface topography on the olivine surface and the TEM image

represents a 2D projection of the 3D structure. After 2 days of reaction (Fig. 3.3B-C),

an amorphous layer of thickness 21-26 nm formed. After 19 days of reaction (Fig.

3.3D-E), the layer expanded to 39 nm (19-S) and 65 nm (19-R) thick. In three of the

images (Fig. 3.3B,D-E), some of the gold coating appears to have penetrated the

surface layer and deposited inside pores, as evidenced by the darker spots inside the

amorphous regions. Cross-sections from two different mineral grains from both

samples 19-R and 2-S were examined to determine the uniformity of the surface layer

and were found to be in agreement with each other. TEM images of larger areas (at

lower zoom levels) also show uniformity and provide confidence that images we show

are representative.

Figure 3.3: Representative TEM crystallinity maps of unreacted (A) and forsterite from

experiments 2-S (B), 2-R (C), 19-S (D) and 19-R (E). Green areas on the right of each image are

crystalline, yellow-colored regions on the left are a protective gold layer deposited on the mineral

surface (colored version online). Uncolored areas are amorphous. The scale bar in (E) applies to all

reacted forsterite (B-E).

76

3.3.3 Chemical compositions of surface layers

The chemical compositions of reacted olivine surfaces are shown in Fig. 3.4 as

Mg/Si and Fe/Si molar ratios plotted as a function of depth. The Mg/Si ratio for the

ureacted olivine is 1.84. After two days of reaction, mineral surfaces (solid-aqueous

interface) are depleted with respect to Mg and the Mg/Si ratio changes as a function of

depth (Fig. 3.4A-B). Olivine reacted for 2 days shows an increase in the Mg/Si ratio at

the mineral-fluid interface (<10 nm depth). After 19 days of reaction, olivine is also

Figure 3.4: TEM/EDS linescans showing Mg/Si ratio as a function of depth in forsterite reacted

without mixing (A) and with mixing (B). Forsterite from all four experiments had a Si-rich (Mg-

depleted) surface layer at least 20 nm thick. Linescans showing Fe/Si ratios are also shown for the

well-mixed experiments (C) and both have a peak of Fe associated with the Si-rich layers. Ratios

were calibrated using spectra from deep in the mineral.

77

depleted in Mg at the surface (Fig. 3.4A-B) but contains two distinct regions: one in

which the Mg/Si ratio is constant with depth (0 to 50 nm depth) and one in which the

Mg/Si ratio changes with depth (19-R only). Both well-mixed experiments (2-R and

19-R) contain a region of Mg depletion deeper than the surface layer, while the

unmixed experiments (2-S and 19-S) maintain the bulk olivine Mg/Si ratio up to the

surface layer.

Iron is also an important component of the reacting olivine (Fo92), and the

Fe/Si ratios for experiments 2-R and 19-R are shown in Fig. 3.4C. A striking feature

visible in both experiments is the spike in Fe/Si at the same depth as the steep decrease

in Mg/Si, indicating an accumulation of iron at this depth. Olivine from experiment 2-

R has a constant Fe/Si at depths >40 nm and the maximum Fe/Si occurs at 16 nm

depth (the minimum Mg/Si occurs at 10 nm depth) (Fig. 3.4C). Olivine from

experiment 19-R has a constant Fe/Si at depths >60 nm with a maximum Fe/Si at 47

nm (Mg/Si reaches a minimum at 40 nm depth) (Fig. 3.4C). At depths shallower than

38 nm, the Fe/Si ratio is near zero indicating that little to no iron is present in this

region. In the case of the stationary experiments, no Fe spike is visible. Instead, the

Fe/Mg ratio is constant with depth at the bulk ratio of 0.09 in reacted olivine from both

2-S and 19-S.

3.4 Discussion

3.4.1 Rates

Olivine dissolution rates were calculated from Mg vs. time data for all four

experiments. For the 19-day experiments, the rates were calculated using a linear

regression of the [Mg] data for days 3-19 and normalized using the BET surface area.

Rates from the 2-day experiments were calculated with the last two data points

because the rate varies with time over the initial 2 days, and the rate from 2-S was

calculated using Si data because the Mg data showed no change between 24 and 49

hours. Again, all were normalized with BET surface area. Fig. 3.5 shows olivine

dissolution rate as a function of Si-rich layer thickness for all four experiments.

Interestingly, the dissolution rate does not decrease with increasing surface layer

78

thickness. In fact, separating the rocking experiments and the stationary experiments

into two sets suggests that the dissolution rate increases with increasing layer

thickness. However, we do not suggest a correlation between layer thickness and

dissolution rate, but merely highlight that layer thickness does not seem to have a

direct effect on dissolution rate in our experiments. This result suggests that the Si-rich

surface layer does not inhibit dissolution over the thicknesses of Si-rich layers we

observe. In order for the surface layer not to inhibit dissolution, diffusion through the

layer must be much be faster than the dissolution rate, which could be achieved by

connected porosity in the surface layer allowing fluid to react at the fresh mineral

surface. The rate from experiment 19-R agrees (within uncertainty) with the rates

determined previously in Chapter 2, where state dissolution occurred over periods as

long as 94 days (Table 3.3).

Mass transport at the mineral-solution interface strongly affects the rate of

olivine dissolution. Two of the experiments in this study were conducted in rotating

furnaces and rocked 180° at 8 rpm, ensuring that the solution was well mixed (2-R and

19-R). The other two experiments were conducted in the same furnaces, but they were

Figure 3.5: Forsterite dissolution rate as a function of Si-rich layer thickness. The

rate does not decrease with increasing layer thickness; in fact, within the two

different data sets (rocking vs. stationary), show that the rates increase with Si-rich

layer thickness. Error bars represent 2-sigma uncertainty due to the few (2-5) data

points available for each rate calculation. No correlation between rate and layer

thickness is implied beyond the data presented here.

79

held stationary such that no mixing occurred beyond the pressurization step (2-S and

19-S). The olivine samples in the rocking experiments dissolved faster, as measured

by both changing Mg and Si concentrations. They also reacted to a greater extent over

the same time period than the olivine samples in the stationary experiments. These

results suggest that dissolution rates from the stationary experiments were limited by

transport rather than reaction kinetics. The dissolution rates from the rocking

experiments may also be transport limited, as we did not perform experiments to

determine the rate of rocking required to remove all transport limitations. For

example, Gislason and Oelkers (2003) performed dissolution experiments at a variety

of stirring rates and found that the dissolution rate increased up to a stir speed of 550

rpm, beyond which the rate remained constant and was determined to be surface-

controlled. However, given the lower dissolution rates in our stationary experiments

relative to the rocking experiments, we can say conclusively that those experiments

are transport limited, and that the surface-controlled reaction rate is faster than the

transport rate in a non-mixed system. The transport limitation could arise from one (or

more) of the three diffusive regions in the reactor system. Carbon dioxide must diffuse

across the water-scCO2 boundary before dissolving and hydrating, and this interface is

much smaller in a non-mixed system than in a mixed one (in the rocking experiments,

we expect CO2 bubbles in the aqueous phase which increases the surface area

available for dissolution). Another possible region for diffusive limitation in the

mineral-aqueous interface, which ions must dissolve across in order to reach the bulk

fluid. In the absence of mixing, concentration and pH gradients could exist near the

mineral surface. Transport through the aqueous phase could also limit the reaction,

and an estimation of the diffusion rate is possible using the characteristic length.

Table 3.3: Olivine dissolution rates from four experiments

Experiment Rate (mol cm-2

s-1

)

1 (Chapter 2) 9.02 ± 0.80 × 10-14

2 (Chapter 2) 8.64 ± 0.43 × 10-14

19-R 1.03 ± 0.44 × 10-13

19-S 2.10 ± 0.16 × 10-14

80

The characteristic diffusion length, Lc, is defined as the length over which

diffusion occurs with diffusivity D during reaction time, t (Equation 1). The diffusion

length calculation is applicable to 19-S, in which diffusive transport through the

aqueous phase dominates, but not 19-R because mixing causes convective transport to

dominate over diffusion.

DtLc (1)

Using a diffusion coefficient of 7.1x10-6

, a typical diffusion coefficient for Mg in

water at 25 °C (Haynes et al., 2014), and reaction time of 19 days, the diffusion length

is 3.4 cm. In other words, a molecule initially at x=0 would be, on average, at x=3.4

cm after 19 days of diffusion. In our experiments, the height of the aqueous phase

separating the mineral from the CO2 is 3-6 cm, which is of the same order of

magnitude as the characteristic diffusion length. The diffusion length applies to both

Mg and Si (originating at the mineral surface) and protons (originating at the aqueous-

CO2 interface). As a result, concentration gradients of all three reacting species could

exist in the aqueous phase, even after 19 days of reaction, and diffusion is slow

enough to potentially limit the reaction rate in the absence of convective mixing.

A larger point regarding transport is that depending on injection rates and host

rock flow characteristics, some regions of an in situ mineralization project will likely

be transport limited. Based on our results, we anticipate that this limitation will not be

directly due to the formation of surface layers on reactive mineral surfaces, but rather

diffusion of ions to and/or from the dissolving mineral surface. On the pore scale, Li et

al. (2008) found that a discrepancy between well-mixed laboratory rates and natural

(simulated) rates only exists when there are both incomplete molecular diffusion and

similar reaction and transport rates, which suggests that individual pores function as

well-mixed reactors under most natural conditions. Our results are in contrast to Li et

al. (2008), but are also derived from experiments on a larger scale. Based on our data,

the kinetics of the surface-controlled dissolution reaction are less relevant than the

transport rates, and we might expect to see dissolution rates up to an order of

magnitude slower than we observe in a well-mixed laboratory reactor. In an ex situ

sequestration project, the reaction could be engineered to remove the transport

81

limitation.

Experiment 19-S was not mixed, thus may best represent the reaction rate and

mineral surface characteristics that one would expect to observe in the subsurface.

Reacted olivine from 19-S also showed the steepest chemical gradient in the surface

layer at the transition between the Si-rich surface layer and the bulk mineral. This

observation is in agreement with published studies including TEM images of natural

samples, which tend to show a very steep, step-like chemical gradient between the

surface layer and the mineral (e.g. Hellmann et al., 2013, 2012). Consequently, we

hypothesize that the absence of a shallow gradient (like that seen in 19-R) is a result of

the transport limitation. More specifically, a scarcity of protons at the mineral surface

to exchange with Mg cations could result in a slower exchange rate, and a slower

exchange rate (diffusion rate) would create a steeper chemical gradient at the mineral-

surface layer interface. More discussion on this topic is presented in Section 4.3.

3.4.2 Surface layer characterization

We observed three distinct types of surface layers from the TEM/EDS results

(Fig. 3.6). The first is 35-40 nm thick and is visible only in the 19-day experiments,

19-R and 19-S. This layer is both amorphous (Fig. 3.3D-E) and Si-rich, but the Mg/Si

ratio does not change with depth within the layer (Fig. 3.4A-B). Given that we only

observe this type of layer on olivine grains exposed to solutions supersaturated with

respect to amorphous silica, and also because of the near complete depletion of Mg

(Mg/Si = 0.1-0.3), we infer that this layer is formed by precipitation of amorphous

silica. This “precipitated layer” appears to have porosity, as the gold that was

deposited on the reacted olivine surfaces before TEM sample preparation penetrated

the surface layer and is visible as dark spots in the amorphous layer on TEM images

from 19-S and 19-R (Fig. 3.2D-E). We hypothesize that the porosity is interconnected

and does not hinder dissolution (similar to Daval et al., 2013, 2009; Hellmann et al.,

2012), because the olivine grains continue to dissolve underneath the coating at a

steady rate for up to 19 days in this study (Fig. 3.2) and up to several months in

previous work (Chapter 2). The porosity can be quantified by comparing the darkened

areas (gold) to the total area of material and the result is a porosity of up to 40%.

82

However, it's important to note that this calculation is based on a 2D projection of a

3D cross section, and there's no way to calculate the actual porosity without assuming

an average shape and size of the pores. Thus, we present only an upper bound. Further

work is currently underway to better understand the formation mechanism of this

alteration layer.

The second type of Si-rich layer sits at the mineral-fluid interface of 2-R and 2-

S (Fig. 3.6). This layer is characterized by a changing Mg/Si ratio with depth that is

about 40 nm thick. At the solid-fluid interface (<10nm), the Mg/Si ratio decreases

with depth, indicating accumulation of Mg at this interface. The Mg/Si ratio reaches a

minimum in olivine for 2-S and 2-R of 0.53 at 12 nm depth and 0.28 at 10 nm depth,

respectively. Below this layer (10-40 nm deep), the Mg/Si ratio increases until it

reaches the stoichiometric value, 1.84. Interestingly, only the top 21-26 nm of the

surface layer is amorphous (Fig. 3.3B-C), which is only about half the total thickness

Figure 3.6: Cross sectional diagram of the reacted mineral surface, specifically for

experiment 19-R. The three different Si-rich layers and their defining characteristics

are visible from top down: Precipitated layer, active layer, and Mg-depleted forsterite.

83

of the Si-rich layer. We define the 20 nm amorphous region with changing Mg/Si as

the “active layer” because it appears to be actively exchanging Mg. The characteristics

of the active layer are also visible in olivine from 19-R at a depth of 40-60 nm (Fig.

3.4B). In two experiments (2-R and 19-R), this layer also contains an increased

amount of Fe relative to the unreacted mineral and the surrounding alteration layers.

Iron in the active layer may exist in the ferric state and stabilize the layer similar to

findings from Saldi et al. (2013) and Sissmann et al. (2013). However, measurement

of hydrogen gas from the scCO2 phase of an experiment with a chemical evolution

similar to that of sample 19-S (fugacity of H2 ranged from 10-4

to 10-3

bars from 3-14

days of reaction) showed that Fe2+

concentrations were several orders of magnitude

greater than Fe3+

.

The third type of Si-rich layer occurs below the active layer (Fig. 3.6). This

layer has chemical characteristics similar to those of the active layer, but unlike the

active layer, is crystalline. We call this “Mg-depleted olivine”, which is visible in

TEM images of samples 2-S, 2-R, and 19-R (Fig. 3.4A-B). This layer extends as

deeply as 150 nm (in 19-R). For samples 2-R and 19-R we also observe maxima in the

Mg/Si ratios in the Mg-depleted olivine regions (Fig. 3.3B) at 40-50 and 70-80 nm

depth, respectively. These peaks suggest an accumulation of Mg and are not visible in

the stationary experiments.

We hypothesize that both the active layer and Mg-depleted olivine are formed

via preferential removal of Mg from the mineral surface and replacement by protons

from solution. In the active layer, protons are present to maintain charge balance, but

the remaining SiO4 tetrahedra polymerize to form a network through which Mg

cations must diffuse to reach the mineral-solution interface. This mechanism has been

proposed previously (Bearat et al., 2006; Daval et al., 2011; Oelkers, 2001; Pokrovsky

and Schott, 2000a, 2000b). In the Mg-depleted olivine regions, protons may form

hydroxyl-like bonds and maintain the olivine crystal structure. This type of Si-rich

layer has not, to our knowledge, been proposed or observed before in olivine.

However, there has been previous work on isomorphic substitution of (O4H4)4-

for

(SiO4)4-

in a variety of minerals (Aines and Rossman, 1984). Foreman (1968)

84

conducted a neutron and x-ray diffraction study on hydrogrossular and found

substitution of four protons for silicon with only slight changes to the structural

parameters; his work was later verified by computational simulations (Wright et al.,

1994) and other experiments (Aines and Rossman 1983). Hydrogen bonding occurs

within the (O4H4)4-

tetrahedra in hydrogrossular (Harmon et al., 1982). Like

hydrogrossular, olivine is a nesosilicate with isolated SiO44-

tetrahedra connected by

interstitial metal cations. One might expect that removing a silicon ion or a metal

cation would cause the structure to collapse on itself; however, at least in the case of

Si, the combination of hydroxyl and hydrogen bonding maintains the crystal structure.

We have no direct evidence that protons substitute for Mg in olivine from our

experiments, but we suggest this mechanism as a way to explain our data that show

Mg-depleted, crystalline regions far from the mineral-fluid interface (up to 150 nm

deep).

Further evidence for the plausibility of proton substitution for Mg in the M1

and M2 sites exists in the hydrous olivine literature. Olivine is generally an anhydrous

mineral (Khisina et al., 2001), but it has been observed to hold up to 0.12 wt% water

(Kohlstedt et al., 1996). Hydrous regions in olivine are known to exist in three

different forms: lamellar defects, small (10 nm) inclusions, and large (100 nm)

inclusions (Khisina et al., 2001). Khisina et al. (2001) measured the concentrations of

Mg, Fe, and Si across the inclusions and found that the Si concentration is the same as

that of the host olivine, so the regions are depleted in Mg and Fe similar to the Mg-

depleted layer in olivine from our experiments. Incorporation of protons and hydroxyl

ions into olivine should affect the structure around the inclusions/defects as well as

bond strengths (Churakov et al., 2003; Haiber et al., 1997) and may affect the

dissolution rate as well (Rimstidt et al., 2012). For example, protons are more

electronegative than Mg cations (2.2 vs. 1.3 Pauling Units, respectively), and we

would expect them to pull electron density away from other bonds in the crystal,

effectively weakening those bonds.

Based on our TEM/EDS data and crystallinity maps, in the absence of

transport limitations, we propose that all three types of Si-rich layers exist on olivine

85

surfaces that have reacted with water and CO2 for times sufficient for the bulk solution

to reach saturation with respect to amorphous silica. The sample from experiment 19-

R fits these criteria, as it exceeded silica saturation and was continuously rocked,

ensuring a well-mixed aqueous phase. Over shorter timescales (or lower reaction

extent), amorphous silica saturation is not reached and the precipitated layer does not

form (e.g., samples 2-S and 2-R). The formation of a precipitated layer does not

depend on transport beyond the effect of transport on overall reaction rate; i.e.

stationary experiments proceeded more slowly and thus took longer to reach

amorphous silica saturation. One might expect a non-mixed experiment to precipitate

amorphous silica even if the bulk silica concentration is below saturation as there

could be locally saturated regions near the olivine surface; however, we did not

observe this.

3.4.3 Diffusion Modeling

In order to investigate whether or not the measured concentration gradients

are the result of diffusion, we used a series of diffusion equations from Lasaga (1979)

and Hellmann et al. (2012). All modeling was done assuming steady state in the

mineral and alteration layer (dc/dt = 0) and thus was only performed on data from the

19-day experiments because they exhibited constant Mg release with time after 3 days

(steady-state dissolution). Modeling was based on Fick’s Second Law for diffusion

with a term added to account for the retreating reaction front as the mineral dissolves

(Equation 2), where a is the velocity at which the mineral surface retreats, c is the

normalized concentration of magnesium (concentration at depth x divided by the bulk

concentration), D* is an effective diffusion coefficient, and x is depth (Doremus, 1975;

Hellmann et al., 2012).

(2)

Equation 2 is a second-order ordinary differential equation, and since the diffusion

coefficient depends on concentration, the ODE must be solved in two steps. The first

integration results in the following expression:

0

x

ca

x

cD

xt

c *

86

constant* acdx

dcD (3)

Deep in the mineral (at large x), the change in cation concentration with depth is zero

and the normalized cation concentration is 1 (dc/dx =0, c=1). This constitutes the

boundary condition to solve for the integration constant in Equation 3, which is equal

to a, and reduces the second order ODE in Equation 1 to the first order ODE in

Equation 4.

*

)1(

D

ca

dx

dc (4)

The effective diffusion coefficient in this case is derived from Equation 15 in

Lasaga (1979), which describes interdiffusion of two ions in a silicate matrix. The

expression assumes that the silicate matrix is stable and that oxygen and silicon

diffusivity are negligible (Lasaga, 1979). In our system, the silicate matrix is not stable

and does dissolve; however, the presence of crystalline regions that are Mg-depleted

suggests that the destruction of Si-O bonds and diffusion of Si and O are slower than

the diffusion of Mg and H+. The expression for the diffusion coefficient is based on a

mean-field model, i.e. the transient effect of individual moving ions on other ions is

not included. Finally, the model assumes a fixed volume, because moving ions have a

very small volume relative to the volume of the silicate network (Lasaga, 1979). In the

case of olivine dissolution, isolated SiO4 tetrahedra must rearrange to form new Si-O-

Si bonds and the associated volume change is about 50%. However, we use the model

only to study the steady-state case, when Mg release is constant with time. Our TEM

evidence suggests that the active layer thickness does not change significantly with

time after the initial 2 days of reaction (21 nm in 2-R and 25 nm in 19-R) and thus the

volume change is negligible within the amorphous layer. The effective diffusion

coefficient D*

is presented in Equation 5, and is a function of the tracer diffusion

coefficients of Mg (DMg) and H (DH), the concentration of Mg (c) (Lasaga, 1979) and

a concentration-dependent structural factor, α, following Hellmann et al. (2012) (see

Appendix 4 for derivation).

ccDcD

cDDD

HMg

HMg

11

)1(4

)13(* (5)

87

The concentration (and thus depth) dependent structural factor, α was added by

Hellmann et al. (2012) to account for physical changes in the altered layers, i.e. the

areas with low cation concentration are also porous and accordingly are expected to

have faster diffusion and higher diffusivity. Hellmann et al. (2012) used an α value of

-0.9 to generate the largest effect of D* on concentration, such that D* is constant for

c>0.1 and then increases rapidly at c<0.1. Using Equation 5, values of α greater than

0.3 resulted in a non-monotonic increase of D* with decreasing concentration, such

that a minimum D* was achieved between c=1 and c=0, when the minimum should

exist at c=1 since this is the region of unaltered olivine (Fig. 3.7A). For the remaining

calculations, we set α=-0.3 because this was the smallest value for which D* increased

monotonically with decreasing concentration.

The dependence of D* on concentration necessitated the use of a numerical

solver to obtain the concentration gradient from Equation 4. We used Matlab and the

function “ode45” for numerically solving non-stiff differential equations. We used

Equations 1-4 to model only the "active" layer of reacted olivine grains. The model

was developed from studies of sodium diffusing in glass materials and thus is not

applicable to crystalline regions (in which diffusion occurs via a different mechanism).

Also, we assume that diffusion through the precipitated surface layer is fast relative to

solid-state diffusion, as it likely consists of cations diffusing through water in pores.

Diffusion coefficients of ions in solid phases vary greatly as a function of

temperature, diffusing species, and the matrix, and estimation is not accurate. For

example, the diffusion coefficient of hydrogen in SiO2 at 200 °C is 6.5E-10 cm2/s

(Cussler, 1997), of Na in rhyolite glass at 60 °C is 6.7E-16 cm2/s (Jambon, 1982) and

the coefficient for interdiffusion of Mg and Fe in olivine at 200 °C is 1.78E-13 cm2/s

(Buening and Buseck, 1973). Further insight regarding the values of tracer diffusion

coefficients can be obtained by observing the limits of Equation 5 as the magnesium

concentration, c, goes to zero and to one. When c=0, the equation reduces to

D*=0.7DMg, a condition that exists in the most altered (Mg-poor) region, and we

follow Hellmann et al. (2012) in assuming that diffusion in these regions is relatively

fast. Thus, we estimate that a reasonable interdiffusion coefficient in the altered region

88

is 10-12

to 10-16

cm2/sec. Setting c=1 gives us the effective diffusion coefficient deep

in the mineral, and the expression simplifies to D*=DH. We used 1E-16 cm

2/s value as

a starting point, following Hellmann et al. (2012), and then assessed the diffusivities

Figure 3.7: Simple diffusion model in which the diffusion coefficient, D*, is a function of

Mg concentration in addition to diffusivity of protons (DH) and of Mg (DMg), plus a

structural factor (α) (A). Decreasing from α 0 to -0.3 results in flattening the profile, and

reducing it further to -0.9 creates a minimum value of D* at c≈0.1. Changing DMg results in a

shift of the concentration gradient curve (B) and changing DH affects both the steepness and

depth of the curve (C). Data from the two 19 day experiments can be fit with this model and

different values of DH (D). Vertical bars indicate the transition from amorphous to crystalline

material, and the model was shifted to the right to align with the “active” layer.

89

required to fit the data. Several glass corrosion studies have verified that DMg>>DH

(e.g., Smets and Lommen, 1982). Also, while the values chosen to fit our data are

larger than diffusion coefficients from tracer diffusion studies, evidence suggests that

in altered, hydrated glass layers ionic transport is faster than in dry glass (Doremus,

1983).

Figs. 3.7B-C show concentration gradients calculated from Equation 5 with a

range of DMg and DH values and a = 1.5E-10 cm/s (calculated from the dissolution rate

of 19-R). In general, the slope is controlled by DH (a lower DH results in a steeper

slope) and the depth of the starting point of the slope is controlled both by DMg and

DH. Depending on which values of DMg and DH are selected, nearly any concentration

gradient can be generated. Thus, one can even produce a very steep, step-like gradient

using this equation, which removes the argument that a steep concentration gradient

precludes the existence of a leached layer. In fact, the slower the diffusion of protons

relative to Mg, the steeper the gradient becomes. Fast Mg diffusion relative to H

diffusion means that the removal of Mg from the mineral is limited by the availability

of protons with which to exchange.

Fig. 3.7D shows calculated concentration gradients that were fit to our EDS

data. The data were shifted and scaled using the bulk Mg/Si ratio of 1.84 such that the

precipitated layer is defined by c = 0 and the active layer-mineral interface is defined

by c = 1. The crystalline-amorphous boundaries for samples19-S (green) and 19-R

(pink) are indicated by vertical bars. For both 19-S and 19-R, D* was calculated using

DMg = 1E-14 cm2/s. The two fits differ in the values of a (velocity of the reaction

front), which were calculated using steady-state Mg release rates to be 1.5E-10 cm/s

(19-R) and 2.7E-11 cm/s (19-S), because the dissolution rate of sample 19-S was

significantly slower than that of sample 19-R. In order to fit the EDS data, different

values of DH were also used for the two data sets (9E-17 cm2/s for 19-R and 5E-18

cm2/s for 19-S). In summary, two Mg concentration gradients in the Si-rich,

amorphous surface layer of altered olivine can be successfully fit using steady-state

diffusion alone, assuming that the diffusivity of the highly altered regions is 2-4 orders

of magnitude greater than that of the minimally altered regions. Even very sharp, step-

90

like gradients can be fit using this approach.

In order to fit our data, the model requires DH to be about an order of

magnitude lower for sample 19-S than for sample 19-R. The implication is that

protons in the stationary experiment diffuse more slowly inside the altered layer than

in the rocking experiment. We are not able to measure concentration gradients in the

fluid at the mineral-fluid interface, and as a result, the diffusion coefficients we use to

fit our data are effective diffusion coefficients that incorporate the effect of any

concentration gradients in the fluid. Thus, slower proton diffusion in the stationary

experiment could be an effect of a lack of protons at the fluid-mineral interface, which

would result in a smaller concentration gradient in the altered layer. Effectively, slow

transport of protons from the bulk solution to the mineral could, in theory, result in

slower proton transport inside the altered layer and thus a smaller effective diffusion

coefficient. In the well-mixed experiments, convective transport could increase the

concentration of protons at the mineral surface, and consequently create a strong

chemical potential for diffusion into the altered layer.

3.5 Conclusions

Dissolution of olivine in a batch reactor under conditions relevant for

subsurface carbon storage results in fluid and mineral phases that were carefully

examined in order to improve our understanding of the mechanism(s) and rate-limiting

steps of the dissolution reaction. Analysis of the fluid phase revealed that amorphous

silica saturation was reached between 1 and 3 days in the well-mixed, rocking

experiment and 7 and 14 days in the unmixed, stationary experiment. By 19 days,

olivine from both experiments (mixed and unmixed) appeared to be dissolving at

steady state because the Mg release rates were constant with time between 3 and 19

days. Mineral phase analysis of thin cross sections prepared with a FIB and analyzed

by TEM yielded information about the chemical composition as a function of depth in

the mineral surface as well as the location of amorphous and crystalline regions.

Combination of the fluid and mineral phase data creates a more complete picture of

the processes that occur during olivine dissolution.

As expected, olivine dissolution proceeds faster in a well-mixed reactor than in

91

an unmixed one, and in an unmixed situation, the reaction appears to be transport

limited. Thus, in a subsurface storage project, one might expect silicate dissolution

rates to be significantly slower than the surface-controlled reaction rates measured in

laboratories. However, the thickness of the Si-rich layer does not allow prediction of

the dissolution rate. In fact, the experiment with the highest measured dissolution rate

(19-R) also had the thickest Si-rich layer (65 nm). However, we observed the

formation of a Si-rich layer after as little as 2 days of reaction, before SiO2 saturation

was reached in the bulk aqueous phase. The formation of this layer coincides with the

previously observed two order of magnitude decrease in olivine dissolution rates over

the first several days of reaction (Chapter 2; Daval et al., 2011; Pokrovsky and Schott,

2000b).

We observed several different types of Si-rich surface layers with different

characteristics. The “precipitated” layer exists at the mineral-fluid interface on olivine

from the 19-day experiments, was amorphous, and contained little to no Mg and Fe.

The precipitated layer may form via SiO2 precipitation from the bulk solution and

contains pores visible in TEM images. Further evidence for the

dissolution/reprecipitation mechanism will be presented in part 3 of this series

(Chapter 4). The precipitated layer was not present on olivine reacted for 2 days.

Beneath the precipitated layer (19 day experiments) or in the case of the 2-day

experiments, we observed a second type of Si-rich layer at the mineral-fluid interface,

also amorphous but with increasing Mg/Si ratios with depth. We call this layer the

“active” layer and suggest that it forms via a leaching mechanism in which Mg-O

bonds are broken and Mg2+

ions diffuses to the surface. Finally, the Mg-depleted

olivine is below the active layer and observed on olivine from three of the four

experiments (2-S, 2-R, and 19-R). This region is crystalline but depleted in Mg

relative to Si, suggesting that it is a hydrous olivine.

Our data indicate that the active layer forms in the first hours to days of

reaction time and the precipitated layer forms later after the bulk solution reaches

saturation with respect to amorphous silica. The correlation between active layer

formation and dissolution rate decrease in the first hours to days of reaction suggests

92

that the active layer may partially passivate the olivine surface. On the other hand,

olivine dissolution rates do not decrease with increasing precipitated layer thicknesses,

implying that the precipitated layer does not further passivate the surface.

Finally, we used a simple diffusion model (Lasaga, 1979; Hellmann et al.,

2012) to fit the Mg/Si ratios as functions of depth in the altered surface layers for two

experiments (19-S and 19-R). The model was originally developed for interdiffusion

of protons and cations in an amorphous matrix and assumes steady-state dissolution

(Doremus, 1975). We fit a curve to our data using reasonable diffusivity coefficients

and showed that many different gradients could be generated, including near step-

functions, depending on the values assumed for the diffusion coefficients. Recent

studies (e.g., Hellmann et al., 2012) have used the presence of step-like changes in

concentration to support the dissolution/reprecipitation mechanism of Si-rich layer

formation, but this justification may not be correct. While our evidence does support

silica precipitation during silicate mineral dissolution at t>2 days, our data and fit

using the simple diffusion model suggests that in the case of olivine, solid-state

diffusion through an active layer of up to 25 nm facilitates the creation and ongoing

presence of a Si-rich leached layer.

The combination of TEM/EDS and ICP data presented in this study allows us

to hypothesize about Si-rich surface layer formation mechanisms, but it does not

directly probe the mechanisms themselves. Additional work focusing on the uptake of

an isotopic Si spike from solution into the surface layer is underway (Chapter 4) and

will further illuminate the processes controlling olivine dissolution. Also important is

the need to broaden the scope of this study by applying the data and conclusions to

build a model that will allow for the prediction of olivine dissolution rates under a

range of conditions and over longer timescales than are practical to investigate in the

laboratory.

93

3.6 Acknowledgments

We acknowledge the Global Climate and Energy Project (GCEP-48942) at

Stanford University for funding the work presented here. We also would like to

acknowledge the staff of the Stanford Nanocharacterization Laboratory, where the FIB

and TEM analyses were performed, particularly Richard Chin for technical assistance.

94

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99

Chapter 4: The role of the Si-rich surface layer in olivine

dissolution 3: Spatially and temporally resolved incorporation of an isotopic tracer (29Si)

Natalie C. Johnsona,*, Burt Thomasb, Robert J. Rosenbauerb, Dennis K. Birdc, Gordon E. Brown, Jr.a,c,d,

Christopher E.D. Chidseye, Kate Maherc

a. Department of Chemical Engineering, Stauffer III, 381 North-South Mall, Stanford University, Stanford CA 94305, USA

b. U.S. Geological Survey, 345 Middlefield Rd, Menlo Park CA 94025, USA

c. Department of Geological and Environmental Sciences, 450 Serra Mall, Braun Hall Building 320,


d. Department of Photon Science and Stanford Synchrotron Radiation Lightsource,

SLAC National Accelerator Laboratory, Menlo Park CA 94025, USA

e. Department of Chemistry, Stauffer II, North-South Mall,


In preparation for submission to Geochimica et Cosmochimica Acta.

100

Abstract

The kinetics and mechanisms of forsterite dissolution are of interest because of

the potential for large-scale subsurface carbon dioxide (CO2) storage via mineral

carbonation. However, an amorphous, Si-rich surface layer forms on the forsterite

surface during reaction with water and supercritical CO2 and the characteristics of this

layer, including its potential for passivation of the mineral surface, are not fully

understood. Forsterite was reacted with solutions containing an isotopic tracer, 29

Si,

and pCO2 (100 bar) at 60 °C for 2 days and 19 days in both well-mixed and unmixed

reactors. The isotopic composition of both solid and aqueous phases were then

analyzed for to resolve incorporation of the tracer both spatially and temporally. A

precipitated surface layer (characterized by incorporation of the 29

Si tracer) exists on

forsterite reacted for 19 days (20% enrichment compared to unreacted forsterite) but is

less evident at 2 days (3% enrichment), suggesting that the precipitated surface layer

forms more rapidly after the bulk fluid reaches amorphous silica saturation. Steady-

state forsterite dissolution and amorphous silica precipitation rates were calculated

from the rate of tracer dilution to be 1.1±0.6×10-13

mol cm-2

s-1

for the mixed

experiment. The unmixed experiment reached steady-state shortly before its

conclusion because of an extended initial transient stage of reaction, the steady-state

dissolution rate was calculated to be 2.5±0.9×10-14

mol cm-2

s-1

. Data from the

experiments were used to further evaluate a surface kinetic model that includes the Si

isotopic tracer. Based on these findings, a complexing agent (Tiron) was added to a

mixed experiment to facilitate transfer of Si from the mineral surface to the bulk fluid.

The presence of a complexing agent for Si doubled the rate of steady-state dissolution

relative to the control experiment.

101

4.1. Introduction

Mineral carbonation, which describes the chemical reaction between silicate

minerals and carbon dioxide (CO2) to make carbonate minerals, is a promising

strategy for subsurface carbon storage. The main advantage of mineral carbonation (or

mineral trapping) over other storage mechanisms is its stability over thousands to

millions of years. Mineral carbonation is thermodynamically favored and occurs in

natural systems (Boschi et al., 2009; Mervine et al., 2014), motivating the study of

reaction kinetics with the ultimate goal of engineering subsurface storage within rocks

rich in reactive minerals.

Over the past two decades, there have been many studies on the dissolution

and carbonation rates of forsterite ((Mg,Fe)2SiO4), a reactive silicate mineral found in

mafic and ultramafic rocks. Flow-through experiments have shown the rate of

dissolution to increase with increasing temperature and decreasing pH (Rimstidt et al.,

2012), while studies using batch reactors report a weak dependence on pH and strong

dependence on H4SiO4 (Chapter 2; Daval et al., 2011; Wang and Giammar, 2013).

During dissolution under a range of conditions, a Si-rich, amorphous layer forms on

forsterite surfaces that may passivate the surface (Andreani et al., 2009; Daval et al.,

2011; King et al., 2010). However, the mechanism of layer formation is not fully

understood: some studies have observed preferential removal of Mg resulting in a

“leached layer”, (Bearat et al., 2006; Daval et al., 2011; E. H. Oelkers, 2001;

Pokrovsky and Schott, 2000a, 2000b), while others have observed sharp interfaces

between the surface layer and mineral (Hellmann et al., 2012), evidence of

psuedomorphic replacement, and uptake of an oxygen isotope tracer (King et al.,

2011), all of which are indicative of a dissolution/reprecipitation process. Others have

proposed that the Si-rich surface layer may form via both mechanisms (Saldi et al.,

2013).

In general, the dynamics of Si removal from dissolving olivine are poorly

understood, in part because the aqueous phase reaches saturation with respect to a

secondary phase (amorphous silica) and thus the Si(aq) reaches a steady-state

concentration and cannot be used to determine the dissolution rate. However, Si

102

removal is known to influence the overall rate (Pokrovsky and Schott, 2000a, 2000b)

and thus the study of Si surface dynamics is relevant and important. Most attempts to

accelerate forsterite (and other silicate minerals) dissolution have focused on changing

the pH or complexing cations with organic acids (Blake and Walter, 1999a; Krevor

and Lackner, 2009; Manning et al., 1992; Oelkers, 2001; Olsen and Rimstidt, 2008;

Prigiobbe and Mazzotti, 2011). In this study, we use an isotopic tracer to improve our

understanding of the role of Si dynamics in forsterite dissolution, and then attempt to

accelerate the kinetics by introducing a Si-complexing agent (catechol).

The isotopic tracer (29

Si) allows this study to constrain both primary mineral

dissolution/secondary mineral precipitation rates using the "isotope ratio method"

from Gruber et al. (2013) and to probe the formation of the Si-rich surface layer.

Analysis of the Si isotopic composition of both the aqueous Si and the surface layer of

the mineral phases allows for precise and accurate tracing of the partitioning of the

29Si spike. For example, a dissolution/reprecipitation process would incorporate

29Si

from the bulk solution, while a leaching process would not, so one would expect a

precipitated Si-rich layer to be at or near isotopic equilibrium with the aqueous phase.

The incorporation of an isotopic spike uniquely allows for the calculation of secondary

phase (SiO2(am)) precipitation rates. The isotopic and modeling approaches presented

here build on observations from a series of previously published experiments, along

with new experiments conducted to evaluate the ability of Si complexing agents to

accelerate forsterite dissolution rates under batch conditions.

Part 1 of this series used high resolution transmission electron microscopy

(HR-TEM) to image and analyze the Si-rich surface layer on reacted forsterite

(Chapter 3). Several distinct types of Si-rich layers were observed: an amorphous, Si-

rich layer with varying Mg/Si (Mg/Si=0.2-1.5) as a function of depth. This first layer

formed within 2 days of reaction, before the bulk solution reached SiO2 saturation, and

is 20-25 nm deep. The second layer to form is porous, amorphous, and very Si-rich

(Mg/Si<0.3) and formed only after the bulk solution reached saturation with respect to

amorphous silica. The third layer was crystalline, but also depleted in Mg. Chapter

three hypothesizes that the first layer formed by preferential Mg removal, or leaching,

103

and the second layer was the result of SiO2(am) precipitation. However, direct

evidence for either mechanism could not be inferred from solely the HR-TEM

analysis.

Part 2 of this study developed a "surface kinetic" model to describe the

dissolution kinetics and spatial relationships between Mg and Si observed in part 1 and

in previous work (Appendix 1). Using parameters from TEM images, we successfully

modeled the temporal evolution of solution composition by operationally defining a 25

nm "active" surface layer that forms via preferential Mg release. Newly precipitated

SiO2(am) is accounted for in the model, but is assumed to play no role in passivating

the surface. The model results suggest that under conditions of high H4SiO4 and

mildly acidic to neutral pH, the rate is controlled by both SiO2 removal from the active

layer-precipitated layer interface and the exchange of Mg for protons within the active

layer. Thus, the model provides further support for the importance of both a leached

(active) layer and a non-passivating precipitated layer, but again, offers no direct

experimental evidence. Here we provide experimental evidence of the conceptual

models developed in parts 1 and 2 of this series.

4.2. Methods

4.2.1 Isotopic tracer preparation

The 29

Si spike was prepared gravimetrically from ISOFleX 99.8% 29

Si in the

oxide form. The 29

SiO2 was dissolved in 2M NaOH, using sonication to increase the

dissolution kinetics, then neutralized with HCl. The tracer solution was then diluted to

a concentration of 1.90 mM 29

Si and 0.64 M NaCl. The tracer was further diluted

before reaction with forsterite using deionized (DI) water, and sufficient NaCl was

added to achieve a concentration of 0.5 M NaCl and 0.29-0.35 M 29

Si .

4.2.2 Experimental apparatus and sampling procedures

Experiments were performed in Dickson-style "rocker bombs" described in

detail in Rosenbauer et al. (1983) that were modified for CO2 analysis following

Rosenbauer et al. (2005). The specific experimental conditions and sampling

104

procedures are described in full in Chapters 2 and 3. Briefly, the experiments were

performed in flexible, Au reaction cells equipped with a Ti-lined sampling tube and

valve for extraction of liquid and gas samples. The reaction cell was placed inside a

stainless steel autoclave and the annular space filled with DI water to function as a

pressure fluid and sustain a pressure of 100 bar. A temperature of 60 °C was

maintained by placement of the steel vessel inside a rocking furnace (Rosenbauer et

al., 1983). The apparatus allows for serial sampling without changing the pressure or

temperature conditions.

Aqueous samples were withdrawn periodically and analyzed for elemental

concentration, alkalinity, dissolved CO2 (see Chapter 2 for details), and Si isotopic

composition (see section 2.4). The total volume of fluid removed during sampling was

10% or less of the starting volume in order to minimize the effect of changing

water:solution ratios throughout each experiment. At the conclusion of each

experiment, the stainless steel autoclave was removed from the furnace, vented, and

disassembled as quickly as possible (<30 minutes) to minimize precipitation from

quenching. The solids were filtered from the reaction solution and rinsed well, then

dried at 40 °C for several hours. Reacted mineral phases were analyzed with imaging

techniques (SEM, TEM) (Chapter 3) and for isotopic composition (see section 4.2.3).

This study includes five experiments, a suite of four experiments designed to

understand the effects of time and mixing on the Si-rich surface layer, and a fifth to

explore the idea of increasing dissolution rate by adding a complexing agent. All five

experiments contained 0.5 M NaCl and were performed at 60 °C and 100 bar. Two

experiments lasted 2 days (2-R, 2-S) and two lasted 19 days (19-R, 19-S). One

experiment of each duration was rocked inside the furnaces to ensure that the reacting

components were well mixed (2-R, 19-R), and one of each duration was not rocked to

investigate potential transport limitations (2-S, 19-S). All four of these experiments

contained a 29

Si tracer in the initial aqueous solution. These four experiments are

discussed in detail in Chapter 3 and are also presented in Table 4.1.

105

Table 4.1: Duration, degree of mixing, and additive concentrations for five experiments.

Experiment name Duration Mixing Additive

2-S 2 days No 0.35 mM 29

Si

2-R 2 days Yes 0.29 mM 29

Si

19-S 19 days No 0.35 mM 29

Si

19-R 19 days Yes 0.29 mM 29

Si

Catechol 35 days Yes 100 mM Tiron

The fifth experiment contained 100 mM of Tiron (4,5-Dihydroxy-1,3-

benzenedisulfonic acid disodium monohydrate, (OH)2C6H2(SO3Na)2·H2O). Tiron is a

sulfonated catechol with a first pKa of 7.2, and is used primarily as a colorimetric

reagent for iron, manganese, titanium, and molybdenum. Tiron has been shown to

complex with silicic acid in the neutral to elevated pH range (Bai et al., 2008). The

complex is not stable below pH of 6 (Bai et al., 2011). Thus, Tiron could potentially

form a complex with Si near the mineral surface (where the pH is high), but return to

the acid state in regions where the pH is lower (due to carbonic acid dissociation)

acting as a shuttle for Si from the mineral surface to the bulk solution.

4.2.3 Isotopic analysis of the aqueous phase

Aqueous samples were prepared for isotopic analysis using ion

chromatography designed to remove dissolved sodium, magnesium, and iron,

Table 4.2: Resin cleaning and Si purification procedure adapted from Georg et al. (2006).

Separation Stage Solution Matrix Volume (mL)

Pre cleaning 2.5 N HCl 3

4.0 N HCl 3

MQ water 1

7.0 N HCl 3

MQ water 1

4.0 N HCl 3

2.5 N HCl 3

Conditioning MQ water 6

MQ water 3

MQ water 3

Sample Load and Collect Sample 2

Collection MQ water 2

MQ water 2 mL

106

following methods established by Georg et al. (2006). Sufficient sample to contain 5

g Si was dried overnight at 100˚C, then placed in water to a total fluid volume of 2

mL. Columns were loaded with 40 g of BioRad AG 50W-X2 (200-400 mesh) resin for

a volume of 1.8-2.0 mL. The columns were prepared by a number of pre-cleaning

steps based on Georg et al. (2006) (Table 4.2), then the sample was loaded onto the

column and Si collected.

Isotopic analyses were performed on a Nu Plasma HR Multi-collector ICP-MS

where the 28

Si, 29

Si, and 30

Si were measured simultaneously in Faraday cups with 15

cycles per sample. Samples were run in duplicate or triplicate and numbers presented

are averages of all data obtained per sample (i.e. they represent 30-45 cycles of data

collection). Before each sample measurement, a baseline measurement was taken

using double distilled water, and then a standard was measured (IRMM 3.8 ppm

solution, 29

Si/30

Si=1.44). Ratios obtained from the MC-ICP-MS were corrected for

mass bias using the 28

Si/30

Si ratio from the standard run immediately before each

sample; the reproducibility of the 29/30 ratio of the standard was very high with 2σ =

0.1% over two days of measurement.

4.2.4 Isotopic analysis of the mineral phase

Mineral surfaces were analyzed for elemental concentration using the

Stanford/USGS Sensitive High Resolution Ion Microprobe-Reverse Geometry

(SHRIMP-RG) built by Australian Scientific Instruments. Fresh and reacted forsterite

grains for SHRIMP analysis were prepared by drilling several small holes in 25.4 mm

epoxy discs, which were then filled with indium metal. The disks and metal were

polished to ensure an even height of 4 mm. Reacted forsterite grains were then pushed

into the indium metal to preserve the surface layers. The mount was coated with gold

using a plasma deposition for 50 seconds and then placed in a vacuum oven for at least

12 hours to dry. Before analysis, each mount was photographed with an optical

microscope camera to aid in sample navigation.

The SHRIMP-RG directs a beam of oxygen anions onto the mineral surfaces.

Reverse geometry (RG) refers to the placement of the magnet prior to the electrostatic

analyzer (ESA), resulting in much higher mass resolution, but also the inability to

107

collect data for several masses at once. In order to minimize the effect of time-

averaging the ratios and also to maximize the number of measurements at the surface

and near surface of the mineral, we used a very low amperage primary beam (0.1-0.3

nA), consisting of O2-

focused through a 50 nm Köhler aperture with a brightness of 6

and a spot size of approximately 10 microns. Using transmission electron microscopy

images and energy dispersive spectroscopy linescans for calibration (Chapter 3), we

determined the rate of sputtering to be 3-9 nm/minute. We collected data for 26

Mg,

29Si , and

30Si by peak hopping, with the entire sampling cycle taking about 20 seconds

due to peak centering and the time allowed for the magnet to settle in between masses.

Thus, the ratios that we present are actually time-averaged ratios over about 20

seconds of collection time. Also, the beam is incident on the sample at a 45° angle,

resulting in slightly uneven milling and sampling of the pit walls; both of which have

an effect similar to depth averaging. Elemental ratio calibration was performed using

unreacted forsterite grains and standard glass, NIST 611.

4. 2.5 Calculation of Dissolution and Precipitation Rates

Dissolution rates were calculated for experiments 19-S and 19-R using two

different methods: (1) a conventional method based on the differences between Mg

concentrations at different sample times (e.g. Chapter 2), and (2) the "isotope ratio

method" from Gruber et al. (2013), which is based on the changes in Si isotopic ratios

with time. Using the conventional method, a dissolution rate, Rd, was calculated

according to Equation 1:

(1)

where the difference between Mg concentrations is divided by the associated

difference in time between the samples, and this term is multiplied by the inverse of

the stoichiometric number (XMg,d=1.84) and the mineral surface area (Ad). For all

experiments, the dissolving surface area is assumed to be constant throughout the

experiment at the measured BET surface area of 5735 cm2/g.

The isotope ratio method was developed by Gruber et al. (2013) specifically to

measure dissolution and precipitation rates of minerals under conditions near

dt

dMg

AXR

ddMg

d

,

1

108

equillibrium. The method requires an isotopically enriched initial solution and the

measurement of both the total concentration of dissolved species and the isotopic ratio

of the solution as a function of time. In our case, we are measuring the rate of Si

release from forsterite and Si uptake by amorphous silica when the system is near

equilibrium with the secondary phase, SiO2(am). The calculations are based on mass

balances for total Si, 29

Si, and 30

Si, where the rate of change of each species is equal to

the dissolution rate minus the precipitation rate. Gruber et al. (2013) show the

derivation in detail; the final result for the dissolution rate is Equation 2:

Fo

Si

Fo

SidSi

d

XXSi

SiA

dt

Sid

dt

Sid

Si

Si

R

293030

29

2930

30

29

(2)

Equation 2 also contains the mol fractions of 30

Si (X30SiFo

= 0.031) and 29

Si (X29SiFo

=

0.047) found in the forsterite. The isotopic ratios were measured for each sample, but

the rates of change of 29

Si and 30

Si are averaged over two samples by necessity, so for

the purpose of this calculation, the isotopic ratios were also averaged over two

samples and thus assumed to be linear with time between each measurement.

The isotope ratio method accounts for both dissolved Si addition and removal

rates as components of the material balance, so once the dissolution rate is calculated,

the precipitation rate can be calculated from Equation 3.

(3)

Equation 3 relates the net change in Si concentrations and dissolution rate, Rd, with the

precipitation rate, Rp (Gruber et al., 2013). This equation includes two stoichiometric

values and surface areas, one each for the dissolving phase and the precipitating phase.

In this case, the stoichiometric value is 1 for both phases (forsterite and SiO2(am)),

and we assume that the surface area available for precipitation, Ap, is the same as the

surface area available for dissolution, Ad. For comparison, we calculated a second

precipitation rate with a different set of assumptions; namely, that Si and Mg are

released congruently, and that any missing Si in solution is due to SiO2(am)

precipitation (Equation 4).

pppSidddSi RAXRAXdt

dSi,,

109

(4)

This equation represents a material balance in which the sum of the precipitation rate

and the observed net change in Si with time is equal to the expected change of Si with

time, or the forsterite dissolution rate as calculated using changes in [Mg]. We note

that the precipitation rates we calculate from Equations 3 and 4 are effectively net

removal rates that include both the new SiO2(am) precipitation rate and any net

exchange of Si(aq) into the reacted surface or Si-rich layer, where the later is

supported by the presence of 29

Si in Si-rich surface layer after 2 days of reaction. We

cannot explicitly separate the exchange rate from the secondary phase precipitation

rate, but we can use a comparison of precipitation rates calculated from different

equations to implicitly calculate each rate.

4.3. Results

4.3.1 Time-resolved solution compositions

As forsterite dissolves and releases Si into solution, the concentration of total

dissolved Si increases and the ratio of 29

Si/30

Si decreases, approaching the natural ratio

of 1.51 (Fig. 4.1A-B). In both 19-day experiments (19-R and 19-S), the solution

reaches and then exceeds saturation with respect to amorphous silica. Saturation was

reached at day 1 in experiment 19-R (Fig. 4.1A) and between 6 and 14 days in

experiment 19-S (Fig. 4.1B). Because of the lack of mixing in experiment 19-S,

forsterite dissolved more slowly than in experiment 19-R and thus a longer time was

required to reach saturation (Chapter 3). Both experiments also show dilution of the

initial 29

Si spike with time (Fig. 4.1A-B). The initial dissolved Si was 99.8% 29

Si , but

Si from the dissolving forsterite was 4.7% 29

Si , 3.1% 30

Si, and 92.2% 28

Si. Thus, the

ratio of 29

Si/30

Si decreased as more Si was released from forsterite. The rate of dilution

is greater in experiment 19-R, again because forsterite dissolution rate was greater in

this experiment.

The Mg/Si ratio was elevated in the aqueous phase for experiments 19-R and

19-S for the entirety of both experiments (i.e. the aqueous phase is enriched in Mg

pppSi

dMg

RAXdt

dSi

dt

dMg

X,

,

1

110

relative to the mineral phase) (Fig. 4.1C). In experiment 19-R, Mg/Si = 4 after 1 hour

of reaction and the ratio drops towards the stoichiometric ratio of 1.84 over the next

several days, then rapidly increases for the remainder of the experiment. In experiment

19-S, Mg/Si decreases monotonically during the experiment but remains above 1.84.

Figure 4.1: Silicon concentrations and 29Si/30Si ratios as a function of time for 19-R

(A) and 19-S (B), with amorphous silica saturation plotted for comparison. Ratios of

Mg/Si vs . time (C) show that the fluid composition is elevated in Mg relative to the

mineral phase.

111

4.3.2 Si ratios on mineral surfaces

The Mg/Si ratios (Fig. 4.2A-B) and 29

Si/30

Si ratios (Fig. 4.2C-D) were

measured on mineral surfaces as a function of time using the ion microprobe

(SHRIMP) and converted to a function of depth using transmission electron

microscope images and energy dispersive spectroscopy linescans to calibrate the rate

of ion milling. Mineral surfaces from all four experiments had lower Mg/Si ratios than

expected based on mineral stoichiometry (Mg/Si = 1.84), which is indicative of a Si-

rich surface layer. The amount of depletion varied by experiment; the level of

depletion increased from experiments 2-S and 2-R to experiments 19-S to 19-R and

correlates with reaction extent (i.e. experiments with greater reaction extents resulted

in mineral surfaces with greater Mg-depletion). The surface of forsterite grains from

all four experiments also showed enrichment in 29

Si, although the degree of

enrichment differed. The 19-day experiments (19-R, 19-S) had more surface 29

Si

compared to the 2-day experiments.

The depths of Mg depletion and 29

Si incorporation differ. For the forsterite

from experiment 19-R, the measured Mg/Si ratio reaches the ratio of bulk crystalline

forsterite (1.84) at about 60 nm depth, but the measured 29

Si /30

Si ratio reaches the

bulk ratio (1.51) at 45 nm deep. The same pattern is visible in experiment 19-S (Fig.

4.2B,D); the Mg/Si ratio reaches the bulk forsterite level at 45 nm and the 29

Si /30

Si

ratio reaches the bulk ratio at 30 nm deep.

4.3.3 Comparison of 29

Si/30

Si ratios in the mineral and aqueous phases

Comparison of the 29

Si/30

Si ratios in the solid surface and aqueous phases from

the last sample (i.e. sample taken at 2 days or 19 days) for four experiments is shown

in Fig. 4.3. The ratio at the solid surface was calculated by averaging the first

SHRIMP-RG data point over 3 to 5 mineral grains, and the error bars represent one

standard deviation. The first measurement taken represents the solid-aqueous

interface, though depth averaging does result in this value being averaged over 3 nm

of layer thickness. Reaction extent increases from left to right and corresponds with

dilution of the initial isotopic spike. Experiment 2-S had the lowest extent of reaction

112

and also has the highest 29

Si/30

Si ratio in the aqueous phase, whereas experiment 19-R

had the highest extent of reaction and the lowest 29

Si/30

Si ratio in the aqueous phase.

The explanation for this trend is the same as discussed above; as the reaction

progresses and Si is released from forsterite at 29

Si/30

Si = 1.51, the aqueous 29

Si/30

Si

decreases and approaches 1.51.

4.3.4 Reaction in the presence of a complexing agent

The addition of a complexing agent (Tiron, a catechol derivative) does increase

the rate of reaction, especially during the first 7 days of reaction (Fig. 4.4A,B). After 7

Figure 4.2: Ratios of Mg/Si as a function of depth for 2,19-R (A) and 2,19-S(B). The

depth was calibrated using the SI-rich layer thickness as measured from TEM images

(65 nm (19-R), 40 nm (19-S), 25 nm (2-S), and 20 nm (2-R)). Isotopic ratios

(29Si/30Si) are also plotted as a function of depth for the rocking (C) and stationary (D)

experiments. Each data point is an average from at least three different forsterite grains.

113

days, three times as much Mg was released by the experiment with catechol than by

the control experiments (19-R and Experiment 1, no complexing agents) (Fig. 4.4A).

Silicon release was also initially elevated in the presence of catechol. Particularly

striking is a sharp increase in Si concentrations from 0 to 2 days followed by a steep

drop to a steady-state concentration at 2 days (Fig. 4.4B). Data from the other

experiments do not exhibit this feature. Over longer times (t > 7 days), the change in

Mg concentrations with time (slope of the data in Fig. 4.4A) is approximately equal to

the rate of change in the control experiments. During that same period, the Si

concentration was constant in the catechol experiment and slightly elevated relative to

Experiment 1, though consistent with experiment 19-R (Fig. 4.4B). The lower Si

concentrations in Experiment 1 are likely due to an imperfect sampling procedure, in

which SiO2 precipitated in the sampling tube and was inadvertently filtered out before

ICP analysis (Chapter 2). Thus, the complexing agent appears to increase the initial

rates of both Mg and Si release, but does not significantly affect the long-term kinetics

or activity of Si in solution.

Figure 4.3: Comparison of isotopic composition of the aqueous and mineral phases for four

experiments.

114

4.4. Discussion

4.4.1 Conceptual Model of Surface Layers on Olivine

A conceptual model for forsterite dissolution was outlined in the first two parts

of this series (Chapter 3, Appendix 1) and is described briefly here. When forsterite is

exposed to water, Mg sites are protonated, which reduces the strength of the Mg-O

bond. As a result, Mg is removed from the forsterite surface and leaves behind a

network of silica tetrahedra and a region depleted in Mg. This process forms the

"active" surface layer and generates a reservoir of surface SiO2 sites, henceforth

referred to as >SiO2. The removal of Mg from the surface is considered irreversible

during dissolution, but H4SiO4 and >SiO2 are expected to exchange. The net rate of

Figure 4.4: Time-resolved Mg (A) and Si (B) concentrations for three experiments: 19-R (this

study), Experiment 1 (Chapter 2), and catechol (this study).

115

active layer dissolution is determined by the difference between the forward reaction

rate, or the removal of >SiO2 from the active layer/aqueous interface, the backward

reaction rate, or the attachment of H4SiO4 to the active layer interface. Aqueous SiO2

is also controlled by precipitation of a secondary phase, amorphous silica, which

precipitates on reactor and mineral grains, but does not appear to passivate the surface.

The sum of net dissolution and precipitation describes the measured changes in

H4SiO4.

Based on HR-TEM data, the active layer forms within two days of the reaction

and remains at a roughly constant thickness of 20-25 nm out to 19 days (Chapter 3).

Thus, this layer appears to control the dissolution rate. The net rate of Si removal from

the active layer/aqueous interface controls the rate at which the active layer advances

into the mineral, while the rate of Mg removal controls the rate at which the active

layer forms. The experimental data used to develop this conceptual model were

collected under one set of conditions, but understanding the kinetics would allow for

prediction of rates under a range of conditions: SiO2(am) solubility, pH, and ionic

strength. In fact, the active layer may not be Si-rich under certain conditions (e.g., high

pH). In Appendix 1, we were not able to constrain the Si dynamics beyond suggesting

the potential importance of the rate of net Si removal from the active layer as a control

on the Mg supply to the active layer and net dissolution. The addition of an isotopic

tracer allows us to uniquely quantify the H4SiO4/>SiO2 exchange rates. Constraining

these rates improves our understanding of Si dynamics on the surface of dissolving

forsterite.

The rest of the discussion is organized as follows. First, we evaluate the rates

of forsterite dissolution from experimental data using elemental and isotopic material

balances. We then analyze the temporal evolution of surface layers on the dissolving

forsterite surface in terms of experimental evidence and a surface kinetic model. The

model includes provision for the isotopic tracer in addition to constraints from solution

data and nm-scale analysis of reacted forsterite. Finally, we discuss the implications of

our findings for the observed early rate increase in the presence of catechol.

116

4.4.2 Dissolution and Precipitation Rates

Two methods were used to calculate the forsterite dissolution and

SiO2(am) precipitation rates: a conventional method based on an elemental mass

balance and the "isotope ratio method" which uses the elemental concentrations as

well as the isotopic composition of the aqueous phase (Gruber et al., 2013.). A

comparison between two methods for calculating the rates from experiments 19-R and

19-S as a function of time is shown in Fig. 4.5A-B using Equations 1-4. The first rate

(point "a") represents the transient initial stage of reaction, which is characterized by

preferential release of Mg over Si (Fig. 4.5A) resulting in an erroneously high

precipitation rate (Fig. 4.5B, point "a"). The dissolution rate calculated using dMg/dt

is four times greater than the rate calculated from the isotope ratio method. This initial

difference in release rates of Mg and Si could be due to incongruent dissolution (e.g.,

Chapter 2) and/or exchange of aqueous Si with Si in the surface layer. The

precipitation rate calculated from the isotope ratio method is zero (not shown),

indicating that only release of Si into solution is occurring during that timeframe (Fig.

4.5B). The precipitation rate calculated from Equation 4 (a material balance of

expected Si release based on the measured Mg release) does indicate precipitation

during this first time interval; however, the calculation assumes stoichiometric

dissolution, which the isotope ratio analysis has shown to be invalid for the first time

point. Thus, the combination of a calculated dissolution and precipitation rate from the

isotope ratio method for this first time point provides strong evidence for incongruent

dissolution, or preferential Mg release (i.e. leaching), during the first hour of reaction

(point "a" in Fig. 4.5 A-B).

In order to satisfy the isotopic mass balance in experiment 19-R, removal of Si

from the fluid phase must begin between 1 hour and 1 day after reaction (indicated by

non-zero precipitation rates calculated from the isotope ratio method at point "b" a,

Fig. 4.5B). However, the precipitation rate calculated from dMg/dt is zero during that

time because dissolution is stoichiometric (Fig. 4.5A, point "b"). Combining these

observations leads us to hypothesize that SiO2(am) is not precipitating between 1 hour

and 2 days of reaction, but rather the "precipitation rate" during this time actually

117

represents the exchange rate between the aqueous phase and surface layer. In other

words, the net precipitation of SiO2(am) is zero, but isotopic exchange proceeds at a

measurable rate. Amorphous silica precipitation begins to contribute to the removal of

H4SiO4 at the 3rd data point, which represents the time between 1 and 3 days of

reaction (point "c"). The bulk aqueous phase reaches SiO2(am) saturation at 1 day,

suggesting that SiO2(am) precipitation does not begin until after the system achieves

saturation.

Between 3 and 19 days, dissolution rates calculated with both methods are

constant and consistent within uncertainty (Fig. 4.5A). The Si removal rate from

Figure 4.5: Dissolution rates for 19-R calculated using the isotope ratio method and dMg/dt indicates

that Mg and Si release are stoichiometric at t>5 days (A), and Si removal rates (precipitation plus

exchange) are the same within uncertainty as dissolution rates at t> 5 days (B). The same

calculations for 19-S reveal slower dissolution and a longer transient stage (C) and precipitation

begins later (D). Missing data are either less than zero or have uncertainties that span positive and

negative rates (i.e. rates are zero within uncertainty).

118

solution (precipitation + backwards exchange) increases during that time (Fig. 4.5B),

possibly due to increasing surface area available for precipitation. The similarity of the

two rates indicates that forsterite dissolution and H4SiO4 removal (via amorphous

silica precipitation and exchange with the mineral surface) occur at the same rate

during the steady-state regime. Also, the rate of Si removal from the surface is roughly

twice the rate of Si attachment to mineral from the fluid phase. Rates of dissolution,

precipitation, and Si exchange are presented in Table 4.3 along with results from the

model (see section 4.4).

Performing the same calculations for dissolution rate for experiment 19-S

yields results similar to those from experiment 19-R, though the rates are slower (Fig.

4.5C). The initial, transient stage in which dissolution is incongruent lasts for 2 days

instead of 1 hour (the first 2 rates from 19-S show preferential Mg release), and the

steady-state rate is nearly 5 times slower than for experiment 19-R. Data from

experiment 19-S highlight the utility of the isotope ratio method for dissolution rate

calculations when the rate is very slow (Gruber et al., 2013). Magnesium

concentrations are nearly constant with time for parts of the experiment, so calculating

the rate of change for each sampling interval results in rates with large uncertainties

that span zero. However, the rate can easily be calculated using the rate of 29

Si dilution

to give consistent rates and small uncertainties (Table 4.3).

Precipitation rates for experiment 19-S were calculated using Equations 3 and

4 (Fig. 4.5D). In this case, the first two rates represent the transient, incongruent stage

of the reaction and thus the precipitation rates calculated from dMg/dt are not

meaningful (points "d" and "e"). Removal (precipitation + exchange) does not begin

Table 4.3: Steady-state dissolution and precipitation rates for 19-R and 19-S .

Forsterite dissolution rate,

Mg removal (mol cm-2 s-1)a

Forsterite dissolution

rate, Si removal (mol cm-2 s-1)b

Rate of Si disappearance from

solution (precipitation + back exchange) (mol cm-2 s-1)b

19-R Exp. 1.1 ± 0.6 × 10-13 1.2 ± 0.4 × 10-13 1.1 ± 0.2 × 10-13

19-R Model 9.4 ± 0.9 × 10-14 1.0 ± 0.4 × 10-13 1.0 ± 0.4 × 10-13

19-S Exp. 2.1 ± 0.4 × 10-14 2.5 ± 0.9 × 10-14 2.4 ± 0.6 × 10-14

19-S Model 2.1 ± 0.5×10-14 2.7 ± 0.5 × 10-14 2.6 ± 0.4 × 10-14

a. Calculated using dMg/dt

b. Calculated using Isotope Ratio Method (Gruber et al., 2013)

119

until the last time interval (14-19 days, point "f") as measured by the isotope ratio

method. The last sampling interval also represents the time when the aqueous phase is

supersaturated with respect to SiO2(am) (Fig. 4.1B). Thus, we do not see definitive

precipitation until the bulk aqueous phase exceeds saturation. Expected precipitation is

non-zero when calculated using Equation 4, though as discussed previously, the lack

of reliability of the rates calculated from dMg/dt reduces the legitimacy of any rate

based on a Mg mass balance. The precipitation rate in Table 4.3 for experiment 19-S

comes from the last time interval and Equation 3, and its similarity to the dissolution

rate suggests that experiment 19-S may also have reached steady-state forsterite

dissolution and SiO2(am) precipitation, though not until 14 days (experiment 19-R

reached steady-state dissolution/precipitation at 4 days). Values for rates with

uncertainties that spanned positive and negative values were not included in the figure.

From the rate analysis above, we can draw several conclusions. First, the

isotope ratio method is a superior method for measuring silicate mineral dissolution

rates when the rate is slow (Gruber et al., 2013). Secondly, we can extract SiO2(am)

precipitation and Si(aq) to >SiO2 exchange rates, which are useful for constraining the

surface kinetic model. Finally, we see strong evidence for a transient stage during the

first hour (19-R) to 2 days (19-S) of reaction, during which Mg is preferentially

removed from the mineral surface. In both experiments, SiO2(am) precipitation does

not begin until after the bulk aqueous fluid exceeds SiO2(am) saturation.

4.4.3 Direct evidence for both leaching and dissolution/reprecipitation mechanisms

Evidence for a "leached" surface layer can be found from both solution data

(rate calculation) and analysis of reacted forsterite surfaces. Unreacted forsterite

surfaces are stoichiometric (as measured by X-ray Photoelectron Spectroscopy in

Chapter 2); consequently preferential Mg release during the initial, transient stage of

reaction must lead to the formation of a Si-rich surface layer via a leaching

mechanism.

Further evidence for leaching is found in the SHRIMP-RG data, as the surfaces

of forsterite grains reacted for 2 days are indeed Si-rich (or Mg-depleted) (Fig. 4.2A-

B). However, these same surfaces exhibit a Si isotopic composition that is very

120

different from the aqueous phase, indicating that SiO2(am) precipitation from the bulk

fluid did not cause the Si-rich layer (Fig. 4.3). Both experiments 2-R and 2-S do show

slight enrichment of 29

Si in the surface layer relative to the bulk mineral composition

(Fig. 4.2C-D), but this is better explained by Si exchange between the aqueous phase

and the surface layer than by precipitation because the mineral surfaces are 53-75%

less enriched in 29

Si than the aqueous phase. Silicon exchange between the aqueous

phase and surface layer results in some uptake of the isotopic spike; the amount of

uptake depends on the relative rates of the forward and backward reactions. If the

backward reaction is faster than the forward reaction, the amount of tracer uptake

would be small. In the opposite situation, with a fast forward rate relative to the

backward rate, the mineral surface isotopic composition would closely resemble that

of the aqueous phase. The low degree of 29

Si enrichment in experiments 2-R and 2-S

suggests that the back reaction (Si attachment) is much slower than the forward

reaction; in other words, the net effect is removal of Si from the mineral in both the

rocking and stationary case.

After the initial, transient stage of reaction, dissolution becomes congruent and

approaches a steady-state rate (Fig. 4.5A,C). At this point, a leached, Si-rich surface

layer has formed on forsterite surfaces, and equivalent release rates of Si and Mg

require that this "leached" layer persists but does not grow in thickness. TEM/EDS

analysis supports this hypothesis (Chapter 3) The surface layers formed during

experiments 2-R and 2-S were depleted in Mg, and the Mg/Si ratios varied with depth.

The characteristic concentration gradient of the leached layer was also observed in

experiment 19-R and to a lesser extent in experiment 19-S, suggesting that the leached

layer retains its thickness and advances into the mineral as the reaction progresses.

At longer times, SiO2(am) precipitation occurs and creates a second, Si-rich

layer. Precipitation begins between 1 and 3 days (19-R) or 14 and 19 days (19-S), after

the aqueous phase reaches saturation with respect to SiO2(am) (Fig. 4.5B,D). Analysis

of forsterite reacted for 19 days indicates that the mineral surfaces are 14-15% more

enriched in Si (depleted in Mg) than 2-R and 2-S (Fig. 4.2A-B). Images and EDS

linescans from the HR-TEM study show that the precipitated layer is porous, very

121

depleted in Mg, and appears to grow in thickness with reaction extent (Chapter 3).

An interesting note is that even after precipitation begins, the mineral surface is

not isotopically equivalent to the aqueous phase. This discrepancy could have several

causes, the first being an analytical limitation of the SHRIMP-RG. Only one element

can be analyzed at any given time, and about 20 seconds are required to cycle through

the three elements analyzed in this study, meaning that each ratio shown is averaged

over 1-3 nm of depth. Further, the beam is incident on the mineral surface at a 45°

angle and secondary ions released by the beam do not all originate at the same depth.

The limitation of depth averaging means that a true surface measurement is impossible

to achieve, though we reduced the depth over which each measurement was averaged

by using a low beam current.

Secondly, the surface that we measure reflects a time-integrated fluid

composition. The isotopic composition of the fluid changes significantly throughout

the reaction, and we know that the exchange of H4SiO4 with >SiO2 is slow relative to

the forward rate of >SiO2 removal. Thus, the time required for isotopic equilibration

may be quite long, and experiments of a longer duration would be required in order to

achieve equivalence.

4.4.4 Surface kinetic model with Si isotopes

The conceptual model for forsterite dissolution presented in Chapters 3 and

Appendix 1 describes the forsterite surface as several layers, based on both TEM

imaging and a surface kinetic model constrained by Mg isotopes. The base layer is

crystalline forsterite, and an amorphous, Si-rich "active" layer sits on top. This layer is

formed via preferential removal of Mg, leaving behind a region depleted in Mg and

enriched in Si. This layer forms via process typically described as leaching, but we use

the term "active" instead because this layer is an actively dissolving reaction front that

recedes into the mineral as dissolution progresses (Chapter 3, Appendix 1). The next

layer is a precipitated SiO2 layer that forms only after the bulk fluid reaches saturation

with respect to amorphous silica. Silicon isotopes allow us to uniquely evaluate this

model and build on the concepts developed in Appendix 1.

This model differs from a traditional Arrhenius kinetic model in two major

122

ways. First, this model explicitly includes rates for both forward and backward

reactions, unlike the Arrhenius equation which accounts for only measured

concentration changes, themselves representing the net change of forward and

backward reactions. Secondly, this new model links spatial configuration (surface

layer formation and migration) with measurable changes in solution chemistry.

Briefly, protonation of Mg surface sites results in weakening of the Mg-O bond

and the irreversible release of Mg (Pokrovsky and Schott, 2000b) plus the generation

of a SiO2 surface site, >SiO2 (Reaction 1).

Reaction 1

Removal of Si from forsterite is described as a reversible reaction in which the surface

sites are hydrated to form silicic acid (Reaction 2).

Reaction 2

Finally, H4SiO4 precipitates as an amorphous silica surface layer that does not

passivate the mineral surface (Reaction 3). The precipitation step dominates H4SiO4

after the reaction reaches SiO2(am) saturation.

Reaction 3

The rate of forsterite dissolution is controlled by the rates of reactions 1 and 2, while

reaction 3 controls the concentration of H4SiO4.

The rate of reaction 1 (Equations 5) is a function of the detachment coefficient,

Mg, the volume of the active layer, VAL, and the probability that any given site

contains Mg, PMg.

ALMgMgMg VPR (5)

Appendix 1 includes expressions for both 26

Mg and 24

Mg in the rate expressions as the

model was originally developed using Mg isotopes to constrain the rates of reaction.

However, in this case, we remove the Mg isotope expressions and add Si isotope

expressions to incorporate the measurements of 29

Si and 30

Si. Thus, Si release is

described with two equations, one for each isotope measured, that are the sum of Si

detachment and attachment rates from/to the active layer surface. The expression for

29Si release from forsterite is shown in Equation 6, with an equivalent expression for

>Mg2SiO4 + 4H + ¾®¾ > SiO2 + 2H2O + 2Mg2+

> SiO2 + 2H2O¾®¾¬¾¾ H4SiO4 aq( )

SiO2 am( ) + 2H2O¾®¾¬¾¾ H4SiO4 aq( )

123

30Si and the rate of release of that isotope.

(6)

In the above expression, SiO2 is the removal rate of >29

SiO2 from the surface of the

active layer and P29SiO2 is the probability that a site contains 29

SiO2. The detachment

rates for all silicon isotopes were assumed to be the same; i.e. we ignored Si isotope

fractionation in the development of the model. Further, 28

Si was not explicitly

included in the model, but was instead assumed to follow 30

Si (i.e. both isotopes are

released from the forsterite at rates proportional to their mole fractions).

The

attachment rate is a function of a rate constant, k>29SiO2, the concentration of silicic

acid (consisting of 29

Si), and the site probability. The sum of the two rates is

multiplied by the forsterite surface area A, the site density Γ, and the molar volume,

Vmin (Appendix 1). Unlike Equation 5, this reaction does not include the term for the

active layer volume because Si is only removed from the active layer surface, whereas

Mg can be removed from the entire active layer volume.

Addition of silicon isotopes to the model requires calculation of the site

probabilities, P>29SiO2, and P>30SiO2. The probability is a function of the bulk forsterite

isotopic composition (X29Si=0.047, X30Si = 0.031), the mole fraction of Si in forsterite

(XSi/Fo = 1), and the molar volume Vmin. Again, the expression shown is for 29

Si

(Equation 7), but an analogous equation was used for 30

Si.

min

29

229V

XXP

AL

Si

AL

Si

SiO (7)

The probability does not change with time as it does in the case of Mg, as any kinetic

isotope fractionation at the per mil level during dissolution is overwhelmed by the

addition of the tracer 29

Si and thus could not be resolved.

The rate of silica precipitation is also expressed as two different equations, one

for each measured Si isotope. In both cases, the rate depends on a rate constant (kSiO2),

the solubility product of SiO2(am) (KSiO2), the concentration of silicic acid (H429

SiO4),

the mol fraction in the fluid phase (X29Siaq

), the surface area, and the molar volume

(Equation 8), following Druhan et al. (2013).

min2294

29

4229229229229 ) ( AVPSiOHkPR SiOSiOSiOSiOSiO

124

min

29229

2

29

429229229 1 Av

XK

SiOHXkR

aq

SiSiO

aq

SiSiOSiO

(8)

We assumed that negligible fractionation occurred during SiO2 precipitation, due to

the fact that the aqueous phase was greatly enriched with 29

Si from the addition of a

tracer.

The rates expressions in equations 5-8 are combined in order to link the

specific reactions to the active layer concentrations of Mg and each Si isotope

(Equations 9-11):

(9)

(10)

(11)

Equations 9-11 display the method through which the individual rates are coupled.

Because the rate expressions include the concentration terms (Px), and the

concentration terms depend on the rates, changing a single parameter in one rate

expression affects the other rates in the system. As such, the model cannot be easily

manipulated to produce a wide range of different reaction trajectories as it partly

constrained by the interrelationships of the rate expressions.

Experiments and analyses allow us to constrain the model significantly. The

active layer thickness was set to 25 nm based on HR-TEM data (Chapter 3) and the

surface area was measured by BET. Time-resolved solution compositions were used to

fit the equations to the data, by adjusting the rates of Mg and Si detachment (g,

SiO2=SiO2) and the rate constants of SiO2 precipitation (kSiO2=kSiO2).

Magnesium was used as the primary constraint because SiO2 precipitation results in a

H4SiO4 plateau, though the addition of Si isotopes in this study does allow for

calculation of a precipitation rate (actually the sum of SiO2 precipitation and SiO2

attachment to the mineral surface), which provides an additional limitation on the

model.

ALSiMgSiOSiOSiOMg

MgVXRRRR

dt

dP/)( /230229228

ALSiOSiMgSiMg

SiO VRXXRdt

dP// 229/29

229

ALSiOSiMgSiMg

SiO VRXXRdt

dP// 230/30

230

125

Two sets of model parameters were determined to fit experimental data from

experiments 19-R and 19-S (Table 4.4). The parameters resulted in steady-state rates

that are comparable to the measured rates (Table 4.3). In experiment 19-R, the rates of

Mg appearance in solution, Si appearance in solution, and Si removal from solution

agree; i.e. forsterite dissolution and SiO2 precipitation are occurring at the same rates

and dissolution is at steady state. The model indicates a slightly lower steady-state Mg

appearance rate, though the two are equivalent within uncertainty. In the case of

experiment 19-S, the rates of Si appearance in solution and Si removal are equal,

which again suggests steady-state forsterite dissolution and SiO2(am) precipitation.

The Mg removal rate (normalized by forsterite stoichiometry) is slightly lower, though

equivalent within uncertainty. Rates calculated by the model and from experimental

data agree within uncertainty.

One major conclusion from the model and relating specifically to experiment

19-S is that this experiment appears to reach steady-state only shortly before its

conclusion. The rates from the model continue to change with time for the duration of

the 20-day period over which the model was calculated. Thus, in the absence of

advective transport caused by mixing, the initial transient stage lasts up to 20 days,

which is five times longer than in the rocking (mixed) scenario. Experiment 19-S

progressed slower than experiment 19-R due to transport (diffusion) limitations

(Chapter 3), thus the extended transient stage is not surprising.

The parameters used to fit the experiment differ, with lower rate constants

needed to fit data from 19-S relative to 19-R. The parameters from 19-R were first

presented in Appendix 1, but the parameters for 19-S are different than the values

presented in the previous study. The addition of the isotopic tracer in this work

provided additional constraints on the rate of Si appearance and disappearance from

Table 4.4: Model parameters for 19-R and 19-S

νMg

(s-1

)

ν>SiO2

(s-1

)

k>SiO2

(M-1

s-1

)

kSiO2(am)

(mol m-2

s-1

)

Active layer

thickness (nm)

19-R Model* 6±3×10-4 3.8±0.3×10-5 <7.3×10-4 ~3.3×10-9 25

19-S Model 1.0±0.5×10-4 1.0±0.3×10-5 <5.0×10-4 ~3.3×10-9 21 *From Appendix 1

126

solution, so for the first time we were able to resolve forsterite dissolution rates based

on Si appearance and SiO2(am) precipitation rates based on Si disappearance. As a

result, the value for ν>SiO2 used in Appendix 1 was found to be nearly an order of

magnitude lower than required to match the measured Si appearance rate. Increasing

ν>SiO2 in the model resulted in a reasonable Si detachment rate, but it also increased

the steady-state Mg detachment rate (because the rate expressions are closely

coupled), and a reduction of the active layer thickness was needed to match the

concentration data. Results from a TEM study suggest that the active layer may be

thinner on forsterite from an unmixed reactor (Chapter 3), and thus the slight reduction

here is justified.

Fits of the model to experimental data are shown in Fig. 4.6. The fit for

experiment 19-R is quite good, with the model replicating both the short and long-

term behavior of Si and Mg concentrations as a function of time (Fig. 4.6A) as well as

the 29

Si/30

Si ratio as a function of time (Fig. 4.6C). The model also replicates the

concentration data for 19-S (Fig. 4.6B), though the model fit to the silicon isotope data

is imperfect (Fig. 4.6C). The parameters were chosen to model each experiment to fit

the data shown in Fig. 4.6 as well as match the rates of Mg appearance, Si appearance,

and Si disappearance (Table 4.3).

The 29

Si tracer was diluted more slowly in experiment 19-S than experiment

19-R due to a decreased forsterite dissolution rate; however, the poor model fit

suggests that the lower dissolution rate alone cannot account for the slower decrease in

29Si/

30Si. Thus, another factor, not accounted for by the model, must be important in

transport-limited systems. One possibility stems from the model's assumption of a

well-mixed active layer. In the experiments, attachment of H4SiO4 to surface sites on

the forsterite would initially result in a reservoir of surface >SiO2 enriched in 29

Si,

assuming negligible fractionation of the H4SiO4 (which is initially predominantly

29Si). However, the model cannot account for the additional

29Si in the top 1-2 unit

cells, and instead distributes it throughout the thickness of the active layer (12-14 unit

cells). As a result, the modeled active layer is only slightly enriched in 29

Si, whereas

the forsterite in the experiments may have significant 29

Si enrichment on the mineral-

127

fluid interface with a 29

Si/30

Si ratio resembling that of the aqueous phase. A higher

concentration of 29

Si on the mineral surface would result in slower dilution of the 29

Si

aqueous spike and may explain the discrepancy between the data and the model. In a

transport-limited system such as experiment 19-S, this effect may be stronger due to

higher rates of >SiO2 attachment relative to >SiO2 detachment (Table 4.4). Additional

spatial resolution in the model, specifically the addition of a third surface layer 1-2

unit cells thick and with an isotopic composition similar to that of the fluid, may

correct this issue.

Figure 4.6: Kinetic model fit to concentration data from rocking experiments

(A), stationary experiments (B), and isotope data from both experiments (C).

128

The possibility of a very thin (1-2 unit cells) surface layer that contains

actively exchanging >SiO2 is an important consideration in experiment that use a Si

isotopic tracer to measure silicate dissolution rates. Exchange between the surface

>SiO2 sites and H4SiO4 may result in a very thin surface layer enriched in the isotopic

tracer that persists beyond the first several hours to days of reaction. Thus, the

dissolution rate calculated from the tracer dilution at intermediate times (3-19 days in

the case of 19-S) may be lower than the actual dissolution rate. We expect this issue to

be particularly important for minerals that dissolve slowly, either due to transport

limitations as we observed in this study or due to slower reaction kinetics.

In summary, the kinetics of >SiO2 removal may not play as significant a role

as previously thought. A comparison of experiments with and without NaCl

(Appendix 1) and with and without mixing show a lack of a clear correlation between

the rates of surface detachment (ν>SiO2) and the dissolution rate. In fact, the experiment

with the second slowest dissolution rate (Exp. 3, [NaCl]=0 M) is associated with the

highest ν>SiO2 (Chapter 2, Appendix 1). In this experiment, the relatively slow

dissolution rate is due to a high >SiO2 attachment rate (k>SiO2, the backwards rate

constant). Thus, the long-term dissolution rate appears to be controlled by the

exchange between aqueous and surface SiO2, and neglecting the backwards rate (SiO2

attachment) yields an incomplete picture of forsterite dissolution, particularly under

conditions characterized by high H4SiO4.

4.4.5 Can we improve the reaction rate by complexing Si?

Numerous studies have used organic acids in order to increase the rate of

silicate mineral dissolution (Amrhein and Suarez, 1988; Bennett, 1991; Blake and

Walter, 1999b; Hänchen et al., 2006; Krevor and Lackner, 2009; Oelkers, 2001; Olsen

and Rimstidt, 2008; Prigiobbe and Mazzotti, 2011; Prigiobbe, 2009; Teir et al., 2007;

Wogelius and Walther, 1991). In particular, the dissolution rate of forsterite is

accelerated in the presence of oxalic and citric acids (Olsen and Rimstidt, 2008;

Prigiobbe and Mazzotti, 2011), which is thought to be the result of ligand-promoted

dissolution. Organic ligands may bind to Mg sites in forsterite, causing the Mg to be

overcoordinated and thus breaking the Mg-O bond (Liu et al., 2006). Thus, organic

129

acids increase the dissolution rate by enhancing the release of cations such as Mg, but

do not directly affect the release of Si from the mineral surface. This study introduced

Tiron, a catechol derivative that is known to form a complex with Si (Bai et al., 2008),

with the goal of specifically enhancing the net rate of Si removal from forsterite.

Tiron does increase the reaction rate during the initial, transient period of

reaction and has a small effect on steady-state forsterite dissolution rates. Between 8

and 35 days, forsterite dissolves at a rate of 1.8±0.2×10-13

mol cm-2

s-1

, which is 80 %

higher than the results of experiment 19-R and double the rate from Experiments 1 and

2 (Chapter 3). Rates for this comparison were all calculated using a linear regression

of [Mg] vs. time data (Chapter 3). While the rate improvement is relatively minor in

this case, we might expect a more significant effect in a transport-limited system.

Tiron was added with the anticipation that it would take advantage of pH

gradients in the aqueous phase to "shuttle" Si from the mineral surface to the bulk

fluid. More specifically, an elevated pH near the mineral surface (expected because

forsterite, an alkaline mineral, consumes protons during dissolution) would shift the

Tiron equilibrium towards the conjugate base, which would then complex with silicic

acid. As the complex moves away from the alkaline conditions near the mineral

surface, it would destabilize and re-form the acid catechol plus a separate silicic acid

molecule. However, results from both rocking and stationary experiments indicate that

the stationary experiments are transport-limited, and may have stronger concentration

gradients in the aqueous phase than rocking experiments. Stronger concentration

gradients could result in a stronger rate effect by Tiron (or another complexing agent).

Because the stationary experiments are perhaps most representative of in situ storage

in the subsurface, complexing agents should be considered as potential additives to

increase the rate of mineral carbonation, despite the relatively minor effect observed

using a well-mixed system.

4.5. Conclusions

Measurement of silicon isotopic compositions of the aqueous and solid phases

from four experiments allowed us to build upon the first two parts of this series in

developing a new kinetic model for forsterite dissolution under conditions relevant for

130

subsurface carbon storage. A suite of four reactions performed at 60 C and pCO2 =

100 bar for 2 and 19 days, with one experiment of each duration mixed (rocked) and

one of each duration not mixed (stationary) containing 29

Si as an isotopic tracer. The

Si isotopic composition of the aqueous phase was measured with MC-ICPMS and

yielded data on the rate of tracer dilution. Precise dissolution and precipitation rates

were calculated from the changing isotopic composition using the "isotope ratio

method" developed by Gruber et al. (2013). Measurements of the Si isotopic

composition of the solid phase were collected from the Stanford/USGS SHRIMP-RG.

Incorporation of 29

Si into the solid phase was 15% greater in forsterite reacted for 19

days than for 2 days, though isotopic equivalence was not observed.

The combination of aqueous and solid phase isotopic data plus HR-TEM data

from part 1 of this study (Chapter 3) resulted in the conclusion that forsterite dissolves

initially by a preferential release of Mg, resulting in the formation of a leached Si-rich

surface layer 20-25 nm thick. This layer forms during the initial, transient stage of the

reaction, which lasts 2 days (mixed experiment) to 19 days (unmixed experiment).

This "active" layer persists for 19+ days and advances into the mineral as a reaction

front. A kinetic model developed based on experimental data describes the relative

rates of Mg and Si removal from the active layer and is able to accurately predict time-

resolved solution compositions from a variety of mixed experiments (Appendix 1),

effectively linking molecular dynamics in the solid phase to bulk, measurable

dissolution rates. Further work is needed to improve the model for non-mixed

reactions, which are likely most representative of the subsurface.

Precipitation of secondary amorphous silica occurs after the bulk fluid reaches

saturation with respect to that phase, resulting in uptake of the isotopic tracer. The lack

of isotopic equivalence between the aqueous and mineral phases even after

commencement of SiO2(am) precipitation suggests that exchange between the solid

and aqueous phases is slow and longer reaction times would be required to observe

isotopic equilibrium. Precipitation occurs on the dissolving forsterite (on top of the

active layer) as well as on reactor walls, though the phase is porous and does not

appear to passivate the mineral surface (Chapter 3).

131

Finally, Tiron (a catechol derivative) was added to the reaction solution to act

as a shuttle, taking advantage of pH gradients that may exist near the mineral surface

to complex with >SiO2 and transport it away from the mineral to the bulk fluid. We

observed a modest increase in the steady-state dissolution rate with the addition of

Tiron in a mixed reaction, though we would expect a larger effect if Tiron was used in

an unmixed reactor where concentration gradients may be more pronounced.

4.6 Acknowledgments

We would like to acknowledge the Global Climate and Energy Project at

Stanford University (GCEP-48942) for funding this work. We also acknowledge the

facilities which operate and maintain the instrumentation used for this study: The

Stanford Nanocharacterization Laboratory, the Stanford-USGS SHRIMP-RG

Laboratory, and the Stanford ICP-MS/TIMS Laboratory. In particular, we

acknowledge Karrie Weaver and Caroline Harris for their technical assistance.

132

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Appendix 1: The role of the Si-rich surface layer in olivine dissolution 2: A spatially resolved surface kinetic model

Kate Maher1, Natalie C. Johnson2, Laura Nielsen Lammers1*, Abe B. Torchinsky1, Karrie L. Weaver1,

Dennis K. Bird1 and Gordon E. Brown, Jr.1,2,3

1 Department of Geological and Environmental Sciences,

Stanford University, Stanford CA 94305-2115, USA 2 Department of Chemical Engineering,

Stanford University, Stanford CA 94305-2115, USA 3 Department of Photon Science and Stanford Synchrotron Radiation Lightsource,

SLAC National Accelerator Laboratory, 2575 Sand Hill Rd., MS 69, Menlo Park, CA 94025, USA

*Now at: Department of Environmental Science, Policy, and Management,

UC Berkeley, CA 94720, USA

Submitted to Geochimica et Cosmochimica Acta, July 2014.

138

Abstract

The development of complex alteration layers on silicate mineral surfaces

undergoing dissolution is a widely observed phenomenon. Given the complexity of

these layers, most kinetic models used to predict rates of mineral-fluid interactions do

not explicitly consider their formation. As a result, the relationship between the

development of the altered layers and the final dissolution rate is poorly understood.

To improve our understanding of the relationship between the alteration layer and the

dissolution rate, we developed a spatially resolved surface kinetic model for olivine

dissolution and applied it to a series of closed-system experiments consisting of three-

phases (water (± NaCl), olivine, and supercritical CO2) at conditions relevant to in situ

mineral carbonation (i.e. 60˚C, 100 bar CO2). We also measured the corresponding

26

Mg of the dissolved Mg during early stages of dissolution. Analysis of the solid

reaction products indicates the formation of Mg-depleted layers on the olivine surface

as quickly as 2 days after the experiment was started and before the bulk solution

reached saturation with respect to amorphous silica. The 26

Mg of the dissolved Mg

decreased by approximately 0.4‰ in the first stages of the experiment and then

approached the value of the initial olivine (-0.35‰) as the steady-state dissolution rate

was approached. We attribute the preferential release of 24

Mg to a kinetic effect

associated with the formation of a Mg-depleted layer that develops as protons

exchange for Mg2+

.

We used the experimental data to calibrate a surface kinetic model for olivine

dissolution that includes crystalline olivine, a distinct “active layer” from which Mg

can be preferentially removed, and secondary amorphous silica precipitation. By

coupling the spatial arrangement of ions with the kinetics, this model is able to

reproduce the early and steady-state long-term dissolution rates, and the kinetic

isotope fractionation. In the early stages of olivine dissolution the dissolution rate is

controlled by exchange of protons for Mg, while the steady-state dissolution rate is

controlled by the removal of both Mg and Si from the active layer. Modeling results

further indicate the importance of the spatial coupling of individual reactions that

occur during olivine dissolution. The inclusion of Mg isotopes in this study

139

demonstrates the utility of using isotopic variations to constrain interfacial mass

transfer processes. Alternative kinetic frameworks, such as the one presented here,

may provide new approaches for modeling fluid-rock interactions.

140

A1.1. Introduction

The mineral olivine (i.e. (Mg,Fe,Ca)2SiO4), common in lower crustal and

upper mantle rocks, is one of the most reactive rock-forming silicate minerals under

surface and near surface conditions. As a result, the dissolution rate of olivine is linked

to the evolution of the lithosphere and upper mantle (Sleep et al., 2004), the utility of

olivine as an industrial feedstock for mineral carbonation (Oelkers and Cole, 2008),

neutralization of acid mine drainage (Jambor et al., 2007), and geoengineering using

enhanced silicate weathering (Hartmann et al., 2013; Koehler et al., 2010). Given the

high reactivity of olivine, the surface chemistry and dissolution kinetics have been

studied under a broad range of experimental conditions, including closed-system

(Daval et al., 2011a; Giammar et al., 2005; King et al., 2010) and well-mixed flow-

through dissolution experiments on powdered olivine samples (Oelkers, 2001;

Pokrovsky and Schott, 2000b), as well as single crystals (Jarvis et al., 2009; Saldi et

al., 2013). Characterization of the reaction products has also included a range of

techniques, such as x-ray photoelectron spectroscopy (Olsson et al., 2012; Pokrovsky

and Schott, 2000a; Zakaznova-Herzog et al., 2008), infrared spectroscopy (Giammar

et al., 2005; Loring et al., 2011; Pokrovsky and Schott, 2000a), transmission electron

microscopy (Bearat et al., 2006; Daval et al., 2011a) and atomic force microscopy

(Ruiz-Agudo et al., 2012). Despite the range of studies focused on olivine reactivity in

the presence of aqueous solutions, a precise description of the processes that control

olivine dissolution kinetics has been elusive (Daval et al., 2011a; Rimstidt et al.,

2012). This uncertainty has been attributed to the broad range of experimental

conditions (Rimstidt et al., 2012), combined with the implicit complexity of multi-step

heterogeneous reactions (Lasaga and Luttge, 2004). The lack of a comprehensive

model for olivine dissolution prevents the design of reliable strategies for both ex situ

and in situ mineral carbonation. In this paper we present a new spatially resolved

kinetic model for olivine dissolution constrained by time-resolved elemental

compositions, Mg isotope fractionation and High-Resolution Transmission Electron

Microscopy (HR-TEM) analysis.

Characterization studies of olivine surfaces from laboratory dissolution

141

experiments (Bearat et al., 2006; Daval et al., 2011a; Ruiz-Agudo et al., 2012) and

naturally-weathered olivine (Hellmann et al., 2012) have observed a pervasive Mg-

depleted amorphous layer on the olivine surface after exposure to water. Exploration

of the olivine-fluid interface using HR-TEM suggests this coating is typically less than

50 nm thick and forms rapidly (hours to days) after contact between the fluid and

olivine surface (Chapter 3, Bearat et al., 2006; Daval et al., 2011a; Pokrovsky and

Schott, 2000a; Ruiz-Agudo et al., 2012). However, the temporal evolution of the

coating has not been explored until recently (e.g., Chapter 3). As a consequence, the

relationship between the Mg-depleted layer and the overall mineral dissolution rate

has remained unclear.

The rapid development of Mg-depleted layers on the olivine surface during

dissolution is consistent with exchange of Mg2+

ions for protons, followed by

repolymerization of SiO4 tetrahedra. Several studies have also observed the olivine

dissolution rate to decrease as amorphous silica (SiO2(am)) saturation is approached

(Chapter 2; Daval et al., 2011b; Pokrovsky and Schott, 2000b), indicating that the

amorphous layer moderates the flux of Mg2+

and Si4+

ions from the olivine surface to

the bulk solution. In contrast, based in part on the sharp interface between the fresh

crystal and the surface layer, other studies have suggested that such coatings (which

are observed on the surfaces of many silicate minerals during dissolution) are a newly

formed precipitate that does not impact release of ions from the surface (Hellmann et

al., 2012). As noted in Chapter 3, the two processes are not mutually exclusive and

both preferential Mg removal and new precipitation of a secondary phase could occur

simultaneously. Regardless, these observations suggest that the spatial relationship

between reactions involving Mg and Si may play a role in determining the net olivine

dissolution rate. However, current models do not commonly address such spatial

considerations, and most quantitative models do not explicitly consider the multi-step

nature of the dissolution process, suggesting the need for an alternative kinetic model

for olivine, and by extension, silicate mineral dissolution.

General insights into the mechanisms associated with silicate mineral

dissolution may come from isotopic studies: kinetic isotope fractionation during

142

mineral dissolution under experimental conditions is now widely observed. For

example, fractionation has been noted for Mg isotopes during experimental olivine

dissolution (Wimpenny et al., 2010) and for Fe isotopes during experimental

hornblende (Brantley et al., 2004), micas (Kiczka et al., 2010) and goethite dissolution

studies (Wiederhold et al., 2006). Such isotope effects, which are not predicted by the

classical description of bulk mineral dissolution, provide constraints on the processes

occurring at mineral surfaces during dissolution. As a result, various models have been

developed to explain the preferential removal of ions from mineral surfaces. Brantley

et al. (2001; 2004) first observed Fe isotopic fraction associated with hornblende

dissolution both in the presence and absence of siderophores, but they did not observe

fractionation during goethite dissolution under the same conditions. The magnitude of

Fe isotopic fractionation in these studies also varied with the degree of fluid mixing

and the binding affinity of the ligand for Fe. The fractionation was attributed to a

kinetic isotope effect associated with the formation of a “leached layer” at the mineral

surface, however time resolved measurements or HR-TEM images were not available.

A number of additional studies have also demonstrated isotopic fractionation during

mineral dissolution (Pearce et al., 2012; Wimpenny et al., 2010; Ziegler et al., 2005).

Such fractionation is often associated with the initial stages of mineral dissolution,

before a steady state and/or stoichiometric dissolution rate is reached and the isotopic

composition of the dissolved fraction returns to that of the initial solid. For example,

Wimpenny et al. (2010) observed that the dissolved 26

Mg released from forsterite

under flow-through condition was approximately 0.2 to 0.4‰ lower than that of the

initial solids, an effect which was attributed to kinetic fractionation during mineral

dissolution. Such transient isotopic fractionation conveys important information about

the processes occurring at mineral surfaces and thus the extent and duration of the

isotope effects can be used to further constrain the interfacial processes controlling

mineral dissolution.

Macroscopic descriptions of mineral dissolution and precipitation are

numerous, and recent studies have extended these approaches to explain kinetic and

equilibrium isotope partitioning under surface reaction-controlled conditions

143

(DePaolo, 2011; Druhan et al., 2013). Such descriptions commonly assume that the

net reaction rate is the difference between the gross forward (precipitation) and

backward (dissolution) rates, where each rate is associated with a kinetic fractionation

(DePaolo, 2011). Although in practice it is difficult to quantify either, the backward

rate and attendant kinetic fractionation factor may be constrained by the far-from-

equilibrium dissolution rate (DePaolo, 2011). However, according to macroscopic

descriptions, persistent kinetic isotope effects during dissolution cannot be quantified

because the surface layers are removed stoichiometrically when a single net rate

constant and surface area are assumed. “Ion-by-ion” models provide a microscopic

description of growth kinetics and isotope and trace element partitioning based on

quasi-elementary ion attachment and detachment events (Nielsen et al., 2013; Nielsen

et al., 2012; Watkins et al., 2013). We use a similar surface kinetic approach here to

develop a model that links the microscopic processes at the olivine interface to the

macroscopic behavior indicated by the net dissolution rate. Because the individual

ions (i.e. Mg2+

, Si4+

and H+) are evaluated independently, but coupled via spatial and

stoichiometric considerations, the approach provides an alternative description of

mineral dissolution and the attendant kinetic isotope fractionation that is consistent

with both microscopic (HR-TEM) and macroscopic (time resolved fluid compositions)

observations.

To develop this framework, we present Mg isotope data for previously

published closed-system olivine dissolution experiments conducted at 60˚C, 100 bar

CO2, with solution compositions and rates detailed in Chapter 2. We also consider a

complementary suite of closed-system experiments conducted in the presence or

absence of fluid mixing where the reacted olivine surfaces have been characterized

using HR-TEM as described in Chapter 3. To explain the results from the four

experiments, a spatially resolved surface kinetic modeling approach is presented as an

alternative framework for describing forsterite (Mg2SiO4) dissolution kinetics. This

model reproduces the time-resolved solution compositions, the observed isotopic

fractionation, and the TEM surface structure and composition.

144

A1.2. Methods

In this study we use the experimental run products (i.e. reacted olivine grains

and resulting fluid samples) and experimental data (i.e. measured Mg and Si

concentrations, measured alkalinity, and calculated pH, saturation states and

dissolution rates) from a series of closed-system olivine dissolution experiments

conducted at 60˚C and 100 bar CO2 and detailed in Chapter 3. A brief description of

these experiments and the results is presented below. We report new data for the

26

Mg of the experimental olivine and the dissolved Mg over the duration of one

short-term experiment.

A1.2.1 Summary of olivine dissolution experiments

The experiments detailed in Chapters 2, 3, and Table A1.1 were conducted in

a flexible and inert Au-bag reaction vessel design with modifications for sampling and

analysis of CO2 (Chapter 2; Rosenbauer et al., 2005). Briefly, liquid CO2 was added to

the reaction vessel with high-pressure syringe pumps and temperature was maintained

by a proportional controller and measured with a calibrated type K thermocouple.

Serial samples were obtained throughout each experiment for total CO2 analysis,

cation analysis, and alkalinity titration (see details in Chapter 2). The olivine sample

is (Fo92) from the Twin Sisters Dunite, Washington, USA. The BET surface areas are

Table A1.1: Summary of experiments from Chapters 2 and 3 used in model development.

Experiment Name Temp. (˚C) PCO2 (bars) Duration

(days)

Electrolyte Mixing Mg

isotopes

Experiment 1a 60 100 74 0.5 M NaCl Well-mixed

Experiment 2 a 60 100 92 0.5 M NaCl Well-mixed

Experiment 3 a 60 100 4 none Well-mixed yes

Experiment 4 a 60 100 98 none Well-mixed

2-Rocking (2R)b 60 100 2 0.5 M NaCl Well-mixed

19-Rocking (19R) b 60 100 19 0.5 M NaCl Well-mixed

2-Stationary (2S) b 60 100 2 0.5 M NaCl Not mixed

19-Stationary (19S) b 60 100 19 0.5 M NaCl Not mixed

a: presented in Chapter 2

b: presented in Chapter 3

145

0.6410 m2/g for experiments 1-4 (38 – 75 m) and 0.57 m

2/g (70-105 m) for

experiments 2R, 19R, 2S, 19S, respectively. For the later series of experiments, a

larger grain size was used to facilitate characterization of the olivine surface after

reaction. The BET surface areas are used in the subsequent calculations.

The results of the eight experiments from Chapters 2 and 3 are presented in

this paper, all using the same starting material (Fo92 olivine), temperature (60oC), CO2

pressure (100 bar), and water:rock ratio by mass (50:1) as summarized in Table A1.1.

Six experiments contained 0.5 M NaCl, whereas two had no added electrolyte. Four

experiments were conducted to assess the temporal evolution of the olivine surface

under well-mixed (continuous rocking of the experimental vessel at 8

rotations/minute) and poorly mixed (stationary experimental vessel) conditions. The

reacted forsterite grains were characterized by HR-TEM, with details provided in

Chapter 3. The duration of the experiments ranged from 2 to 94 days. The shortest

experiments were conducted with higher sampling frequency to look at the initial

(non-steady state) dissolution kinetics as silica saturation is approached.

A1.2.2 Mg isotope analyses

We analyzed the isotopic composition of the starting olivine material and the

dissolved Mg from one experiment: experiment 3 (4 days, no electrolyte). For the

long-term experiments, the sample volumes were small in order to maintain

approximately constant water:rock ratios over more than 90 days. Thus, most of the

early samples for experiments 1, 4, 2R, 2S, 19R, 19S were consumed for elemental,

alkalinity, dissolved inorganic carbon (DIC) and Si isotopic analyses. For experiment

2, we found small samples combined with the presence of 0.5 M NaCl compromised

the isotopic analysis of the dissolved Mg.

All sample preparation procedures were carried out in laminar flow hoods in

the PicoTrace metal-free clean laboratory at Stanford University, and all acids were

Optima grade diluted with Milli-Q (18 M) water. Both San Carlos, AZ olivine and

the experimental olivine (WA) derived from the Twin Sisters Dunite (50 g) were

dissolved in capped screw-top Teflon beakers with 1 ml of a 3:1 mixture of

146

concentrated HF and HNO3, and left overnight at room temperature. The beakers were

then heated to approximately 90C for 24 hours before the caps were removed, and the

HF and HNO3 mixture was evaporated. The samples were then dissolved in 1 ml of

aqua regia, left overnight at room temperature, and then evaporated to dryness and

finally dissolved in 1N HNO3 prior to cation exchange chromatography. Fluid samples

were centrifuged for 10 minutes, evaporated to dryness, and dissolved in 1N HNO3

prior to cation exchange chromatography.

To purify and isolate Mg for isotopic analysis, Mg dissolved in 1N HNO3 was

loaded onto 0.5 ml of pre-cleaned Bio-Rad AG50W-X12 (200-400 mesh) resin.

Matrix elements were eluted in 1 N HNO3 and 0.1 N HF. Magnesium was eluted in 1

N HNO3. The samples were then dried and the above procedure was repeated twice.

Calcium was removed from the sample using Eichrom DGA resin (50-100 m).

Following the steps outlined above, the samples were dissolved in 2 N HNO3 and

loaded onto columns containing 0.2 ml of pre-cleaned Eichrom DGA resin. Mg was

eluted and collected with 2N HNO3 while Ca remained on the columns. The collected

samples were then evaporated to dryness to complete the Mg separation process. The

yield on the chromatographic procedure was >99.95%. Processing of the pure Mg

standards CAM1 and SU1 (internal elemental standard) with this technique did not

lead to a detectable shift in the measured Mg isotope ratio.

Mg isotope measurements were carried out on a Nu Plasma MC-ICP-MS using

medium resolution and wet plasma at Stanford University. Purified Mg samples were

dissolved in 2% HNO3, centrifuged, and diluted to 1.7 ppm prior to MC-ICP-MS

analysis. Purified Mg-bearing solution was introduced to the instrument through a

self-aspirating Glass Expansion SeaSpray nebulizer directly into the spray chamber.

Mg isotopes were measured simultaneously with 24

Mg, 25

Mg, and 26

Mg collected in

the L10, L5, and H1 Faraday cups, respectively; ion beams were positioned such that

measurements were collected on the low-mass side of the CN+ interference. Sample

measurements were bracketed by analysis of the standard DSM3, and between all

measurements a 2% HNO3 rinse solution was aspirated for approximately two minutes

until the signal on the H1 Faraday cup was less than 1x 10-4

volts (Galy et al., 2003).

147

For each analysis, (26/24

Mg)DSM3/‰ (and (25/24

Mg)DSM3/‰) values were calculated by

comparing the measured 26

Mg/24

Mg (25

Mg/24

Mg) ratio of the samples to the average

26Mg/

24Mg (

25Mg/

24Mg) ratio of the bracketing measurement standards. Hereafter, we

abbreviate the (26/24

Mg)DSM3/‰ as the 26

Mg. To constrain the accuracy and

precision of measurements made on the MC-ICP-MS, we compared the measured

isotope ratios at two standard deviations (2 s.d.) of pure Mg and natural rock reference

materials to accepted or reported values (Table A1.2). The reference material CAM1

was repeatedly measured over four months of analytical sessions with a 26

Mg value

of -2.60 0.17 (n=32), in agreement with the accepted value of -2.580.14 (Galy et al.,

2003). The isotopic ratio of an in-house synthetic measurement standard consisting of

1000 ml of High-Purity Standards pure 1000 ppm Mg elemental standard was

characterized by repeated measurements over four months. This measurement

standard, “Stanford University 1” (SU1) was analyzed 76 times and found to have a

26

Mg value of -0.55 0.14 (n=76).

The natural rock standards BHVO-1, BIR-1, and San Carlos olivine were also

within the uncertainty of accepted values. The measured 26

Mg of BHVO-1 was -0.19

Table A1.2: Mg isotope data for experimental olivine and experiment 3 from Chapter 2 along with

average values for reference materials, where n is the number of times the individual sample was

analyzed to obtain the average value and standard deviation.

Samples Time

(days)

[Mg]

(mM) 26

MgDSM3 2 s.d.

Exp. Olivine -0.35 ± 0.10 (n=8)

Exp. 3 (no NaCl) 0.04 7.36 -0.71 0.21 (n=7)

0.13 9.30 -0.64 ± 0.12 (n=4)

0.29 10.12 -0.58 ± 0.09 (n=3)

0.63 13.92 -0.52 ± 0.21 (n=5)

0.96 12.40 -0.60 ± 0.14 (n=3)

1.44 13.68 -0.58 ± 0.18 (n=3) 2.00 16.77 -0.48 ± 0.06 (n=3)

2.52 15.80 -0.47 ± 0.27 (n=6)

Standards

CAM 1 -2.60 ± 0.17 (n=32)

BHVO-1 -0.19 ± 0.09 (n=7)

BIR -0.25 ± 0.03 (n=2)

San Carlos

Olivine -0.75

±

0.09 (n=5)

SU-1 -0.55 ± 0.14 (n=76)

148

0.09 (n=7) within the previously reported values of -0.30.08 (Huang et al., 2009)

and -0.085 (Baker et al., 2005). Measured 26

Mg of BIR-1 was -0.25 0.03 (n=2),

which is consistent with the value of -0.23 0.23 (Wombacher et al., 2009) and -0.29

(Baker et al., 2005). Measured San Carlos olivine 26

Mg was -0.75 0.09 (n=5), in

agreement with other reported values of -0.73 0.06 (Teng et al., 2007). In all cases,

the measured 26

Mg values were within the uncertainty of the literature values. Each

sample reported in Table A1.2 was measured 3-7 times during different analytical

sessions, and the average values and standard deviations are reported along with the

number (n) of times that an individual sample was analyzed. Because of the small

volume of samples, duplicate samples of experiments could not be prepared and thus

the reported uncertainties reflect only the measurement uncertainty.

A1.3. Results

A1.3.1 Elemental concentrations and Mg isotope results

The evolution of Mg and Si concentrations and pH over time for the well-

mixed experiments 1 and 2 (with 0.5 M NaCl) and experiments 3 and 4 (no NaCl) is

summarized from Chapter 2 and shown in Figs. A1.1A-C. Early experimental stages

(ca. < 10 hours) are characterized by incongruent dissolution with preferential release

of Mg over Si. At longer times, the Mg release rate is constant while Si concentrations

plateau due to precipitation of SiO2(am) (Chapter 2). Magnesite saturation was

reached between 10 and 25 days in the experiments with NaCl (experiments 1 and 2)

and at 90 days in the absence of NaCl (experiment 4), although magnesite

precipitation did not occur in measurable amounts until after about 75 days in the

NaCl experiments (Chapter 2). The alkalinity increased over the duration of each

experiment in stoichiometric relation to the amount of olivine dissolution. Early and

long-term rates are markedly different between the experiments with and without 0.5

M NaCl. As suggested by the data in Fig. A1.1, olivine dissolution rates under the

closed-system conditions do not exhibit the pH dependence over the pH range 4 to 7

observed in experimental flow-through studies (e.g., Pokrovsky and Schott, 2000b).

The weak dependence on pH is an important feature of the data explored in the

149

subsequent modeling efforts.

The second series of experiments (i.e. well-mixed experiments 2R and 19R,

and unmixed experiments 2S and 19S, all with 0.5 M NaCl) are shown in Fig. A1.1D-

E. These experiments were conducted over shorter durations to examine the evolution

of the Si-rich layer under both well-mixed conditions, and in the absence of

mechanical mixing. Complementary high-resolution TEM analyses after 2 and 19 days

Figure A1.2. Magnesium isotope data for the short-term experiment 3 (no NaCl) over 3

days of reaction time. Error bars represent 1.s.d.

Figure A1.1. Summary of previous

experimental data from Chapter 2 in (A)-(C)

and Chapter 3 in (D)-(E). Vertical arrows in

(A) and (D) indicate time when experiments

reached MgCO3 saturation, horizontal line

with arrows indicates interval when MgCO3

precipitation is thought to have occurred in

experiment 2, based on the lack of

precipitates in experiment 1 at 74 days.

Horizontal dashed lines in (B) and (E)

indicate saturation with respect to amorphous

silica. Error bars represent 1 s.d.

150

of reaction constrain the evolution of the thickness and composition of the Si-layer and

olivine surface (Chapter 3). The well-mixed experiments (2R and 19R) agree well

with experiments 1 and 2, which were conducted under similar conditions. The poorly

mixed experiments show a similar transient rapid increase in Mg release over Si,

followed by near steady long-term dissolution, but at much slower rates.

Results of Mg isotopic measurement of WA olivine and the samples from

experiment 3 are presented in Table A1.2. All fluid samples from experiment 3 were

isotopically enriched in 24

Mg (26

Mg from -0.71 to -0.47) compared to WA Olivine

(26

Mg of -0.35). The 26

Mg of the first fluid sample has the lowest 26

Mg value, and

as the experiment progressed the dissolved 26

Mg values increased progressively such

that the 26

Mg of the final sample is within uncertainty of the value of unreacted WA

Olivine (Fig. A1.2). The Mg isotopic measurements of samples from experiment 3

are consistent with the preferential release of 24

Mg during olivine dissolution. The

addition of isotopically light Mg during initial phases of dissolution is consistent with

prior results from flow-through experiments (Wimpenny et al., 2010).

A1.4. Discussion

A1.4.1 Conceptual framework and spatial considerations for olivine dissolution

The experimental results considered here represent an array of conditions

likely to occur as CO2-rich fluids react with lithologies rich in olivine. The first set of

experiments detailed in Chapter 2 (experiments 1-4) considered the effect of

supporting electrolyte and found that in the presence of 0.5 M NaCl the initial olivine

dissolution rates were slower, while the long-term rates were more rapid, compared to

the experiments with no electrolyte in the initial solution. We present new 26

Mg data

for the electrolyte-free experiment. The second set of experiments (2R, 19R, 2S, 19S)

detailed in the first part of this series (Chapter 3) compared the results of experiments

conducted under well-mixed and poorly mixed conditions. In the mixed experiments,

dissolution rates were approximately five times faster compared to the poorly mixed

experiments. Cross sections of reacted olivine grains after 2 and 19 days of reaction

were also analyzed for crystallinity and chemical composition using HR-TEM. A

151

complex sequence of Mg-depleted surface layers were observed: (1) olivine which is

crystalline, but depleted in Mg relative to the bulk olivine composition, (2) an

amorphous “active layer” (AL) where Mg/Si changes rapidly with depth, and (3) a

newly precipitated amorphous layer where Mg/Si < 0.3 (Fig. A1.3). The Mg-depleted

olivine was most pronounced in the mixed experiments, where Mg depletion was

observed over zones extending up to 80 nm within crystalline material (Fig. A1.3C).

In poorly mixed experiments this zone was less than 20 nm thick (Chapter 3). The

active layer was present on all reacted forsterite examined, and was of a similar

thickness in the HR-TEM profiles from all four experiments. In contrast, the

precipitated layer was only visible in experiments that exceeded SiO2(am) saturation.

Given the 20 to 40% porosity observed in TEM images (Chapter 3), the precipitated

layer does not form an appreciable barrier to ion transport from the active layer to the

bulk fluid.

The entire sequence of alteration, from Mg-depleted crystalline olivine to the

precipitated Si layer, is consistent with the both the development of a non-

stoichiometric “leached layer” (e.g., Casey and Bunker, 1990; Casey et al., 1988;

Chou and Wollast, 1984; Hellmann, 1997; Luce et al., 1972; Stillings and Brantley,

1995), and a process of interfacial dissolution-reprecipitation (Hellmann et al., 2012;

King et al., 2010; King et al., 2014). However, given the stratigraphy evident in the

alteration layer, including a sharp transition between amorphous and crystalline

material and multiple chemical gradients indicated by the Mg/Si (and Fe/Si) profiles,

Chapter 3 further subdivided the altered layer into the zones defined above and in Fig.

A1.3. In the development of the kinetic model, we make additional simplifications.

First, we assume an average value for Mg/Si within the active layer that evolves from

an initial stoichiometric value to the value required by mass balance constraints

imposed by time resolved solution compositions and the HR-TEM profiles (Fig.

A1.3C). The initial development of the active layer should preferentially contribute

26Mg to solution, resulting in lower dissolved

26Mg relative to the bulk olivine as

observed. Second, we do not explicitly treat the process of solid-state diffusion (e.g.

Chapter 3, Hellmann et al., 2012; Yeng et al., 2009) implied by the complex Mg/Si

152

Figure A1.3. Conceptual model for the surface kinetic model. (A) High resolution TEM image

shows the general features observed in the outer 100 nanometers of olivine after reaction for 2

days (modified from Chapter 3), with the fluid-solid interface to the left of the image. Average

Mg/Si ratios measured by EDS are provided for reference. The black arrows indicate the

migration of the active layer into the crystalline olivine over time, as determined by the rates of

the individual reactions in (B). (B) The conceptual model for the independent rates considered in

the model and the resulting mass balance constraints. The net rate (Rnet) is the Mg exchange rate

plus the net difference between the net <SiO2 dissolution rate and the net precipitation rate of

amorphous silica. Magnesium is removed from the active layer of volume VAL, while >SiO2 can

only be dissolved or added from the surface of the active layer. (C) Representative HR-TEM EDS

linescan of the Mg/Si ratio in reacted olivine from experiment 19R from Chapter 3 with a Lowess

curve fit (green line) compared to the model representation (bold teal line). The grey shaded

region (indicated (-)) shows the Mg depletion relative to the assumed stoichiometric composition,

while the green shaded region (indicated (+)) shows the Mg-enrichment in the active layer

relative to model Mg/Si. To maintain mass balance the total Mg in the two zones must be equal.

153

gradients in both the amorphous active layer and the Mg-depleted olivine. Instead, we

assume a stoichiometric flux of Si and Mg into the active layer and account for the

total Mg depletion within the active layer. The consequences of these assumptions will

be discussed in a subsequent section. Conceptually, the active layer can be viewed as a

reaction front that maintains a constant thickness as it advances into the unreacted

olivine. This thickness is moderated by the balance between the removal of ions at the

fluid-active layer interface and the supply of ions from the crystalline olivine.

In summary, the key features of olivine dissolution we seek to address through

development of an alternative kinetic model include: (1) non-stoichiometric release of

Mg relative to Si during the early stages (ca. <1 day of reaction time); (2)

enhancement of the Mg release rate at early times in the absence of an electrolyte,

followed by lower steady-state dissolution rates compared to experiments with an

electrolyte present, (3) preferential release of 24

Mg to solution during the early stages,

(4) weak dependence of the dissolution rate on pH under closed-system experimental

conditions, and (5) a zone of Mg depletion between the fluid-solid interface and the

crystalline olivine. As many of these features would not be captured by existing rate

laws, we have developed a framework that considers the exchange of individual ions

within the active layer and between the surface of the active layer and the bulk

solution.

A1.4.2 Spatially resolved surface kinetic model for olivine dissolution

A1.4.2.1 Stoichiometric and mass balance constraints

For olivine, where octahedrally coordinated Mg is linked to isolated silica

tetrahedra, protonation of the magnesium surface sites is required to release

magnesium from the bulk crystal (for clarity, Fe is omitted below). The hydrolysis

reaction requires the exchange of four protons for two magnesium ions at the surface

of the mineral, followed by polymerization of the isolated surface silica tetrahedra

(Pokrovsky and Schott, 2000b), according to the following net reaction:

(1)

>Mg2SiO4 + 4H + ¾®¾ > SiO2 + 2H2O + 2Mg2+

154

where > represents a site within the active layer. At low temperatures, reaction (1) is

considered irreversible, and should depend on pH. However, the exact dependence is

difficult to constrain as protons may also be distributed between surface sites and/or

adsorbed to surface layers (Pokrovsky and Schott, 2000). Diffusion of Mg out of the

active layer is not the rate-controlling step for reaction (1) under well-mixed

conditions because the steady-state dissolution rate is independent of Mg

concentration in solution (Chapter 3).

Although reaction (1) has been included in previous models, it has not been

explicitly linked to the compositional evolution of the surface. Here, reaction (1) only

occurs within the volume (VAL, m3) of material defined as the active layer (Fig.

A1.3B), as suggested by both the HR-TEM results and the early non-stoichiometric

dissolution observed in the experiments. Penetration of protons into the olivine

structure at depths greater than one unit cell is further suggested by x-ray

photoelectron spectroscopy (XPS) of the olivine surface (Chapter 2; Pokrovsky and

Schott, 2000a). The VAL is calculated as FoAhVm, where Fo is the site density of

olivine (3.3 x 10-5

mol/m2 Wogelius and Walther, 1991), A is the physical surface

area in m2

from measured BET surface area and the mass of initial olivine, Vm is the

molar volume of olivine (4.38 x 10-5

m3/mol) and h is the number of olivine layers

from which Mg can be extracted according to equation (1). A list of parameters is

presented in A1.3. The equivalent thickness of the active layer is 20 nm (h ≈14) with

a steady-state Mg/Si of 0.3 to 1.5 determined by (1) the rates required to match the

measured Mg and Si release rates of Fig. A1.1 and (2) mass balance considerations

based on HR-TEM imaging of olivine cross-sections shown conceptually in Fig.

A1.3C.

As the active layer forms, residual silica populates the volume that was once

crystalline olivine. The volume change from crystalline olivine to amorphous silica,

on a per mole basis, is approximately 51%. Although volumetric expansion mostly

likely occurs during the formation of the active layer, we cannot constrain the extent.

Therefore, the overall mass balance is calculated on a per mol basis so the potential

volume change does not impact the model results. Our calculation of VAL based on an

155

active layer thickness of 20 nm is consistent with a volume increase of about 30%

based on the HR-TEM results. Active layer thickness is provided hereafter only as a

guide.

Once the surface silica sites are formed, the dissolution of silica can be treated

as a reversible reaction:

(2)

Unlike exchange reaction (1) above, removal of silica is largely confined to the

surface of the active layer, Fo A, rather than VAL (Fig. A1.3B). This spatial constraint

is required to reproduce the observed non-stoichiometric dissolution and to allow for a

steady state active layer thickness to emerge. Mathematically, the active layer can be

viewed as a reaction front that moves inward at a rate controlled by both the rate of

Mg exchange according to reaction (1) and the net release of Si via reaction (2).

Closed-system experiments, such as those reported here, show a plateau in Si

concentrations near SiO2(am) saturation, while Mg continues to increase, supporting

the presence of amorphous silica precipitates. Precipitation of SiO2(am) can occur

directly on the mineral surface or in other parts of the reaction vessel as shown by

reaction (4):

H4SiO4 aq( )¾®¾¬¾¾ > SiO2 + 2H2O (3)

This local equilibrium controls the aqueous Si (i.e. H4SiO4(aq)) at later stages of the

experiments once SiO2(am) saturation is exceeded (e.g., Fig. A1.1).

Reactions (1) through (3), combined with the conceptual model of Fig. A1.3

emphasize the coupled reactions that occur during the initial and steady-state periods

of olivine dissolution. The rate of reaction (1) and the net rate of reaction (2) can be

considered to control the dissolution rate of olivine, while reaction (3) represents an

indirect control on both the rates of reactions (1) and (2) at greater extents of reaction

progress as it determines the aqueous Si concentrations once amorphous silica

saturation is reached. Although previous models have considered such coupling

(Pokrovsky and Schott, 2000b), the spatial relationships between the reactions have

not been explicitly accounted for. We hypothesize that the spatial relationship between

the reactions explains the majority of the dissolution behavior outlined above.

> SiO2 + 2H2O¾®¾¬¾¾ H4SiO4 aq( )

156

A1.4.2.2 Rate equations and inclusion of isotopes as additional constraints

Similar to the assumptions commonly made to describe mineral dissolution

rates, most previous surface isotope exchange models assume the surface layer

composition is at steady state (DePaolo, 2011; Nielsen et al., 2012). Here, the

development of the active layer results in a surface layer multiple unit cells thick that

is evolving isotopically and compositionally. Such transient behavior is difficult to

solve for analytically. Thus, we use a numerical model to track the fluid and solid

compositions over time given the coupling among reactions (1), (2) and (3) enforced

by the spatial constraints and the kinetic framework presented below. The approach is

conceptually similar to that of Brantley et al. (2004) and Wiederhold et al. (2006).

However, previous studies were not able to precisely constrain the size of the active

layer, or did not require it.

In order to develop a kinetic model for the reactions (1), (2) and (3), that

includes a provision for kinetic fractionation of Mg isotopes during the early stages of

dissolution, we used a set of relationships that are based on the “ion-by-ion” growth

model developed for crystal growth and applied to calcite precipitation in Nielsen et

al. (2013; 2012). In this approach, the olivine dissolution rate is described by the net

rate Rnet, which is the difference between the ion fluxes from (Rb) and to (Rf) and the

surface, where the subscript b refers to the backward or dissolution reaction and

subscript f refers to the forward or precipitation reaction (DePaolo, 2011). As reaction

(1) is treated as irreversible, the flux of Mg is only characterized by Rb, providing an

opportunity to quantify both Rb and the associated kinetic isotope effect. In contrast,

reactions (2) and (3) are assumed to be reversible and thus only the net Si release is

observable.

The isotope-specific Mg exchange rate (RMg,, mol/s) from the active layer

associated with reaction (1) is a function of the rate coefficient for Mg exchange, Mg

(s-1

) and the concentration, Pi (mol/m3) of a given isotope or solid component, i, in the

surface layer:

ALMg

n

HMgMg VPaR 2424 (4)

The dependence of Mg exchange rate on pH is expressed via a dependence on the

157

proton activity (aH+n), where n is between 0 and 0.5 (Pokrovsky and Schott, 2000a;

Rimstidt et al., 2012). The value of n is difficult to assess because of the variable

mechanisms for proton uptake, so we used the value 0.37 suggested by Rimstidt et al.

(2012) based on synthesis of a large number of experimental studies. Similarly, for the

minor isotope the rate equation can be written in terms of the common isotope using

the kinetic fractionation factor between Mg2+

in olivine and in solution (Mg-Fo), to

describe the preferential removal of 24

Mg:

ALMg

n

HMgFoMgMg VPaR 2626 (5)

The exchange rate coefficient, Mg, along with Mg-Fo constitute the unknowns in the

rate equations. Equation (1) is used to represent the stoichiometry for mass balance

purposes. Although we track the individual rates, VAL is originally determined based

on the molar volume of olivine, and hence it is equivalent to calculating the rates in

terms of mole fraction and the number of original moles of olivine in the active layer.

Thus, any positive volume change associated with reaction (2) does not impact our

mass balance results.

Although the isotopes of Mg are not required to model olivine dissolution

using our approach, they provide a constraint on the rate of reaction (1). The model

approach we present may also be useful for considering other kinetic isotopes effects

(e.g., Pearce et al., 2012). However, to model isotopic fractionation introduces

additional calculations. First, we calculate PMg24 initially as a function of the mole

fraction of Mg that is 24

Mg, XMg24, and the stoichiometric Mg:Si ratio in olivine, XMg/Fo

(1.84 for the olivine considered here):

1

/2424 )(

mFoMgMgMg VXXinitialP (6)

An analogous equation describes PMg26. As the surface layer evolves, PMg,i is tracked

according to the individual reaction rates. In addition to the coupling between Mg and

Si associated with reaction (1), the removal of >SiO2 sites allows the reaction front to

migrate inward, supplying Mg to the active layer. Thus, PMg,i is not only a function of

the magnesium release rate but also the net rate of reaction (2). To describe the net

rate of silica release (R>SiO2) from the active layer associated with reaction (2), we

assume that the backward (detachment) rate is a function of the concentration of

158

>SiO2 at the surface only, while the forward (attachment) rate is a function both >SiO2

and the aqueous Si activity, [H4SiO4]:

mFoSiOSiOSiOSiOSiO AVPSiOHkPR 2442222 (7)

where SiO2 (s-1

) is the surface detachment rate and P>SiO2 is the concentration of Si

surface sites throughout VAL and k>SiO2 (M-1

s-1

) is the rate constant associated with

attachment of SiO2 at the surface. The key difference between equation (7) and

equations (4) and (5) is that the thickness of the surface layer is not included in this

rate expression because we assume that the attachment and detachment of Si can only

occur from the surface and not the entire volume of the active layer (i.e. h = 1). This

treatment allows for incongruent dissolution during the active layer formation, and

maintains a constant active layer thickness as suggested by HR-TEM analyses.

Equation (7) is computed for the Si associated with each Mg isotope. Initially P>SiO2 is

assumed to be zero, and is sequentially updated based on the rates from equations (4),

(5), (6) and (7).

The rate of new silica precipitation is described according to the equilibrium

constant for SiO2(am), or KSiO2, and the precipitation rate kSiO2 (mol m-2 s-1):

1

2

44

2)(2

SiO

SiOamSiOK

SiOHAkR (8)

To calculate both the non-steady state evolution of the surface layer, and the spatial

relationship between the ion-specific reactions, we couple the rate formulations above

to the active layer concentrations (Pi) according to:

ALFoMgMgSiOMg

MgVXXRR

dt

dP//24224

24

(9)

ALFoMgMgSiOMg

MgVXXRR

dt

dP//26226

26

(10)

ALSiOFoMgMgMg

SiO VRXRRdt

dP// 2/2624

2

(11)

In equations (9) and (10) the concentration of Mg in the active layer is determined by

the balance between the rate of Mg exchange and the detachment rate of >SiO2, as

required to maintain the constant VAL suggested by HR-TEM characterization.

159

Similarly, the concentration of >SiO2 is controlled by the difference between the rate

of Mg exchange, which generates >SiO2, and the net removal of >SiO2 from the

active layer. These equations emphasize the coupling between the Mg and Si removal

rates and the distribution of Mg and Si in the altered layer.

The corresponding active layer Mg/Si (Mg/SiAL) can be calculated from:

(12)

This approach uniquely allows us to track the Mg/Si and 26

Mg in the active layer and

the fluid without assuming a steady-state surface composition.

The coupled set of equations represented by equations (1) through (12),

combined with the constraints on the active layer provided by isotopic data, HR-TEM

analyses, and time-resolved solution compositions, results in the following adjustable

parameters that are fit using the experimental data (1) Mg (and Mg, which depends on

Mg), and (2) SiO2 and k>SiO2, which determine R>SiO2. The value of kSiO2 cannot be

precisely determined because we do not know the surface area associated with

SiO2(am) precipitation, although the long-term steady-state Si concentrations provide

a useful constraint on the overall rate.

A1.4.3 Application of model to experimental data

To model the closed-system experimental data of Chapters 2 and 3, we use a

forward model of the coupled set of reactions/equations (1)-(12) using the reactor

volume, the initial mass of olivine, homogenous stoichiometric olivine with Mg/Si of

1.84, and the measured BET surface area as initial conditions (see Table A1.3 for

parameter values and sources). We do not consider aqueous or solid state diffusion.

Alkalinity is calculated based on the Mg release rate and is used to solve for pH

according to “apparent” equilibrium constants for CO2 solubility and carbonate

speciation in the presence or absence of 0.5 M NaCl and at appropriate temperature

and pressures. Equilibrium constants are determined using the approach of Duan and

Sun (2003). We also assume unit activity coefficients for aqueous species.

Mg

Si AL(t) = PMg( ) t( ) / PMg t( ) / XMg/Fo( ) + P>SiO2 t( )é

ëùû.

160

Because the early release rates of both Mg and Si are controlled by the rate of

reaction (1), Mg was adjusted to match the early (< ~2 to 3 days) experimental Mg

and Si profiles. Then, because the net removal of >SiO2 according to reaction (2)

controls the supply of the Mg to the active layer via equations (9) and (10), R>SiO2 is an

additional control on Mg concentrations at steady state. As Si concentrations plateau

once the active layer is formed due to SiO2(am) precipitation, the early SiO2 and long-

term Mg profiles constrain the net >SiO2 dissolution rate. Accordingly, the rate was

adjusted to match the long-term Mg profile by varying the ratio of SiO2 to k>SiO2. The

model fit to experiments 1 and 2 is considered the “reference model” hereafter, with

parameters provided in Table A1.4. The reference model was then adjusted to fit the

additional experimental data following the above procedure.

The model is able to reproduce the major features of the data from experiments

1- 4, including the initial incongruent dissolution (Fig. A1.4). The Mg/Si in the active

layer evolves from 1.84 to 0.5 after 5 days (the isotopic and surface layer evolution

Table A1.3: Model parameters and values applied to experiments 1-4, 2R, 19S, 2S, 19S.

Parameter Description Units Value or range

Vm Molar volume m3 mol-1 4.38 x 10-5

Fo Site density mol m-2 layer-1 3.3 x 10-5 a

h Number of layers --- 14b

A Surface area m2 2.24c/2.0d

VAL Active layer volume

=FoA hVm

m3 calculated

RMg,i Mg isotope release rate mol s-1 calculated

R>SiO2 Net SiO2 release rate mol s-1 calculated

RSiO2(am) Precipitation rate mol s-1 calculated

Mg Exchange rate coefficient for

Mg

s-1 variable

SiO2 Detachment rate coefficient for

>SiO2

s-1 variable

k>SiO2 Attachment rate coefficient for >SiO2

M-1s-1 variable

kSiO2 Rate coefficient for SiO2(am) mol m-2 s-1 variable

XMg/Fo Mole fraction Mg in olivine 1.84c

XMg,i Mole fraction of i in Mg

component

calculated

Mg-Fo Kinetic fractionation factor --- variable

PMg26, PMg24 Concentration in VAL mol m-3 calculated

P>SiO2 Concentration of >SiO2 in VAL mol m-3 calculated

KSiO2 Equilibrium constant for

SiO2(am)

--- 10-2.4067e

161

will be discussed in more detail in a subsequent section). Relative to experiments 1

and 2, the early Mg release rate in the electrolyte-free experiments 3 and 4 was more

rapid, followed by slower long-term rates. To fit the data requires an increase in Mg

by a factor of 3 and a decrease in R>SiO2 by a factor of 4.5. Although we cannot

determine uniquely whether the later decrease was associated with the attachment or

detachment rate of >SiO2, to account for the lower Si concentrations appears to

require an increase in k>SiO2 by a factor of 50 because increasing k>SiO2 more strongly

impacts the steady-state Mg release rate, while decreasing >SiO2 impacts both early

and steady-state Mg and Si rates (cf. Fig. A1.1). The Mg isotopes also place

constraints on Mg as discussed in section 4.4. However, the rapid increase in Mg

concentrations appears to require an increase in the thickness of the active layer (AL)

relative to the experiments that contained a supporting electrolyte (Fig. A1.4C and D).

These changes in rate coefficients result in a decrease in the overall olivine dissolution

rate from 10-13.1

to 10-13.75

mol/cm2/sec between the reference model and the

corresponding model for experiments 3 and 4 (Table A1.4). The rate constant for

SiO2(am) precipitation of 3.3 x 10-9

mol/m2/sec, using the olivine surface area, is also

in agreement with previously published values at neutral pH (3.1 x 10-9

mol/m2/sec at

60˚C (Rimstidt and Barnes, 1980)).

The decrease in R>SiO2 in the absence of an electrolyte is consistent with the

observed decrease in rates of SiO2(am) dissolution with decreasing electrolyte

concentration (Icenhower and Dove, 2000). As noted in Chapter 2, the solubility of

silica may also be impacted by the absence of a supporting electrolyte. Explaining the

increase in the Mg rate is more difficult. The enhanced exchange of Mg in the absence

of an electrolyte is surprising as sodium is thought to modify the nucleophilic

properties of water (Icenhower and Dove, 2000), and a reduction in ionic strength

generally results in an increase in the thickness of the electrical double layer (Brown

and Parks, 2000). It is possible that the high concentrations of Na+ may interfere with

with proton exchange. The more rapid Mg exchange rate also generates more

depletion of Mg in the active layer leading to model Mg/Si of 0.05 in experiments 3

and 4, compared to 0.5 in experiments 1 and 2. Thus, the lower R>SiO2 and increase in

162

>SiO2 concentration in the active layer associated with more rapid Mg exchange

create a feedback that reduces the long-term net dissolution rate substantially, despite

the lower pH in these experiments. To determine the precise nature of the dependence

of Mg and >SiO2 on supporting electrolyte concentration would require a broader

range of experimental conditions.

Experiments 2S, 2R, 19S and 19R, conducted with larger olivine grains, show

Figure A1.4. Model fit to experiments 1-4. Magnesium (open symbols) and Si (closed symbols)

over the full experimental duration are shown in (A), and during the initial incongruent

dissolution phase in (B). The model fit to the combination of experiments 1 and 2 in (A) is

considered the reference model. The same scheme is applied in (C) and (D) where model results

for experiments 3 and 4 are presented. The changes in rate coefficients are indicated and the

thickness of the active layer (AL, nm) is indicated. For experiments 3 and 4, a sensitivity analysis

showing variation in the AL is provided. All experiments were conducted at 100 bar CO2 and

60˚C in the presence of 0.5 M NaCl (Chapter 2) .

163

similar behavior and are well described by the model after adjustment of some rate

parameters (Fig. A1.5). For experiments 2R and 19R, the data are best fit with a Mg

that is a factor of 3 greater than in the reference model but within the uncertainty,

while R>SiO2 and the associated Si rate parameters remained consistent with the

reference model. Overall rates are comparable to those determined for experiments 1

and 2. In contrast, for the poorly mixed experiments (2S and 19S), both Mg and

R>SiO2 are slower by a factor of 6 and 10, respectively, compared to the well-mixed

experiments. The experiments also yield net dissolution rates that are nearly an order

of magnitude slower than those determined for the rocking experiments. This

difference in rate may reflect chemical gradients that decrease both transport of H+ to

Figure A1.5. Model fit to the combined experiments 2R and 19R (well mixed) are shown

over the full experimental duration (A), and during the initial incongruent dissolution phase

in (B). Model fit to experiments for 2S and 19S (not-well mixed) over the same durations are

shown in (B) and (C). The changes in rate coefficients relative to the reference model are

indicated. All experiments were conducted at 100 bar and 60˚C in the presence of 0.5 M

NaCl (Chapter 3).

164

the surface and transport of SiO2 away from the surface, and are not captured using the

bulk solution properties. Under these conditions, the calculated rates are effective rates

that include transport effects. The data and modeling approach presented here do not

allow us to constrain the full dynamics of transport effects (e.g., Li and Steefel, 2000;

DePaolo, 2011). More discussion of diffusion limitation is provided in Chapter 3.

A1.4.3.1 Overall dissolution rates and comparison to previous studies

The model rate profiles for net Mg and Si release (i.e. R>SiO2 – RSiO2) are shown

as a function of time, pH, and H4SiO4 in Fig. A1.6 for experiments 1 and 2. Early in

the experiments, Mg release rates are substantially greater than Si because the rate of

Si dissolution requires formation of >SiO2 sites via the Mg exchange reaction. The

rapid early increase in >SiO2 from the start of the experiment to approximately 1 day

occurs because P>SiO2 increases more quickly than aqueous SiO2 concentraitons, where

the later controls the attachment rate. Because of the feedback between Mg release,

the creation of >SiO2 in the active layer and aqueous Si concentrations, the rates

eventually stabilize at a steady state characterized by stoichiometric dissolution, with

rates in agreement with those calculated from a linear fit to the data in Chapter 2.

Although there is a weak dependence on pH incorporated into the model, the

relationship between rates and pH in Fig. A1.6 is partly an artifacy of the correlation

between reaction progress and pH (Fig. A1.1). Experimental studies under flow-

through conditions generally observe that the overall rate of olivine dissolution

decreases with increasing pH, suggesting that Si concentrations in these experiments

were sufficiently low that Mg release rates have a stronger effect on the net dissolution

rate. As discussed in Chapter 2, a correlation between rate and pH is not observed in

the experiments presented here, likely because at late stages (after several days) the

net dissolution rate is controlled by both R>SiO2 and RMg.

Flow-through and closed-system experiments have shown an inverse

correlation between the aqueous Si concentration and both Mg and net dissolution

rates. For olivine, the breaking of Si-O bonds at low pH is typically designated as the

rate limiting reaction. Our modeling results suggest that the overall dependence of the

rate on Mg and Si dynamics is complex (Fig. A1.7). During the formation of the

165

active layer, the Mg release rate initially controls the Si release rate. Once the active

layer is established, then the net destruction of >SiO2 becomes more important, such

that R>SiO2 determines both the Mg release rate and the steady-state dissolution rate at

high degrees of Mg depletion in the surface layer, or efficient Mg exchange (e.g., Figs.

A1.4A compared to Fig. A1.4C). At lower Mg exchange rates, such as observed in

the electrolyte-free experiments, Mg exchange continues to moderate the overall

dissolution rate by regulating the re-polymerization of silica.

Figure A1.6. Rate profiles as a function of (A) time; (B) pH; and (C) H4SiO4

concentrations for the reference model. The bar at top indicates the dominant

processes occurring from initial to steady-state dissolution.

166

The assignment of single reactions as rate limiting thus appears to be of limited

utility, even for a relatively simple silicate such as olivine. The spatially resolved

surface kinetic description affords an alternative insight into how the kinetics of the

various reactions and the solution stoichiometry control the overall rate. One key

assumption of the model, that appears to be supported by the elemental and isotopic

data, as well as the TEM analysis, is the presence of an active layer. Conceptually, this

may consist of several layers of altered material where solid-state diffusion of Mg and

H+ are rapid enough to maintain the rates observed (Chapter 3), or alternatively, for

other minerals it may represent kink sites and other surface defects that allow for

depletion of one element over the other in excess of what is allowed by the BET

surface area and one monolayer of mineral. Regardless of the exact mechanism, the

coupling imposed by reactions (1), (2), and (3) exerts a strong control on the overall

rate. This is shown conceptually by individually varying the individual rate constants

and running the model to steady-state rates (Fig. A1.7). As Mg increases, the

sensitivity of the overall dissolution rate to the Mg exchange rate decreases. This is

because at high Mg, the supply of Mg to the active layer, where it can exchange with

two H+, is determined by the removal of >SiO2. Thus, there is a stronger positive

relationship between SiO2 and the overall dissolution rate, and the inverse is true for

k>SiO2. The initiation of a plateau in the overall rate at high SiO2 is presumably

because Mg exchange eventually becomes limiting. Thus, under flow-through

conditions where H4SiO4 is continually removed, the >SiO2 attachment rate may

become so small that the overall rate depends more strongly on Mg. Finally the

dependence of the overall rate on kSiO2 is weaker, but occurs because net SiO2(am)

precipitation impacts R>SiO2 by controlling the attachment rate of >SiO2 once

SiO2(am) saturation is reached.

A1.4.3.2 Consequences of spatial discretization and implications for rate coefficients

The determination of all kinetic parameters is subject to assumptions made

regarding the reactive surface area, and other factors that contribute to the observed

overall rate (e.g., the dependence of overall rate on pH, reaction affinity and ionic

167

strength). Here, the observed Mg release rate was reproduced according to the values

assigned to represent the VAL, Mg and PMg (which is partly a function of R>SiO2). As

noted previously, the HR-TEM profiles of Chapter 3 show remarkable complexity,

including a zone of Mg-depleted crystalline olivine 80-100 nm thick adjacent to the

active layer in the mixed experiments, and approximately 10-20 nm thick in poorly

mixed experiments. In contrast, the boundary conditions in the model assume that

stoichiometric olivine was supplied to the active layer as >SiO2 was removed from the

surface. This assumption was necessary to avoid solving explicitly for solid-state

diffusion. Below we qualitatively describe the uncertainty arising from this

assumption. In addition, we find that the rate coefficients differ in the presence or

absence of a supporting electrolyte. As a consequence, the rate parameters provided in

Table A1.4 should be considered “effective” rate coefficients applicable to the

specific experimental conditions.

Although the model reproduces the solution composition convincingly, we

further evaluate the solid phase mass balance because the solid phase stoichiometry is

coupled to the rate coefficients via equations (9)-(11). In order to calculate the

maximum amount of Mg removal from the HR-TEM profiles, we assume constant

volume replacement and that Si is conservative throughout the altered layers (cf. Fig.

Figure A1.7. Sensitivity of the steady-state dissolution rate to the individual rate coefficients. Each

rate coefficient was varied independently while the others were held constant at the values

determined for the reference model (see Table 4). The best fit to experiments 1 and 2 is shown by the

grey bar.

168

A1.3C). The resulting difference between the HR-TEM and the model is -24% and

12% for 19R and 19S respectively, which is reasonable given that the HR-TEM

calculations represent a maximum estimate of Mg depletion. The consequence of

preserving the mass balance through averaging the active layer concentration is that

the value of PMg is artificially low (and P>SiO2 high) and concentration gradients are

not honored. The rate of Mg exchange also differs between the Mg-depleted olivine

and the active layer. These underlying assumptions are embedded in the effective rate

coefficients. However, effective rate coefficients can still be useful if they capture the

key processes: the model successfully reproduces both the widely observed initial

incongruent dissolution and steady-state dissolution, as well as the formation of

altered surface layers. For olivine, given that most of the Mg depletion occurs within

the active layer, where Mg/Si ratios drop from ca. 1.5 to 0.2 over approximately 30

nm, our treatment of only the active layer appears reasonable. However, more studies

that combine HR-TEM constraints on composition and crystallinity of the surface as a

function of depth, combined with spatially resolved models that account for solid-state

interdiffusion (e.g., Yang et al., 2009), may yield further insights into the importance

of the Mg-depleted crystalline zone for both the evolution of the active layer and

overall dissolution kinetics.

A1.4.4. Isotopic fractionation and surface layer evolution during dissolution

The rapid increase in dissolved Mg relative to Si observed in the early stages

of the experiment is accomplished in the model through the creation of a Si-rich and

Mg-depleted active layer as indicated by HR-TEM analyses (Chapter 3). Figure

A1.8A shows the modeled change in Mg/Si of the active layer (Mg/SiAL) from

stoichiometric values of 1.84 to steady-state values of approximately 0.05. For

comparison, in experiments 1 and 2, with more rapid net dissolution rates but lower

Mg exchange rates, the Mg/SiAL is much higher and stabilizes at values closer to 0.3.

169

The 26

Mg of the active layer (26

MgAL) and dissolved Mg evolve in unison.

Values of Mg-Fo of between 0.9995 – 0.999 are consistent with the observed isotopic

variation in the dissolved Mg (Fig. A1.8B). In comparison to the dissolved Mg

profiles, the model 26

Mg of the surface layer is complex. During the initial stages of

reaction, Mg release is most rapid as indicated by the rapid decrease in Mg/Si and

corresponding increase in dissolved Mg concentration. Subtle variation in 26

MgAL

evident around 4 days when the Mg/Si depletion reaches steady state. Due to the

initially high Mg exchange rate, a maximum in R>SiO2 also occurs coincident with the

26

Mg maximum because P>SiO2 increases more quickly than aqueous SiO2

concentrations, where the later controls the attachment rate. This results in the early

enrichment of 26

Mg of the active layer. As the rate of Mg release decreases, an

increased supply of Mg to the active layer from the bulk crystal reduces the 26

MgAL

until eventually a steady-state balance develops between the net release of >SiO2 and

the supply of Mg. The slight drop in the 26

MgAL after 4 days is thus associated with

the attainment of a lower steady-state R>SiO2. Once steady-state dissolution is reached,

the dissolved Mg supplied to solution has the isotopic composition of the crystalline

olivine and the fractionation is no longer preserved in the fluid. In contrast, the surface

Figure A1.8. Model magnesium isotopic and surface layer Mg/Si evolution for experiment

3. (A) The model change in the Mg/Si of the active layer (Mg/SiAL) is shown in comparison

to the 26Mg of the active layer (AL) and the dissolved Mg. (B) Comparison between

model and measured 26Mg of the aqueous Mg (uncertainties are represented as 1 s.d.). The

best fit to the data is between Mg-Fo = 0.9995 and 0.9990 and variations in Mg-Fo are shown

for reference.

170

remains permanently enriched in 26

Mg.

Although the limited data in this study preclude full evaluation of the Mg

isotope systematics, the model suggests the isotopic composition of dissolved Mg

under closed system conditions is much more sensitive to variations in vMg compared

to variations in VAL, whereas the dissolved Mg responds identically to both. In

addition, because the early release rate of Mg determines the isotopic fractionation, the

isotopes are not appreciably sensitive to the value of SiO2. The sensitivity of the

isotopes to only one model parameter suggests that isotopic fractionation could

provide a useful tool for constraining individual ion exchange rates, even in the

absence of HR-TEM constraints. We also assume that no secondary processes such as

sorption influence the dissolved isotopic composition. As Mg would likely form weak

outer sphere complexes with amorphous silica resulting in negligible fractionation,

Figure A1.9. Model evaluation of Wimpenny et al. (2010) experimental series FO2 at

pH 3 and 25 ˚C. (A) Model fit for Mg and Si concentrations (see parameters in Table

4), (B) Comparison between measured 26Mg to model prediction using Mg-Fo = 0.999.

171

and we observe no other secondary phases in experimental products (Chapters 2, 3),

this assumption appears reasonable.

The experiments were also conducted only under closed-system conditions

where concentrations evolve with time. To explore the ability of the model to

reproduce observed Mg, Si and 26

Mg evolution under flow-through conditions, we

applied the model to data of Wimpenny et al. (2010) using their experimental

conditions and reported parameters. In the absence of HR-TEM constraints, we

assume an active layer thickness of 20-40 nm (an active layer greater than 12 nm is

required to reproduce the observed features). The model suggests a transient period of

dissolution in the early stages (<0.5 days) followed by attainment of steady-state

release (Fig. A1.9). A similar pattern is observed when the experimental pH was

subsequently lowered to 2 in the reactor, although we did not model this case because

of the uncertainty introduced by the previous experimental conditions. The model is

also consistent with the observed 26

Mg, although given the limited information and

number of measurements, the long-term behavior (i.e. attainment of bulk olivine

26

Mg values) and the value of Mg-Fo cannot be precisely constrained. Relative to the

closed-system experiments, the flow- through experiments are highly sensitive to the

Mg exchange rate and much less sensitive to the Si attachment and detachment

kinetics, as suggested in the earlier rate profile analysis (Fig. A1.9A and C).

It is likely that the kinetic isotope fractionation observed and modeled here

occurs during the dissolution of many minerals, although it may not be observable

under all conditions. However if several layers are active, then an isotopically depleted

layer may be maintained indefinitely on mineral surfaces. The slower the preferential

release rate of the element is relative to the migration of the active layer, the more

strongly the fractionation will be expressed within the mineral surface.

A1.5. Conclusions

Descriptive models of silicate mineral dissolution must be balanced against

their utility for describing complex multi-component open systems. Kinetic models for

silicate mineral dissolution have been largely based on a simplified version of

172

Transition State Theory (TST), where the overall dissolution rate is equal to the

product of the kinetic rate constant, surface area, the reaction affinity, and the activity

of ions that inhibit or accelerate dissolution. For complex silicate minerals, such as

olivine and many other major rock-forming minerals, the application of a single

kinetic rate constant and reaction affinity may not be appropriate if spatial constraints,

such as the formation of an active layer, determine the overall dissolution rate.

The model approach used here also suggests that no single reaction is rate

limiting, but rather the relationships between various components, over space and

time, determine the overall dissolution rate. For isolated SiO4 tetrahedra of olivine,

technically no Si-O bond has to be broken for the crystal structure to be disrupted.

Nevertheless, the dissolution of repolymerized SiO4 tetrahedra regulates the supply of

Mg to the active layer. Concurrently, the net exchange of Mg for protons controls the

rate of re-polymerization of tetrahedral SiO4, leading to net mineral dissolution. The

interdependency of these processes appears to explain the order of magnitude variation

in overall dissolution rates we observed and modeled. The possibility that similar

processes may occur in other silicate minerals is supported by the observation of

kinetic isotope effects during the dissolution of amphiboles and micas; however in

such cases the inter-relationship among individual components may be more complex.

The approach presented here represents a model of moderate complexity that

affords an evaluation of the coupling between the fluxes of individual ions and the

overall dissolution rate of olivine. Such an approach may be advantageous in

extracting rates from experimental data, as an interpretive tool for probing the

interconnection between key reactions. Although parameterizing the rate equations

does require more information, the approach presented here could still provide an

alternative rate law for geochemical and reactive transport models applicable at the

continuum scale (e.g., Druhan et al., 2013). Ideally, such approaches might ultimately

replace the simplified versions of net TST rate laws commonly used, leading to

improved models of mineral-fluid interactions across a range of geological

environments.

173

A1.6. Acknowledgments

We acknowledge the Global Climate and Energy Project (GCEP-48942) at

Stanford University for funding the work presented here. We are grateful to the Earth

Surface Geochemistry group at GFZ Potsdam for comments and discussions that

greatly improved the manuscript. We also acknowledge the staff of the Stanford

ICPMS, Environmental Measurements-1 and the Nanocharacterization Laboratories.

174

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179

Appendix 2: Experimental Protocols

A2.1 Gold Bag Preparation

1. Check bag for leaks: Assemble gold bag with titanium collar, titanium head

with the sampling valve attached, washer, and flanged compression cap containing

thrust bolts (Fig. A2.1). Tighten the bolts, a little at a time, alternating bolts to ensure

an even seal. Place the assembled bag in a large beaker full of water and pressurize

using the house air line. Look for bubbles leaving the bag. If bubbles are escaping

from a hole in the gold itself, the hole will need to be welded (see Section A2.2

Repairing Gold Bags). Mark the tear now by drawing a small circle around the tear

with a permanent marker. If bubbles are escaping from the collar/head seal, see

Section A2.3 Improving the seal between Au bag and Ti collar. If the bag is mostly

collapsed, filling it with air may cause a tear in the gold. You can reduce the chance of

this happening by pre-heating the assembled bag in the furnace for a few minutes (see

step 8 for instructions) to soften the gold.

2. Nitric acid wash: If bag does not leak, it is ready to be cleaned. Place the bag

in a glass beaker surrounded by DI water, and place the beaker on the hotplate in the

hood. Plug in the hot plate and set the temperature to 180 °C. Pour 25-50% trace metal

grade nitric acid into the gold bag, filling it to just below the top of the gold. The Ti

head and Ti-Au filter should also be washed in nitric acid; pour 2 cm of nitric acid into

a small glass beaker on the hot plate, then add the filter and head. Let all three (bag,

Figure A2.1: Gold bag

assembly. From left to

right: gold bag with Ti

collar, Au/Ti filter in Ti

head with attached

sampling tube, washer,

flanged compression cap

containing thrust bolts.

180

filter, and head) sit in hot nitric acid for about 30 minutes, label the fume hood with

"Nitric Acid" and the % concentration. The purpose of this step is to oxidize any

residual material inside the bag.

3. Rinse: After 30 the nitric acid wash, pour the acid back into the labeled

bottle. The DI water that was outside the bag can be poured down the sink (you are

confident that the gold bag is intact, because you tested it in step 1). Rinse the head

and filter, set both aside to dry. Rinse the gold bag, inside and outside VERY well and

change gloves before the next step.

4. Hydrochloric acid wash:. Place the gold bag back in the tall beaker with

fresh DI water and put the beaker on the hotplate, set the temperature to 150 °C. Pour

HCl (25-50%) into the gold bag, ensuring that the level stays 1 cm below the Au-Ti

interface. Let the bag sit for 30 minutes, but ensure that the acid does not boil (the

vapor will corrode the Ti collar). A few important notes: (1) Mixing HCl and HNO3

makes aqua regia, which dissolves gold, and (2) HCl is corrosive to titanium, so Ti

parts cannot be cleaned with HCl.

5. Rinse: repeat Step 3. If the bag was previously exposed to SiO2, go to step

6. Otherwise skip to 8.

6. HF wash: If the bag has been exposed to precipitating amorphous silica, you

need to dissolve the silica using dilute hydrofluoric acid. There may be a 1% HF in

50% nitric acid solution in the fume hood, if not you'll need to make one using

concentrated HF (in the blue cabinet) and nitric acid. Also, HF is consumed by

dissolving silica (4HF + SiO2 = SiH4 + 2H2O) and silicon tetrafluoride volatilizes

rapidly. Thus, a HF/Nitric acid solution will eventually lose its ability to dissolve

silica. HF is corrosive to both glass and Ti, so secondary containment must be teflon.

Do not put HF in a gold bag unless you are absolutely sure that there are no holes in

the gold. Once you have teflon secondary containment and a intact gold bag set up,

wash with the HF/Nitric solution the same way you completed the other washes.

Minimize contact between HF and Ti, but if there is precipitated SiO2 on a Ti part that

you can't scrape off, a brief HF wash is acceptable. Working with HF is very

hazardous. Appropriate personal protective gear must be worn, including gloves, face

181

protection, and a lab coat. Contact with skin or inhalation can result in very severe and

permanent consequences. Calcium glutamate (used to treat HF burns) is located in the

lab fridge. Obtain proper training before working with concentrated HF.

7. Rinse (see step 3).

8. Bake-out: This step is particularly important if you did a HF wash, as HF

dissolves the TiO2 coating on the titanium pieces, exposing raw Ti metal, which may

act as a catalyst for some reactions. Set the furnace in the rocker room to 420 °C (See

section A2.7.1 Using the Furnace) and place the assembled bag inside the furnace. Lay

the assembled bag diagonally so that the Ti tube fits inside the furnace. Ensure that no

metal from the bag is touching the heating coils in the furnace as this could cause a

short circuit. Close the door and let bake for at least 12 hours (24+ is best).

9. Final tightening: Before loading the reactants, it's a good idea to tighten the

center tube where it joins the head, since this bolt tends to loosen and is a major source

of leaks. Disassemble the gold bag and wrap the head with 3-4 kimwipes. Place the

wrapped head into the inside of a glove, then place in the small vice in the rocker

room. The purpose of the kimwipes and glove is to protect the head from scratches

imposed by the vice, which can permanently destroy the head. Once the head is held

by the vice, tighten the bolt at the base of the tube (clockwise) as much as possible.

Reassemble the gold bag and test one more time in the beaker with DI water and the

house air line.

A2.2 Repairing Gold Bags

1. Cleaning: If the gold bag has a tear, it will need to be fixed by welding a

small piece of gold onto the tear. In order for the patch to stick, both the bag and the

small gold piece must be very clean. The cleaning procedure mostly follows steps 2-5

of Section A2.1 Gold Bag Preparation, with the only difference being that the bag

must be cleaned inside and out. That means that for each acid wash, the bag should be

placed in a beaker of acid and then filled with acid to slightly above the level of the

tear. Again, it is very important to not mix nitric acid and HCl when cleaning the bag.

Also, the nitric acid wash must be done first, followed by a rinse, followed by the HCl

wash.

182

2. Preparing to weld: For gold, use the acetylene torch next to the workbench

with the valves. The torch has two tubes coming out of it, one goes to the oxygen tank

(green) and the other goes to the acetylene tank (red). The torch is quite bright, wear

the dark green glasses to protect your eyes (usually located on top of the red tool

cabinet). Also, tie back hair and loose clothing. Turn both tanks on, then open the

acetylene valve on the torch very slightly. Light the torch using a sparker or a lighter.

A yellow flame will appear. Slowly open the oxygen valve on the torch until the flame

turns white/blue. Too much oxygen will cause the flame to go out, but the more

oxygen you have, the hotter the flame will be. Start with a cool flame- you can always

add more heat. You can leave the lit torch in a vice attached to the lab bench for short

periods of time when you are at the bench, but if you leave the bench, turn the torch

off by first turning off the oxygen, then the acetylene.

3. Welding: Place the disassembled gold bag on the stone heat sink and make a

slight indent at the tear using your thumb. Place the small gold ball directly on top of

the tear, then direct the torch at the ball. You will see the ball heat up and start to

glow, then it will suddenly cool (after making conductive bond with the bag, allowing

heat to dissipate). Continue to heat the small ball, carefully. Eventually, it will glow,

and then suddenly melt. At that point, withdraw the heat. It may look like a very large

hole initially, but (hopefully) it's just a very smooth, reflective weld.

4. Testing: The bag will be very hot at this point, so do not attempt to move it

without using heat gloves. Depending on the size of the tear, you may be able to test

the bag by holding the opening up to the desk lamp on the lab bench and looking for

light penetrating through the bag, but the optimal test involves reassembling the bag

and inflating it in the beaker full of DI water.

5. Repeat steps 2-4 until the tear is welded closed and no longer leaks air

bubbles in the pressure test. Then proceed with bag preparation.

A2.3 Improving the seal between Au bag and Ti collar

If you notice air escaping from the head/collar assembly during the submerged

pressure test, there are a few potential causes. I'll address them in order of ease to fix.

1. Loose bolts holding the head inside the collar. Loosen the 6 bolts on top of

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the bag assembly and then re-tighten, being sure to alternate bolts and tighten each one

a little bit at a time. Re-test.

2. Poor seal between the gold foil inside the collar and the head, part 1: Ensure

that the gold inside the collar is clean and free of debris, and that the head is also clean

and smooth. Rinsing with water and light scrubbing with a brush should be enough to

remove debris. Check for scratches on the head: horizontal ones are probably fine, but

vertical ones may be the (unfixable) culprit. Reassemble and test.

3. Loose connection between the Ti sampling tube and the head: Disassemble

the bag and take the Ti head with attached sampling tube. Wrap the head with 3-4

kimwipes and place inside a heat glove (to prevent scratches caused by the vice) and

place the head securely in the small vice attached to the lab bench in the rocker lab.

Tighten the 5/8" bolt that connects the tube to the head, it should be very tight. Do not

put the head directly in the vice without protection, the texture on the vice will dent

the head and may permanently damage it. Reassemble the bag and test again.

4. Poor seal between the gold foil inside the collar and the head, part 2:

Sometimes an extended bake-out in the furnace is sufficient to improve the seal.

Assemble the bag and place in the furnace for at least several hours, overnight is best.

Remove from furnace, let cool for about 30 minutes, then retest.

5. Poor seal between the gold foil inside the collar and the head, part 3: If the

bag has been used many times, the gold foil will become thin at the seal point and will

no longer create a seal. At this point, the only solution is to remove the collar from the

gold bag, trim off the top 2-3 cm of the bag, and put the collar back on. I've found a

screwdriver to be effective at loosening the bag from the collar, though it is an arduous

process that requires time, strength, and agility. Trimming is best done with scissors

and an even top edge will make things easier. To reinsert the bag to the collar, the bag

diameter must be reduced at the top by creating loose folds or waves in the foil. Once

the folded/waved bag is inside the collar, it can be stretched out to fit the form of the

collar. Pay attention to any sharp folds that form, those are nearly impossible to

remove later. The top of the new gold should extend at least to the slope change inside

the collar, though higher is better as you will later be pushing the gold down when you

184

reintroduce the head. Also remember that the new gold top is a thicker foil than the old

one, so inserting the head may take several iterations of pushing down (possibly

lightly pounding with a small hammer), heating to soften the gold, and manual

stretching of the gold to coat the inside of the collar. Once the bag is successfully

reassembled with the head and bolts tightened, place it in the furnace to bake for at

least overnight, but longer is better. Several days may be required to create a solid

seal, and several iterations of heating, testing, and reassembly might be necessary.

A2.4 Assembling the reactor

1. Calculate amount of reactants needed: Measure the volume of the gold bag

by taring the scale with the gold bag inside a tall beaker. Pour DI water into the bag

until the water level is at the slope change in the bag, this weight is the total mass of

water that will fit inside a sealed bag. It's safe to take that number as your volume in

cubic centimeters. To prevent the bag from bursting, set aside 20% of that volume, so

the volume you will be filling with reactants=80% of the total volume. Calculate how

much water, mineral, and gas you will be adding to the bag at this point and be sure

that the total volume <80% of the available volume (so a 100 mL bag may have 7 mL

of CO2, 70 mL of water, and 3 mL of rock). For this calculation, be sure to use your

desired rock:water and water:gas ratios. A sample calculation is below, where ρ is the

density of a substance at reaction conditions.

gaswaterrock volumevolumevolumevolumebag _*8.0

gas

gas

water

water

rock

rockmassmassmass

volumebag

_*8.0

if your water:rock ratio = 50:1 by mass, then 50

waterrock

mm

if your water:gas ratio = 10:1 by volume, then water

waterwatergas

mvv

1010

It's also a good idea to calculate the volume of CO2 that you will be adding

now, even though you won't actually add it until later. The total volume of added CO2

at reaction temperature should be less than the free volume in the bag. So if you are

185

adding 70 mL of fluid to a 100 mL bag, the total volume of CO2 at reaction

temperature should be less than 30 mL to account for the time when the CO2 is heated

to reaction temperature but not yet dissolved. See the sample calculation below.

aseseperateph

CO

dissolved

CO

tot

CO molmolmol 222

water

dissolved

CO volumeLmolsolubilitymol *)/(2

)/(_

)(_

22

molccvolumemolar

ccvolumemol

Treaction

COaseseperateph

CO

)/(_*_

2

_

2 molccvolumemolarmolvolumeTroomtot

CO

Troom

CO

)/(_*_

2

_

2 molccvolumemolarmolvolumeTreactiontot

CO

Treaction

CO

2. Add reactants: Add all solid and liquid reactants to the bag, then assemble it

(bag and collar, head with Ti/Au filter and Ti rod, washer, and flanged compression

cap) and pressure test it one more time. Be sure to record weights and/or volumes of

reactants added.

3. Attach bag to stainless steel head: When assembled, the gold bag will hang

inside the stainless steel reaction vessel from the stainless steel head. Place the

stainless steel head in the smaller vice on the lab bench and tighten securely. Brush a

small amount of nickel grease onto the Ti tube on the bag assembly about half way

along the tube and on the 5/8" bolt at the base of the tube. Push the tube through the

largest hole in the middle of the stainless steel head until the bolt contacts the bottom

of the head, tighten the bolt using a 5/8" wrench as tight as you can make it. Expect

the bench to shake a little. If this bolt is not sufficiently tight and leaks when you

pressure test the assembled apparatus, you will need to take almost everything apart to

tighten it.

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4. Load the SS pressure vessel: Place the steel pressure vessel in the larger vice

attached to the lab bench, with the opening facing up and the rod protruding down

through the base of the vice. The vessel has two small notches at the base that allow it

to sit securely in the vice. Fill the vessel most of the way with DI water and put the

gasket in the groove on top of the vessel. Use Ni grease along the top edge of the

vessel and coat the gasket well. Next, remove the SS head (with gold bag attached)

from the small vice and place it on top of the SS vessel. Water should overflow as the

bag is lowered into the vessel. If it doesn't, add more water until it does. It is very

important to ensure that the vessel contains no air in the annular space, as this could

Figure A2.2: Stainless steel pressure vessel with steel head, gasket, and thrust bolts. The

gold reaction cell is contained in the vessel and surrounded by a pressure fluid (DI water).

187

later cause the bag to collapse. See Fig. A2.2 for a diagram of the assembled pressure

vessel.

5. Seal the pressure vessel: Generously grease the threads on the SS pressure

vessel with Ni grease and lift the stainless steel compression cap (containing 10 thrust

bolts) over the Ti tube and onto the SS pressure vessel. Ensure that the thrust bolts are

loose, then rotate the SS compression cap on the threads on the vessel until tight.

There are two metal rods that can be placed in holes on the sides of the compression

cap to reduce the forced needed to tighten. Once tight, loosen by 1/4 turn. Grease each

thrust bolt and tighten them to barely finger tight. Then, use a torque wrench to tighten

the thrust bolts in 5 lb increments and alternating bolts: tighten 1, skip 2 and 3, tighten

4, skip 5 and 6, tighten 7, skip 8 and 9, tighten 10, skip 1 and 2, tighten 3, skip 4 and 5,

tighten 6, skip 7 and 8, tighten 9, etc. After tightening all 10 thrust bolts at a given

torque, increase the force by 5 lbs. Stop at 30 lbs.

6. Attach thermocouple and pressure fluid inlet tube/valve: The two remaining

ports on the SS head are for the thermocouple and pressure fluid inlet tube and valve.

Using the 5/8" wrench, securely tighten the bolts on the thermocouple and on the tube

into the ports.

7. Build the support structure for the Ti tube and sampling valve: The Ti tube

is relatively fragile, so we build a structure that prevents us from putting any lateral

force or torque on it when moving the vessel around and sampling. Screw two vertical

rods into the two holes on top of the compression cap, which is attached to the SS

vessel. Place a tube over each rod (the tubes are slightly shorter than the rods and wide

enough to slide over them easily). Now place the horizontal strut over the top of the

rods; the Ti-tube should sit freely in the middle of the strut and the strut should rest on

the tubes encasing the two rods. Use a washer and nut (9/16") on each tube to secure

the strut in place. It should feel very tight (Fig. A2.3C). Finally, attach the metal cage

to the strut. There are two holes on the side of the strut near the Ti tube, these

correspond to two holes on the metal cage. For now, place a bolt (1/2") through the

cage and then the strut, hold in place with a nut but do not tighten. The cage should

freely rotate, once the valve is attached you'll tighten it.

188

8. Attach the sampling valve: Place a hollow bolt, threaded side facing up, on

the Ti tube and let it fall. Then, screw on a collar to the threaded top of the Ti tube.

The tube is reverse-threaded, so you need to twist it counter-clockwise to tighten. This

can require more force than you can apply with your hands, you can use a hand-held

vice to assist you (simply adjust the vice so that it clamps tightly on the collar, when

you are done squeeze the lever near the handle to release the compression). The collar

should rest slightly below the top of the Ti-tube but not nearly to the bottom of the

threads. Place the valve on top of the collar, and raise the protective cage (Fig.

A2.3A). Ensure that the sampling port on the valve is accessible with the cage up, and

take note of the required orientation for the cage to fit the valve. Drop the cage, and

bring the bolt up the Ti tube to attach to the valve. Tighten very well, using two

wrenches (5/8" on the bolt and a large adjustable one on the valve). Raise the cage,

making certain that it fits snugly around the valve (if the fit is too loose, several

washers can be used between the valve and the cage), and tighten the bolt connecting

the cage and strut. Add the second bolt next to the first. Use a hose clamp to secure the

valve in the cage. Fig. A2.3B shows the attached valve and support structure.

9. Purge the gold bag of air: Remove air from the gold bag by adding pressure

Figure A2.3: Assembling the reactor

vessel. A. Attaching the sampling

valve (step 8). B. Full assembled

reactor. C. Completed support

structure, top view. Potential leak

points are visible in B and C. If the

leak is below the valve (B), tighten

the bolt connecting the valve to the

tube. If the leak is visible from a top

view (C), tighten accessible bolts and

retest. Disassembly may be required.

189

fluid to the annular space between the bag and the SS vessel (see section A2.7 for

more information on the pressure system). First, attach the inlet/outlet tube and valve

to the workbench pressure line to the right of the large vice. Use a hollow bolt with a

plug in the third opening of the inlet/outlet valve, this valve should be closed. At the

bench with the pressurization system, close the valves for racks 3 and 4, open the

reservoir valve and the workbench valve. Use the bleed to drop the pressure to room

pressure. Next, open the valve on the bench next to the vice as well as the inlet/outlet

valve on the vessel and open the sampling valve. Use the pump valve on the

pressurization system to add pressure fluid to the vessel, air will come out the

sampling valve. When water starts to come out of the sampling valve, close it and turn

off the pump. The gold bag is now air-free.

10. Pressure test the system: With the vessel still connected to the

pressurization system and the sampling valve closed, open all valves between the

pump and the vessel (two at the vice plus "workbench" at the pressure bench) and

bring the pressure up to 100 bars. Check for leaks, which will look like slowly (or

quickly) growing pools of water on top of the vessel. If no water is visible, increase

the pressure to 200 bars and let set for 10 minutes. If there is still no water present, the

vessel is sealed and ready to go, skip to step 12. Otherwise troubleshoot the leak (step

11).

11. Troubleshooting the leak: Most leaks are easy to fix, so if in doubt, try all

of those fixes before disassembling the vessel (see Fig. A2.3 for location of leak

points).

- Water is leaking out of the sampling port of the valve: A leaky valve can't be

fixed easily, but it can be plugged using a hollow 5/8" bolt with a plug. Tighten

the plug with a wrench, but do not over torque and make sure the valve is

stabilized by the support structure so as not to damage the Ti tube.

- Water is leaking out of the junction between the valve and the Ti tube:

Tighten the bolt at this connection. You will probably need to remove the cage

to access the bolt, and use a large wrench to hold the valve steady while you

tighten the bolt with a 5/8" wrench.

190

- Water is leaking at the connection between the SS head and either the

thermocouple or the pressure fluid inlet/outlet: Tighten the connection with a

5/8" wrench.

- Water is leaking where the Ti tube comes out of the head: This is the tough

one. The leak is the result of a poor connection between the gold bag and the

SS head; the only way to fix it is to disassemble the whole reactor and

retighten the bolt (Step 3).

12. Load the vessel into the rocking furnace: Bleed off the pressure to take the

reactor back to 1 bar. Disconnect the pressure fluid inlet/outlet line and valve from the

workbench line and remove the plug from the valve. Close the valve to the left of the

vice and the "workbench" valve on the pressure bench. Tilt the rocking furnaces such

that the opening is facing out, and prop them up using a jack and a few pieces of wood

(on the floor in front of the controllers). Loosen the vice holding the SS reactor vessel

and lift it out. Place the vessel into the furnace, rod first, such that the sampling valve

is facing out and up. The strut will be vertical. The vessel is very heavy and can cause

significant injury if dropped or carried improperly. If you are not confident that you

can move it yourself, find someone to help.

13. Secure the vessel inside the furnace: Maneuver the vessel such that the rod

at the bottom sticks out through the hole in the back of the furnace. This is easiest to

do with two people: have one person stand in front and lift the rod up towards the hole

by pulling the strut downwards, and have the second person standing behind the

furnace with a long, narrow screwdriver. When the person in back sees the rod near

the opening, insert the screwdriver into the hollow rod and guide it into alignment with

the opening. The person in front can than push the vessel further into the furnace and

the rod will extend out the back. Hold the rod in place by using a 3/4" nut on the rod,

though it should not yet be fully tightened. If the nut does not easily move along the

rod but appears to be the correct size, check the thread spacing. Some rods and nuts

have wide spacing, others have narrow spacing, and they are not compatible with each

other. Be very careful when working behind the furnaces as there are bare wires

present.

14. Attach the vessel to the furnace in front: The holes at the top and bottom of

191

the strut should align with holes on the furnace, though depending on which strut you

use and which furnace, sometimes only one hole aligns. Using 1/2" bolt(s), secure the

strut to the furnace. You will need to lift the strut in order to line up the openings,

again a second person is useful. If you have trouble lifting the vessel and strut, the nut

in back may be too tight and prevent the needed movement.

15. Completing the pressure fluid inlet/outlet lines: The valve attached to the

vessel must be screwed down to the left-top of the furnace using two long screws,

such that the valve is facing outwards (it will look similar to the valve already attached

on the right side of the furnace). Once secured, the line that goes to the pressure

release valve and the line that goes to the right-side valve should be attached to the

valve connected to the vessel. The right valve should be closed, now open the left

valve and leave it open for the remainder of the experiment. This valve connects the

pressure fluid inside your experiment to the pressure release valve, and should you

have runaway heating due to a broken component, the pressure release valve will

prevent an explosion from occurring.

16. Weight the back of the furnace: In the back, tighten the 3/4" nut using a

wrench. Next, place a lead weight on the rod and then another 3/4" nut to hold the

weight in place. The weight is necessary to shift the center of mass of the furnace

towards the middle so that the motor can rock the reactor. Without it, you risk

overworking the motor.

17. Turn on the furnace: Flip the switch to the right of the temperature

controller to turn on the furnace (Fig. A2.4). Below the controllers are 4 variacs

(variable transformers), these control the power output to each furnace. Turn the

variac that corresponds with the furnace you are using up to 50-90%. The higher the

power, the faster the vessel will heat up, but you will also have greater overshoot by

the controller (so the temperature of the furnace will oscillate over a larger range).

You can always use a high power to heat the furnace and then turn the power down

later. Set the temperature on the controller by pushing down on the middle circle and

turning it. The red arrow points to the set temperature and the green arrow points

towards the current temperature. Unfortunately the numbers on the controllers do not

192

necessarily correspond with actual temperatures, so you may need to calibrate the

furnace you are using to achieve your desired temperature. Keep in mind that the

temperature used to control the furnace is measured inside the furnace itself, and will

be 5-10 degrees higher than the temperature inside the reactor.

18. Monitor pressure and temperature: While the reactor is heating, it's a good

idea to keep an eye on the pressure and temperature inside the reactor, which can only

be done if the furnace is not rocking. To monitor temperature, simply connect the

thermocouple from the reactor to the thermocouple extension cord in port 2, the read-

out temperature will be between the two sets of non-operational furnaces on the left.

Monitor pressure by opening all the valves between the reactor and the pressure

gauge, including the "reservoir" which acts as a pressure buffer. See section A2.7.2

Pressurization System for more information.

19. When desired temperature is reached, take an aqueous sample: This first

sample will be your t=0 data point. Pressurize the reactor to at least 50 bars in order to

take the sample (since you are removing liquid, the pressure will drop quickly with

only small amounts of fluid removed, and you cannot sample if the pressure inside the

reactor is equal to the outside pressure). Take a aqueous sample of about 3 mL into a

syringe, then filter 1 mL into a vial to be tested later for elemental concentration.

Figure A2.4: View of 4 rocking

furnaces (A) showing temperature

controls and variacs. Zoomed in

image of temperature controls (B)

shows the temperature read-out,

power switch, and fuse for each of

the four furnaces.

193

Acidify the sample and be sure to get the weight of the sample and of the sample +

dilution. Use the remainder of the sample to directly measure the pH. See more

detailed sampling protocol in section A2.5 Sampling), but keep in mind that this first

sample is simpler because you are only taking one aqueous sample for both ICP and

direct pH measurement. After sampling, run the pump until the reactor is slightly

below your target pressure.

20. Add CO2: Open the CO2 tank (near the bench with the vices) and the valve

to the left of both racks of furnaces. Turn on the pump, both the power switch on the

unit on the bottom shelf of the cart and the power switch on the pump on the top shelf

of the cart. Fill the pump's reservoir by pressing "refill." The reservoir will fill with

CO2 at the tank pressure, which should be around 60 bar (if it's lower, the tank is out

of liquid and should be replaced). Once the reservoir is full (volume is about 100 mL),

compress the gas to your desired pressure by selecting "constant pressure," setting

your pressure ("A", then enter desired pressure, then "enter") and pressing "run." The

volume will decrease as the pressure increases until the set pressure is reached. Open

the valve above the pump for a second (or less) to clear the line of air, then close the

valve and connect the line to the sampling port of your experiment. Tighten the bolt

well, then open the valve above the pump again. The line is now pressurized and the

volume will drop. Wait until the flow rate is below 0.1 mL/min, make a note of the

volume in the reservoir, then open the sampling valve to allow CO2 to flow into the

reactor. Use the bleed valve to slowly remove pressure fluid from the reactor in order

to make space for the injected gas. Once your desired volume of gas has been injected,

close the bleed valve, close the sampling port, then close the valve above the CO2

pump. The pump should be stored with some gas inside. Turn off both power

switches, close the valve on the wall, and close the tank. Remove the line from the

sampling port of the reactor and replace it with a plug. Close the right valve on the

reactor plus the other valves in line (the rack 3 or 4 valve + the valve on the rack next

to the reactor), then remove the pressure line from the reactor. Detach the

thermocouple and begin rocking the reactor by flipping (and holding, if necessary) the

switch on the side of the rack.

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A2.5 Sampling

1. Stop the reactor from rocking, measure temperature and pressure: Flip the

switch next to the reactor to stop it from rocking. Use a jack and several pieces of

wood to hold the furnace into the desired position (sampling valve facing towards you

and slightly down for an aqueous sample). Attach the thermocouple to the extension

from port 2, check the temperature readout on the display between furnace racks 1 and

2. Connect the pressure fluid line to the top right valve and pressurize the line by

opening the valve for rack 4 (or 3), the reservoir, the valve on the rack, and pumping

until you reach the desired reactor pressure. Close the reservoir valve. Open the valve

on the top right of the reactor and read off the pressure.

2. Prepare for taking an aqueous sample: Open the reservoir valve and pump

the system until you reach your desired pressure (if necessary). Remove the plug from

the sampling port and replace it with the teflon sampling tube (Fig. A2.5).

3. Preweigh vials and syringes: For an aqueous sample, you will generally be

taking a fluid sample for ICP analysis and alkalinity analysis in the same syringe, plus

a sample for dissolved CO2 analysis in a separate syringe. You will first need to take a

"bleed" sample, which effectively clears the Ti sampling tube of stagnant water so that

you are sampling water that is representative of the reaction fluid. In all, you will have

three syringes (bleed, ICP/alkalinity, CO2) and two vials (ICP, alkalinity) that need to

be labeled and pre-weighed. The CO2 syringe should be pre-weighed attached to a 3-

way valve, as this will be used during sampling and left on to isolate the aqueous CO2

sample from the air. The ICP/alkalinity syringe should be weighed with the filter to be

used later for filtering the sample.

4. Take bleed: Attach the "bleed" syringe to the teflon sampling tube and

slowly open the sampling valve until water and gas begin filling the syringe. This

sample should be at least 0.5 mL of water, the gas volume will depend on your

temperature/pressure conditions.

195

5. Take ICP/alkalinity and CO2 samples: Attach both the ICP/alkalinity and the

CO2 syringes to the three-way valve, with the CO2 syringe isolated (switch pointing

towards this port). Insert the third side of the 3-way valve into the sampling port and

slowly open the sampling valve. Water and CO2 will flow into the ICP/alkalinity

syringe. Take about 0.5 mL of aqueous sample, then flip the switch on the 3-way

valve to isolate the ICP/alkalinity syringe and allow fluid and CO2 to flow into the

CO2 syringe without touching the sampling valve. Collect about 0.3 mL of fluid and

associated gas, then flip the switch back to isolate the CO2 syringe and continue taking

the ICP/alkalinity sample. In total, collect 1-2 mL of water in the ICP/alkalinity

syringe, then close the sampling valve.

6. Finish taking ICP and alkalinity samples: Moving quickly, remove the

ICP/alkalinity syringe from the 3-way valve, attach the filter, and weigh it. Pushing

the aqueous sample through the filter, inject about half into each of the pre-weighed

icp and alkalinity vials. Weigh both vials. Add approximately 10 mL of 3-5% nitric

acid to the icp vial, weigh again. Do not acidify the alkalinity sample.

7. Finish taking the aqueous CO2 sample: The CO2 syringe will still be

attached to the 3-way valve and isolated from the lab. Use pressurized house air to dry

the valve (any residual water is not part of your sample) and weigh the syringe + valve

+ sample. Record this mass. Next, inject the sample into the coulometer for analysis,

the output is in mg C which can be converted to mol CO2/kg sample (see A7.3 for

details on coulometer operation).

8. Preparing to take a gas sample: Carefully rotate the furnace such that the

sampling tube is pointing straight up (the CO2 phase is less dense than the aqueous

phase). Purge the sampling tube of water by taking a bleed, expect 1-3 mL of water to

Figure A2.5: Sampling syringe with 3-way valve, attached to sampling port. The

sampling port consists of a stainless steel, 5/8" bolt with a teflon insert, and

plastic tubing connects the insert to the 3-way valve.

196

be removed before you reach the gas phase. Use the house air line to clear water from

the teflon sampling port and dry the valve with a kim wipe. Prepare your syringe by

attaching a simple 2-way valve to the end, pre weighing is not necessary. Prepare your

storage vessel by evacuating and backfilling with an appropriate gas, such as helium.

9. Taking a gas sample: Replace the sampling port into the sampling valve,

connect the syringe to the port. Open the sampling valve slowly and fill the syringe

with gas, then close the sampling valve. Close the valve on the syringe as well to

isolate the sample from the lab air, then remove from the sampling port. Attach a

needle to the valve, which allows for the penetration of the rubber stopper on the

evacuated storage vial. Open the valve on the syringe and inject the gas sample into

the storage vial, then close the valve and slowly withdraw the needle from the rubber

stopper. Gas samples are generally stored in the freezer to minimize the reactivity of

water that may have been inadvertently introduced.

10. Finishing the sampling process: Ensure the sampling valve is closed and

replace the sampling port with a stopper (in the sampling valve). Pump the reactor if

necessary to reach the desired pressure. Close all pressure valves and remove the

pressure line from the top right (Rack 4) or left (Rack 3) valve on the furnace. Unplug

the thermocouple from the reactor. Flip the switch on the outside of the rack to turn on

the motor that rocks the furnaces.

A2.6 Taking down an experiment

To take down an experiment, repeat the set-up in reverse, starting at step 17.

Before beginning the take-down process it's worthwhile to set up your filtration

system, so that when you have opened the gold bag you can simply pour the contents

into the filter without needing to change gloves and set everything up.

1. Turn off the furnace by flipping the switch on the temperature control board.

Turn the variac down to zero (no power).

2. Remove the lead weight from the back of the reactor, using a 3/4" wrench to

remove the nut holding the weight on the rod. Remove the second nut, if present. Once

again, be cautious of bare wires and debris behind the furnaces.

3. Turn off both valves on top of the furnace. Loosen the two lines connected

197

to the "pressure release valve" (top left (Rack 4) or top right (Rack 3)). Then remove

the valve by removing the two screws securing the valve to the furnace. Unplug the

thermocouple.

4. Detach the steel strut from the furnace by loosening the bolts on the top and

bottom of the structural element. The stainless steel autoclave and attached structure

should now be free of the furnace.

5. Remove the stainless steel autoclave from the furnace, keeping in mind that

it may be very hot. The vessel is quite heavy, be sure to take appropriate precautions

(e.g. insulated gloves, a second person to assist with moving the vessel). Place the

autoclave in the large vice on the workbench and tighten securely.

6. Vent the gas phase by opening the sampling valve. You want to disassemble

the reactor as quickly as possible to minimize chemical changes during take-down

(e.g. precipitation of secondary phases). Thus, while the experiment is venting, begin

disassembling the structure that supports the sampling valve and tube.

7. Remove the hose clamp from the valve and detach the metal valve cage.

Remove the nuts that secure the horizontal strut to the vertical rods, remove the strut.

Then, unscrew the rods from the stainless steel compression cap.

8. Once the experiment has vented, remove the sampling valve using 2

wrenches, one to hold the 5/8" bolt and one to hold the valve itself (1-2"). Carefully

unscrew the bolt, putting as little torque on the sampling tube as possible. Remove the

collar from the top of the Ti-tube (it's reverse threaded) and the hollow bolt will slide

off the top.

9. Loosen the bolts connecting the thermocouple and pressure fluid inlet line to

the stainless steel head. Some water will likely leak out, if you see any gas escape then

you know that your bag is unlikely to be in good shape. It's essential that you have

vented the gas from inside the gold back before releasing pressure from the pressure

fluid, otherwise the gas inside the bag will expand and you'll create a hole in the bag.

10. Loosen the thrust bolts on top of the compression cap. Loosen one, skip

two, loosen the fourth, skip the fifth and sixth, etc. If the last bolt or two are stuck, try

tightening the bolts on each side of the stuck bolt to relieve some of the pressure and

198

reduce the force necessary to release it. Remove compression cap by unscrewing it

and then lifting it over the top of the Ti tube.

11. Carefully lift the stainless steel head with Ti-tube and gold bag attached out

of the stainless steel vessel. Place it in the smaller vice on the right side of the bench

and tighten the vice around the head, such that the bolt connecting the bag and head is

accessible. Loosen the bolt with a 5/8" wrench, then gently pull the bag away from the

head to release the Ti-tube.

12. Disassemble the bag by loosening the bolts on top of the flanged

compression collar. Often the last bolt gets stuck, tighten the two bolts on each side of

it to release the pressure.

13. Pour the contents of the gold bag into the filter. Generally you'll want to

use a vacuum filter set-up because the mineral clogs the filter quickly, plus you may

need to rinse with a lot of water. Collect some of the filtrate for analysis (pH,

alkalinity, ICP) and store it in sample bottles, acidifying and diluting the ICP sample

only. Rinse out the bag using DI water, pour into the filter. Repeat several times, until

the bag is empty of mineral/rock powder.

14. Lift the filter paper out of the filter and place on a watch glass, then leave

to dry (in either the hood or in a low temperature oven).

A2.7 Other Procedures

A2.7.1 Using the Furnace

1. Turn on power switch on the bottom right. Four numbers will appear on the

two displays on the bottom right, the two red numbers are the current temperature and

the green numbers are the programmed temperatures. The leftmost display shows the

"SP" (set point) temperature in green, this is the desired temperature and should be

420 for baking out gold bags. The rightmost display is the "Exceeded" (upper bound)

temperature and must always be greater than the set temperature. When the furnace

exceeds this higher temperature, it turns off until it cools below the set temperature.

For baking gold bags, this number should be 430.

2. Change the "SP" temperature by simply pressing the up or down arrow on

199

the leftmost display, when the desired temperature is reached, it the "set/enter" button.

Change the "Exceeded" temperature by holding down the "set/ent" button for 3

seconds, until "A1" is displayed on the top line. Adjust the temperature using the

arrows until the desired temperature is reached, which must be greater than the "SP"

temperature. Press "set/ent" again to set the upper bound temperature and then press

and hold "set/ent" for 3 seconds to return to the normal display.

3. Once the "SP" and "Exceeded" temperatures are what you'd like them to be,

start heating by holding down the "reset" button on the rightmost display until you

hear a click, at which point the readout temperature (in red) should start to increase.

A2.7.2 Pressurization System

Pressurization of reactor is achieved by compressing DI water, stored above

the pressure bench in a large plastic container (Fig. A2.6). Water is pumped by the

"pump" and can be used to pressurize several vessels. The first is the "reservoir"

which is on the second level of the pressure bench. The pump is also connected to the

furnaces on Racks 3 and 4 through valves on the pressure bench. Each of the two racks

has two pressure lines, one for the top furnace and one for the bottom furnace. These

lines are not connected to the furnaces themselves by default (just the rack structure to

the right of rack 4 and left of rack 3), and must be detached when the furnaces are

rocking to prevent shearing of the tubing. The fourth place that the pump can

pressurize is a vessel located on the main lab bench, through the "workbench" valve.

There is a second valve attached to the corner of the workbench, between the large

vice and the red tool cabinet. The 6th valve located on the pressure bench is the

"bleed" valve, this releases pressure by draining water out of the vessel to which you

are currently connected. It's generally a good idea to ensure that all valves on the

pressure bench are closed before you begin to work with the pressurization system to

prevent inadvertently affecting an experiment.

To pressurize a vessel on the workbench, connect the vessel's pressure fluid

line with the valve on the workbench (next to the vice). Ensure that all valves on the

pressure bench are closed, then use the bleed to reduce the pressure in the reservoir to

room pressure (open reservoir valve, open bleed valve, once pressure has stopped

200

decreasing, close bleed valve). Next, open the "workbench" valve and the valve next

to the vice, you now have a connection between your reaction vessel, the reservoir,

and the pump. Increase the pressure by turning the pump valve. When the desired

pressure is reached, close all valves (next to vice, "workbench", and "reservoir").

To pressurize a vessel loaded in a furnace, first ensure that the pressure fluid

inlet/outlet lines are attached to the furnace. Then, take the pressure line from the right

(Rack 4) or left (Rack 3) of the furnace and attach it to the valve on the top right (or

left) of the furnace, using a 5/8" wrench to tighten. Close all valves on the pressure

table. Then, open the reservoir valve and bleed it (if necessary) such that the pressure

is equal to what you expect the reactor pressure to be. Open all valves in line with

your experiment (Rack 3 or 4 on the table, plus one on the side of the rack, plus the

one on the top right (or left for Rack 3) of the furnace). Increase the pressure using the

pump valve on the pressure bench.

Figure A2.6: Pressurization system on the pressure bench. Valves across the front are labeled (left to

right): Bleed, Pump, Reservoir, Rack 3, Rack 4, Workbench. Analogue pressure gauge hangs above

the valves. The Reservoir sits below the bench and has its own gauge.

201

A2.7.3 Coulometer Operation

Gas delivery system: Air is taken in from the back left of the gas delivery

system (Fig. A2.7) and passes through a KOH solution to remove CO2. The air then

moves through a tube to the glass test tube, where it bubbles through the acidic

solution, picks up CO2 from the sample, and passes through a silver chloride solution

to remove sulfur. The gas then enters the coulometer. Once inside the coulometer, the

gas bubbles through a proprietary cathode solution in an electrochemical cell. CO2

reacts with the blue cathode solution to turn it clear, which increases the transmission

of the light through the electrochemical cell.. The increased transmission signals the

coulometer to run a current through the electrochemical cell and presumably reduce

the CO2 species, making the solution blue again. The coulometer measures the amount

of current needed to reduce the transmission back to 28% and converts that number

into milligrams of carbon, which is the number it outputs.

Sample injection: Wait for the coulometer reading to steady, such that the

current is at 28 and the total carbon is constant. Hit the "reset" switch to set the total

carbon measured to zero. The sample is

introduced as liquid, gas, or a combination

through a 3-way valve that connects the sample

syringe, glass test tube, and phosphoric acid

(10%) reservoir. Inject the sample by closing the

valve towards the acid reservoir, then close the

valve towards the glass test tube and backfill the

syringe with 2 pumps (4 mL) of phosphoric acid.

Close the valve towards the acid reservoir again

and inject the acid from the syringe into the glass

tube.

Calibration: The coulometer's calibration

can be checked by using test tubes with known

amounts of calcium carbonate. Inject 4 mL of

phosphoric acid into the test tube, which will

Figure A2.7: Gas delivery system for

the coulometer. Sample is injected at

3-way valve.

202

dissolve the carbonate, and the output of mg C should be comparable to the amount of

carbon you put it. To calibrate the coulometer, flip the switch on the lower left to

"calibrate". In this mode, the coulometer will NOT run a current through the cell, so

you cannot make a measurement. However, you can adjust the % of light transmitted,

such that 28% is transmitted when the electrochemical cell has no CO2 and 100% is

transmitted when it is saturated with CO2. This will affect the strength of the electrical

current applied, which affects the time required for a measurement.

Fluid replacement: When the coulometer is working well, you should see the

transmission % increase quickly after the addition of your sample, remain high for a

while, then decrease quickly to 28-30%. If you observe a tail on your measurements,

you likely need to replace some (or all) of the fluids- KOH, cathode solution, or anode

solution.

203

Appendix 3: Redox State of Reaction

We did not control for the oxidation/reduction potential in our experiments;

however, it's possible that redox state plays an important role in determining the

kinetics of olivine carbonation. Olivine contains about 10 mol% Fe, which is a redox

active element. Iron exists in the ferrous state in olivine and in its carbonate form,

siderite, but in the presence of oxygen and water, iron will oxidize to Fe3+

(Equation

A2.1).

Fe2+

+ H+ + 0.25O2 = Fe

3+ + 0.5H2O (log K=5.897 at °60 C) (A3.1)

The positive value of logK means that equilibrium favors the products, in this case,

ferric iron, over the reactants. Thus, we expect that any dissolved oxygen remaining in

the reactor will oxidize ferrous iron to ferric iron. By knowing the fugacity of oxygen

in the reactor at any given time, we can predict the partitioning of iron into the ferric

and ferrous states.

In order to determine the fugacity of oxygen in the reactor, we measure the

concentration of hydrogen gas in the supercritical CO2 phase. Measurements were

made using an Agilent 6890 Series Gas Chromatograph (GC) with a pulse discharge

detector and He as the carrier gas. ChemStation software was used to integrate peak

areas, and a four point calibration curve ranging from 100 to 800 ppm was used to

quantify the peaks. Hydrogen partial pressures are plotted as a function of time in Fig.

A3.1B and show increasing concentration as a function of time. Elemental

concentrations from the aqueous phase of this experiment are shown in Fig. A3.1A

and also show increasing concentration with time. The chemical evolution of this

experiment was very similar to experiment 19-S from Chapters 3 and 4.

Figure A3.1: Element concentration (A) and H2 pressure (B) as a function of time.

205

Appendix 4: Derivation of diffusion coefficient from Lasaga (1979).

We start with equation 15 from Lasaga (1979) for interdiffusion of n ions, linking the

flux of component i with the concentration gradient of component j:

o

njn

k

o

kkk

iji

o

i

ij

o

iij DD

Dcz

czzDDD

0

2

For binary interdiffusion, n=2 and i=j=1. For i=j, δ=1.

o

k

o

kkk

oo

DD

Dcz

czDDD 2

0

122

1

2

11111

oo

oooo

oo

ooo

DczDcz

czDDczDD

DczDcz

DczDczDD

22

2

211

2

1

1

2

1121

2

111

22

2

211

2

1

22

2

211

2

1111

oo

oooooooo

DczDcz

czDDDDczczDDDDczD

22

2

211

2

1

1

2

112122

2

21

2

111111

2

111

Define normalized concentrations (mol fractions) 1

21

1 xcc

c

2

21

2 xcc

c

oo

oooo

DxzDxz

xzDDDDxzD

22

2

211

2

1

1

2

112122

2

211

Set charges on Mg (z1=2) and H (z2=1).

oo

oooo

DxDx

xDDDDxD

2211

11212211

4

4

oo

oo

DxDx

xxDDD

2211

121211

4

)4(

206

Substitute for x2 to put the expression for D in terms of Mg concentration only.

121 xx

oo

oo

DxDx

xxDDD

2111

111211

14

)41(

)1(4

)13(

1211

12111

xDxD

xDDD

Rename variables (D11 becomes D*, 1 becomes Mg, 2 becomes H, x1 becomes c) and

add the structural term from Hellmann (2012) to get Equation 4.

ccDcD

cDDD

HMg

HMg

11

)1(4

)13(*

Reference:

Lasaga, A.C., 1979. Multicomponent exchange and diffusion in silicates. Geochim.


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