METAL-ORGANIC MATERIALS FOR HARMFUL ANIONIC SPECIES ... · parents (Mr. Youfu Wang and Mrs. Chunyan...

METAL-ORGANIC MATERIALS FOR HARMFUL

ANIONIC SPECIES REMOVAL FROM AQUEOUS

SOLUTION: INVESTIGATION,

CHARACTERIZATION AND APPLICATION

WANG, CHENGHONG

NATIONAL UNIVERSITY OF SINGAPORE

IMPERIAL COLLEGE LONDON

2017





WANG, CHENGHONG

(B.Eng. Hons, Nanyang Technological University)

A THESIS SUBMITTED

FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

NUS GRADUATE SCHOOL FOR INTEGRATIVE

SCIENCES AND ENGINEERING

NATIONAL UNIVERSITY OF SINGAPORE

2017





WANG, CHENGHONG

(B.Eng. Hons, Nanyang Technological University)

A THESIS SUBMITTED

FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF CHEMICAL ENGINEERING

FACULTY OF ENGINEERING

IMPERIAL COLLEGE LONDON

2017

NATIONAL UNIVERSITY OF SINGAPORE (NUS) –

IMPERIAL COLLEGE LONDON (ICL) JOINT PHD

PROGRAM

SUPERVISORS

Associate Professor J. Paul Chen (NUS)

Professor Kang Li (ICL)

EXAMINERS

1. Professor Li Fong Yau, Sam

2. Dr Jerry Heng, Imperial College London

3. Professor Feng Xianshe, University of Waterloo

DECLARATION

I hereby declare that this thesis is my original work and it has been written by

me in its entirety. I have duly acknowledged all the sources of information which

have been used in the thesis.

This thesis has also not been submitted for any degree in any university

previously.

The copyright of this thesis rests with the author and is made available under a

Creative Commons Attribution Non-Commercial No Derivatives licence.

Researchers are free to copy, distribute or transmit the thesis on the condition that

they attribute it, that they do not use it for commercial purposes and that they do

not alter, transform or build upon it. For any reuse or redistribution, researchers

must make clear to others the licence terms of this work

WANG, Chenghong

16 September 2017

Acknowledgments

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ACKNOWLEDGMENTS

I would like to express my deep and sincere gratitude to everyone who gave me

suggestion, guidance and support during the doctorate study.

First of all, I would like to thank Associate Professor Paul Chen at the

National University of Singapore (NUS) and Professor Kang Li at Imperial College

London (ICL), my both supervisors, who gave me not only research related

suggestions, but also support and often-needed pushing hands. Discussing issues

with them always led to fruitful consequences and they have given me

encouragements on countless occasions. I would not have been able to enjoy my

studies without their wisdoms, supports, and patience.

Furthermore, I am extremely grateful to a postdoctoral fellow who taught

me to develop my own research style, Dr. Xinlei Liu. Dr. Liu was always generous

in sharing his knowledge and expertise, and was there whenever I needed advice

and help during the research, study, and publication processes. He was a great

teacher and it was both fun and exciting working with him.

Throughout the four years in the NUS as well as the Imperial College, there

is also a long list of people who assisted with and influenced my research. I am

grateful to all of them, including my colleagues from the same research groups as

well as all the technicians, who often gave me great advice and assisted me in

various experiments.

Finally, I am forever grateful to my family and closest friends, who were

there to support and accept me as who I am, and whatever decision I make. My

parents (Mr. Youfu Wang and Mrs. Chunyan Liu) showed me unconditional love

Acknowledgments

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and encouragements, and continuously made sacrifices to ensure that I can carry

out my studies in the utmost comfort. I would also like to thank my close friends,

who alleviated my stress by reminding me that there is a world outside of my Ph.D.

studies. At last, I would like to thank Dr. Melanie Lee, who did not only give great

advice and support, but was also a great sponge when I faced tough and challenging

situations, and lightened my research days with positivity and energy.

Table of Contents

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS …………………………………………………………...….. i

TABLE OF CONTENTS ………………………………………………………………... iii

SUMMARY …………………………………………………………………………..… vii

LIST OF TABLES ………………………………………………………………………. xi

LIST OF FIGURES …………………………………………………..…………..……. xiii

NOMENCLATURE …………………………………………………………................ xix

CHAPTER 1 INTRODUCTION …………………………………………………………. 1

1.1 Background ………………………………………………………………………. 1

1.2 Objectives ……………………………………………………………..………..... 6

1.3 Thesis Structure ………………………………………………………….............. 7

CHAPTER 2 LITERATURE REVIEW ………………………………………………….. 9

2.1 Water Contaminants ……………………………………...………………….…... 9

2.1.1 Arsenic ……………………………………...……………………………... 9

2.1.2 Chromium ……………………………………...…………...……………. 14

2.1.3 Fluorine …………………………………………...……...………………. 18

2.1.4 Phosphorus ………………………………………..……...………………. 21

2.1.5 Selenium ……………………..…………………………...………………. 24

2.1.6 Silica ……………………………………...………………………………. 28

2.2 Adsorption Technologies ……………………………………...………………... 33

2.2.1 Adsorption ……………………………………...……………………….... 33

2.2.2 Functional adsorbent for water decontamination …………………………. 36

2.3 Metal-Organic Materials …………………………...…………...………………. 48

2.3.1 General introduction ……………………………………...………………. 48

2.3.2 Water stable metal-organic materials ………..…………………………… 52

Table of Contents

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2.3.3 Metal-organic materials in adsorption ………………………………….… 59

CHAPTER 3 SUPERIOR REMOVAL OF ARSENIC FROM WATER WITH

ZIRCONIUM METAL-ORGANIC FRAMEWORK UIO-66 ………………………….. 76

3.1 Introduction ……………………….……………………………………………. 77

3.2 Methods ……………………….……………………………………..…………. 80

3.3 Results and discussion ……………………….…………………………………. 84

3.3.1 Characterization of adsorbent ……………………….……………………. 84

3.3.2 Arsenate adsorption …………………………..………………………...… 85

3.4 Conclusions …………………………………………………………………….. 98

CHAPTER 4 USE OF WATER STABLE METAL-ORGANIC FRAMEWORK UIO-66

FOR EFFECTIVE UPTAKE OF AQUEOUS SILICA ………………………………... 100

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

4.2 Materials and methods ………………………………………………….……... 104

4.2.1 Material and UiO-66 synthesis ………………………………………….. 104

4.2.2 Characterization techniques …………………………………………….. 104

4.2.3 Adsorption studies ………………………………………………………. 107

4.3 Results and discussion ………………………………………………………… 109

4.3.1 Characterizations of UiO-66 …………………………………………….. 109

4.3.2 Optimal pH for adsorption ………………………………………………. 109

4.3.3 Effect of co-existing ions ………………………………………………... 111

4.3.4 Isotherm study …………………………………………………………... 112

4.3.5 Kinetics study ………………………………………………………….... 113

4.3.6 Post-adsorption analysis ………………………………………………… 115

4.3.7 Adsorption mechanism ………………………………………………..… 119

4.4 Conclusions …………………………………………………………………… 121

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CHAPTER 5 METAL-ORGANIC FRAMEWORK/α-ALUMINA COMPOSITE WITH

NOVEL GEOMETRY FOR ENHANCED ADSORPTIVE SEPARATION …………. 122

5.1 Introduction …………………………………………………………………… 123

5.2 Materials and methods ………………………………………………………… 127

5.2.1 Materials ………………………………………………………………… 127

5.2.2 Methods …………………………………………………………………. 127

5.3 Results and discussion ………………………………………………………… 131

5.3.1 Optimization of composite ……………………………………………… 131

5.3.2 Performance of composite ………………………………………………. 137

5.3.3 Additional discussion …………………………………………………… 141

5.4 Conclusions …………………………………………………………………… 144

CHAPTER 6 AMORPHOUS METAL-ORGANIC FRAMEWORK UIO-66-NO2 FOR

OXYANION POLLUTANTS REMOVAL: TOWARDS PERFORMANCE

IMPROVEMENT AND EFFECTIVE REUSABILITY ………………………………. 145

6.1 Introduction …………………………………………………………………… 146

6.2 Materials and methods ………………………………………………………… 149

6.2.1 Materials ………………………………………………………………… 149

6.2.2 UiO-66-NO2 synthesis ………………………………………………….. 150

6.2.3 UiO-66-NO2 amorphization ……………………………………………. 151

6.2.4 Characterizations ………………………………………………………... 151

6.2.5 Adsorption batch experiments …………………………………………... 152

6.3 Results and discussion ……………………………………………………….... 153

6.3.1 Characterizations of materials ……………………………………..……. 153

6.3.2 Adsorption performance for oxyanions …………………………………. 156

6.4 Conclusions ………………………………………………...…………………. 166

Table of Contents

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CHAPTER 7 ZIRCONIUM-BASED NANOCLUSTERS AS MOLECULAR ROBOTS

FOR EFFECTIVE ANIONS UPTAKE …………………………...…………………... 168

7.1 Introduction …………………………………………………………………… 169

7.2 Methods and materials ………………………………………………………… 170

7.3 Results ………………………………………………………………………… 174

7.3.1 Material Characterizations ……………………………………………… 174

7.3.2 Sorption performance …………………………………………………… 180

7.3.3 Mechanism analyses …………………………………………………….. 187

7.4 Discussion and conclusion …………………………………………………….. 190

CHAPTER 8 CONCLUSIONS AND RECOMMENDATIONS ……………………… 194

8.1 General conclusions …………………………………………………………… 194

8.2 Recommendations …………………………………………………………….. 198

LIST OF PUBLICATIONS ……………………………………………………………. 200

APPENDIX ……………………………………………………………………………. 202

REFERENCES ………………………………………………………………………... 205

Summary

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SUMMARY

Clean and safe water is a necessity to humanity. The ever-increasing pollutant level

in water has been a critical global issue. Water pollutants can generally be divided

into two categories – organic and inorganic, based on their chemical composition.

Generally, inorganic pollutants are more persistent in the environment than organic

contaminants. In particular, they consist of a variety of metal and metalloid species

which often rapidly oxidize to oxyanions in industrial waste, due to the high

temperatures and varying pH conditions used in industrial processes. In addition to

the anionic metal complexes (e.g. chromate, arsenate/arsenite, selenate/selenite,

etc.), the industrial development has also delivered a number of anionic species (e.g.

phosphate, fluoride, etc.) into ecosystems. Given that these anionic pollutants are

charged molecules, they tend to be highly soluble in water making them a very

bioavailable group of pollutants. It is therefore extremely problematic if these

pollutants are allowed to enter the water supply systems since many anionic species

are toxic to human and wildlife at ppm- or even ppb-level concentrations.

With a clear intention to ensure regulation and environmental control,

international authorities like the World Health Organization (WHO) and U.S.

Environmental Protection Agency (USEPA) have set stringent standards to limit

the concentration of these priority contaminants in drinking and ground water. The

stringent regulation standards to remove these water pollutants and provide quality

water require effective technologies for water decontamination. A cost-effective

method involves the use of a permanently porous material to adsorb the

contaminants. Conventional porous materials that have been widely studied include

Summary

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activated carbons, zeolites, metal oxide nanoparticles, etc. However, there are a few

drawbacks associated with these adsorbents, including: (1) low to moderate surface

areas that limit the number of sites available for adsorption, (2) lack of tunability

making specific selectivity difficult to achieve.

A recently developed class of porous materials, metal-organic frameworks

(MOFs), has attracted substantial attention during the last decade. They are typically

comprised of inorganic metal-containing units linked by organic ligands through

coordination bonds. The formed porous structures with pores of molecular

dimensions are associated with a series of desirable properties such as low density,

high surface area and high porosity. Moreover, MOFs are preferred over other

porous materials, owing to their customizable chemical functionalities, versatile

architectures and milder synthesis conditions. As a result of these advantages,

MOFs have been proposed by researchers for a range of applications including gas

storage, separation, sensing and catalysis. In this thesis, the feasibility of water

stable MOF materials working as functional adsorbents for contaminated water

remediation (especially centered on anionic pollutants removal) was explored.

Three stages of research were developed, which includes: firstly, the application of

water stable MOF for the highly effective removal of specific anionic species; and

secondly – resolving the applicability problems of MOF adsorbents; and thirdly –

the introduction of using metal-organic nanoclusters for efficient water

decontamination.

In the first-stage of the studies, it was found that the hydro-stable zirconium-

based MOF, UiO-66, is capable of removing arsenate and silicate species from

wastewater. In the case of arsenic uptake, the synthesized UiO-66 adsorbent

Summary

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functioned excellently across a broad pH range of 1 to 10, and achieved a

remarkable arsenate uptake capacity of 303 mg/g at optimal pH. This is one of the

highest arsenate adsorption capacity ever reported to date, much higher than that of

currently available adsorbents (5-280 mg/g, generally less than 100 mg/g). For the

removal of aquatic silica, the highest uptake achieved was found to be 50 mg-Si per

gram of adsorbent. The presence of common ions showed little evidence of

hindering the adsorption process. The superior uptake performance of UiO-66

adsorbent could be attributed to its highly porous crystalline structure containing

zirconium oxide clusters, which provides a large contact area and plenty of active

sites in unit space. The studies at this stage provided significant new insights to the

application of MOFs in water treatment, and it appeared that water stable MOF

could work as a promising advanced adsorbent in the water decontamination

industry.

However, some applicability problems had risen in regard to the practical

use of this relatively new porous material, e.g. the lack of a binder to support the

MOFs as they are normally developed in particle form, and the reusability problem

as the crystalline MOF adsorbents for water applications exhibited limited

regenerative capabilities. Hence, in the second-stage of the studies, strategies for

resolving these two critical problems were investigated. The functional MOF

adsorbents were incorporated into specifically designed ceramic hollow fibers for

enhanced adsorptive separation. Such development provides a creative approach to

use the adsorbent in a more efficient way, compared to binding and packing them

into adsorption columns. When it was applied for arsenic contaminated water

remediation, it produced the potable water recovery directly; whereas to achieve a

Summary

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similar performance, the packed column bed required eight times amount of active

MOF adsorbents. Furthermore, the hydro-stable MOFs can be properly amorphized

(defect engineering) for an enhanced adsorptive performance and excellent

regenerative capability for anionic pollutants uptake. It was found that, with the

amorphous MOF adsorbents, more than 80% of the adsorption capacities was

retained after 8 cycles of applications.

To examine the extreme capability of metal-organic materials, metal-

organic nanoclusters were developed as proof-of-concept molecular robots for

super-rapid anions capture from wastewater. Notably, with this approach, the

removal of pollutants can be completed within seconds, which is two to four orders

of magnitude faster than the removal rates of typical sorbents. Besides, the

nanoclusters exhibit a stimuli-responsive behavior by dissolving in acidic aqueous

solutions for molecular-level decontamination, and quickly aggregate for post-

remedy collection at a neutral pH. Overall, advancing from the current anionic

sorbents, the metal-organic clusters acting as molecular decontamination robots

could provide superior performance. With further improvement and engineering,

metal-organic materials might be of significance one day in addressing the global

problems of water scarcity and environmental pollution.

List of Tables

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LIST OF TABLES

Table 2-1. Chemical structures of key inorganic and organic arsenic species. .............…. 10

Table 2-2. List of water stable MOFs under aqueous solution conditions ………………. 55

Table 3-1. Kinetics parameters with respect to pseudo-first-order and pseudo-second-order

models, [UiO-66] = 0.1 g/L, [As(V)]0 = 60 mg/L, and T = 25±1 oC. …………………… 90

Table 3-2. Langmuir and Freundlich isotherm parameters for arsenate adsorption onto UiO-

66 adsorbents, [UiO-66] = 0.5 g/L and T = 25±1 oC. ……………………………...……. 92

Table 3-3. Comparison of arsenate adsorption among prevalent adsorbents. …………… 93

Table 4-1. Langmuir isotherm fitting parameters for silicate adsorption onto UiO-66. ... 113

Table 4-2. Kinetic models and fitting parameters regarding the silicate adsorption kinetics

using UiO-66 adsorbents. …………………………………………………………….... 115

Table 4-3. Binding energy and relative contents of relevant peaks in XPS spectra of spent

UiO-66 sample. ……………………………………………………………………..…. 118

Table 4-4. Maximum theoretical silicate uptake for Mechanisms A and B in comparison to

the experimental uptake at pH 10. …………………………………………………...…. 120

Table 5-1. Spinning parameters for α-alumina hollow fiber ………………………….... 129

Table 5-2. Optimized parameters for vacuum filtration process ……………………….. 136

Table 5-3. Optimized experimental parameters for arsenic contaminated water remediation

using composite-1 ……………………………………………………………………... 138

Table 5-4. Experimental parameters for arsenic contaminated water remediation using

packed column beds ………………………………………………………………….... 140

Table 6-1. List of toxic contaminants (forming oxyanions) and their health effects. …... 146

Table 6-2. Binding energy and relative contents of Zr 3d orbitals with respect to UiO-66-

NO2 and am-UiO-66-NO2 sample. …………………………………………………….. 164

Table 7-1. Representative sorbents comparison ……………………………………….. 183

List of Tables

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Table 7-2. Commercially available arsenic removal products and costs …..…… 191

Table 7-3. Production cost of Zr-cluster ……………………………………….. 191

Table 7-4. Production cost of Zr-cluster estimated based on wholesale prices … 192

Table 8-1. Comparison and evaluation amongst metal-organic materials studied in

current thesis ………………………………………………………………..…. 195

List of Figures

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LIST OF FIGURES

Figure 1-1. Flow chart of thesis organization …..………………………………………… 8

Figure 2-1. Distribution of arsenic species in aqueous solution. Up: As(V). Down: As(III).

(Simulated by MINEQL+4.5) …………………………………………………………... 11

Figure 2-2. Predominance diagram of chromate in aqueous solution. Distribution of

chromium-related species is complicated, and is dependent on the total dosing centration

of chromium-related species. ………………………………………………………….... 15

Figure 2-3. Distribution of fluoride species in aqueous solution. ………………....…….. 18

Figure 2-4. Distribution of phosphate species in aqueous solution. ………………….…. 21

Figure 2-5. Distribution of selenium species in aqueous solution. ……….……………... 25

Figure 2-6. Distribution of silica species in aqueous solution. ………………….………. 29

Figure 2-7. Basic terms and illustration of adsorption. ……………………………..…… 34

Figure 2-8. One typical example of MOF, UiO-66: (a) theoretical cluster unit, (b) SEM

morphology of crystals. …………………………………………………………………. 49

Figure 2-9. Schematic illustration of the new strategy for efficient adsorbent. …………. 71

Figure 3-1. (a) Six-center octahedral zirconium oxide cluster. (b) fcu unit cell of UiO-66;

blue atom – Zr, red atom – O, white atom – C, H atoms are omitted for clarity. …….…. 79

Figure 3-2. (a) PXRD pattern and FTIR spectrum of pristine UiO-66 adsorbent. (b)

Nitrogen adsorption (filled circles)-desorption (open circles) isotherms and SEM image of

pristine UiO-66 materials. ……………………………………………………………..... 85

Figure 3-3. (a) pH effect on arsenate adsorption. (b) pH effect on As(V) speciation,

adsorbent surface charge and adsorption performance. (c) Coexisting anion effects on

arsenate adsorption at pH 2. [UiO-66] = 0.5 g/L, [As(V)]0 = 50 mg/L, [coexisting anions]

= 1 g/L, T = 25±1 oC. ……………………………………………………………………. 86

List of Figures

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Figure 3-4. Adsorption kinetics of arsenate adsorbed onto UiO-66 adsorbent: (a) [UiO-66]

= 0.3 g/L, [As(V)]0 = 60 mg/L, pH = 2.0, T = 25±1 oC; (b) [UiO-66] = 0.3 g/L, [As(V)]0 =

60 mg/L, pH = 7.0, T = 25±1 oC. ……………………………………………………..…. 89

Figure 3-5. (a) Adsorption isotherm of arsenate onto the UiO-66 adsorbent at pH = 2 and

7; Langmuir fitting model is in red solid lines, Freundlich fitting model is in blue dash lines;

[UiO-66] = 0.5 g/L, pH = 7.0, T = 25±1 oC. (b) Comparison on arsenic adsorption

performance among prevalent adsorbents. This figure was made based on Table 3-3;

working pH range length is defined as how many integral pH values the working pH range

covers. …………………………………………………………………………………... 91

Figure 3-6. SEM image (a) and corresponding EDX data (b-d) of UiO-66 sample. The green

and red signals in (b) and (c) represent Zr and As, respectively. The quantitative

composition of C and O in (d) is not accurate as the carbon tape was employed as

background. ……………………………………………………………………………... 94

Figure 3-7. PXPRD patterns (a) and FTIR spectra (b) of UiO-66 samples before and after

use. In (b), the spectra from 600-1200 cm-1 is enlarged in the lower right corner. Proposed

adsorption mechanism of arsenate onto UiO-66 through coordination at (c) hydroxyl group

and (d) BDC ligand. In (d), H atoms in the cluster are omitted for clarity; (OOC) is part of

the BDC linker (-OOC-benzene-COO-) and linked to another Zr6 cluster. ………….… 96

Figure 4-1. Silica uptake with UiO-66 adsorbent at different pH values. ……………… 111

Figure 4-2. Silica uptake with UiO-66 in presence of coexisting ions. ……………….... 112

Figure 4-3. Adsorption isotherm of silicate onto UiO-66 at pH = 10 and room temperature

together with fitted adsorption isotherm. ………………………………………………. 113

Figure 4-4. Adsorption kinetics of silicate adsorption onto UiO-66 adsorbents. ………. 115

Figure 4-5. PXRD patterns for pristine and spent UiO-66. …………………………….. 116

Figure 4-6. FTIR spectra for pristine and spent UiO-66. ……………………………….. 117

List of Figures

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Figure 4-7. High resolution scan XPS spectra on spent UiO-66 adsorbent with respect to:

(a) Si 2p, (b) O 1s, and (c) Zr 3d orbitals. ………………………………………….…… 118

Figure 4-8. Proposed adsorption mechanisms. ……………………………………….... 119

Figure 5-1. Arsenic adsorption kinetics comparison: UiO-66 and other typical sorbents with

same order-of-magnitude particle size. ……...………………………………………… 125

Figure 5-2. Schematic diagram of adsorptive separation by composite-1: for arsenic

contaminated water remediation. The inset demonstrates an enlarged cross-sectional view

of composite-1. Blue molecule: water; green molecule: arsenic pollutant. ……………. 126

Figure 5-3. Scheme of vacuum filtration process. ……………………………………… 129

Figure 5-4. Prototype of experiment setup, using composite-1 for arsenic contaminated

water remediation. ……………………………………………………………………... 130

Figure 5-5. Prototype of experiment setup, using packed column bed setup for arsenic

contaminated water remediation. …………………………………………………….... 131

Figure 5-6. SEM images: (a) Alumina particles constituting the walls of ceramic hollow

fiber micro-channels. (b) Scattered UiO-66 crystal particles. (c) Enlarged view inside the

micro-channel showing UiO-66 crystals stay with alumina particles. Yellow shades

indicate the octahedral UiO-66 crystals. ……………………………………………….. 132

Figure 5-7. SEM and TEM images: (a) Cross section of α-alumina hollow fiber; the yellow

dashed circle signifies two distinct layers. (b) Enlarged cross-sectional view showing open

micro-channels; yellow lines highlight three examples of micro-channels. (c) Outer surface

morphology of α-alumina hollow fiber, showing the opening of micro-channels at the shell

side. (d) Inner surface of α-alumina hollow fiber. (e) UiO-66 crystals; the inset with yellow

dashed line border shows the corresponding TEM image. (f) UiO-66 crystals deposited

within micro-channels; micro-channel walls are formed by the packing of alumina particles;

yellow shades indicate the deposited octahedral UiO-66 crystals. …...………………… 133

Figure 5-8. Pore size distribution of the 3D pore structure of α-alumina hollow fiber. ... 134

List of Figures

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Figure 5-9. Outer surface of α-alumina hollow fiber (micro-channel opening). ……….. 134

Figure 5-10. XRD pattern of as-synthesized UiO-66 sample. ………………………….. 135

Figure 5-11. Nitrogen adsorption (filled circles)-desorption (open circles) isotherms of as-

synthesized UiO-66 sample. ………………………………………………………..….. 135

Figure 5-12. Breakthrough studies: (a) using composite-1 for arsenic water

decontamination (1 ppm, 10 ppm and 20 ppm as the arsenate concentration in the feed

solution were investigated); (b) using equivalent packed columns for arsenic water

decontamination (1 ppm as the arsenate concentration in the feed solution was used for

comparison). With reference to the quantity of MOF loaded in composite-1, the columns

were packed with: equal (1X), twice (2X), five times (5X) and eight times (8X) the amount

of MOFs, respectively. The data in (b) are reported as the average of duplicate

experiments. ………………………………………………………………………….... 139

Figure 5-13. TGA analyses for weight changes with temperature on composite-1, alumina

and UiO-66. ……………………………………………………………………………. 142

Figure 5-14. FTIR spectra of composite-1, alumina and UiO-66. ……………………... 143

Figure 6-1. Characteristics of UiO-66-NO2 and am-UiO-66-NO2: (a) and (d) FESEM image

of UiO-66-NO2 and am-UiO-66-NO2; (b) PXRD patterns of UiO-66-NO2 and am-UiO-66-

NO2; (c) FTIR spectra of UiO-66-NO2 and am-UiO-66-NO2. ………………………..... 154

Figure 6-2. (a) Nitrogen adsorption-desorption behaviors of UiO-66-NO2 and am-UiO-66-

NO2. (b) Pore width distribution of UiO-66-NO2 and am-UiO-66-NO2. ……….……… 156

Figure 6-3. Adsorption isotherms as well as reusability in multiple cycles with respect to

As (a & b), Cr (c & d) and Se (e & f). ………………………………………………….. 158

Figure 6-4. Elemental mapping analysis with respect to post-adsorption am-UiO-66-NO2:

(a) arsenate uptake, (b) chromate uptake, and (c) selenate uptake. (d) Post-arsenic-

adsorption analysis using FTIR: red line – spent adsorbent sample, black line – pristine

material sample. ……………………………………………………………………….. 160

List of Figures

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Figure 6-5. High resolution scan XPS of Zr 3d orbitals with respect to: (a) UiO-66-NO2

sample, and (b) am-UiO-66-NO2 sample. ……………………………………………… 163

Figure 6-6. High resolution scan XPS spectra on post-adsorption am-UiO-66-NO2

adsorbent in the case of: (a & b) arsenate uptake, (c & d) chromate uptake, and (e & f)

selenate uptake. …………………...…………………………………………………… 165

Figure 6-7. High resolution scan XPS spectra of nitrogen 1s orbital with respect to am-UiO-

66-NO2 material, and post-adsorption adsorbent in the case of arsenate uptake, chromate

uptake and selenate uptake. …………...……………………………………………….. 166

Figure 7-1. Structural concepts of Zr-cluster and schematic representations of molecular

robots for water decontamination. (a) Photograph of as-synthesized Zr-clusters and

structural representation of zirconium clusters with octahedral metal center (octahedron-

shape highlighted in blue); color code: Zr (blue), C (grey), O (red), H atoms are omitted for

clarity. (b) HRTEM image of Zr-cluster with EDX analysis shown in inset (bottom). Inset

(top): AFM image of well-dispersed clusters. (c) ATR-FTIR spectrum of Zr-cluster

indicating critical molecular groups. (d) Zeta-potentials of Zr-cluster in water at pH 2 and

pH 6.5. Inset: Photograph of dissolved clusters under acidic aqueous condition and

aggregated flocculants formed in neutral environment. e, Schematics of molecular robotic

concept, illustrating the process of Zr-cluster as stimuli-responsive molecular robots for

water decontamination. …….………………………………………………………….. 176

Figure 7-2. HRTEM image of well-dispersed Zr-cluster. ……………………………… 177

Figure 7-3. AFM image of Zr-cluster particles. ………..………………………………. 177

Figure 7-4. PXRD full spectrum of as-synthesized Zr-cluster. ……………………….... 178

Figure 7-5. ATR-FTIR full spectrum of as-synthesized Zr-cluster. ……………………. 179

Figure 7-6. Figure 7-6. TGA analysis of as-synthesized Zr-cluster. ..…………..… 179

Figure 7-7. Uptake equilibrium isotherms with respect to respective anionic pollutants by

Zr-cluster. ..…………………………………………………………………………….. 182

List of Figures

~ xviii ~

Figure 7-8. Sorption equilibrium isotherm being analyzed by Langmuir and Freundlich

models with respect to (a) arsenate, (b) chromate, (c) fluoride and (d) phosphate

uptake. ............................................................................................................................. 182

Figure 7-9. (a) Removal rates with respect to respective anionic pollutants by Zr-cluster.

(b) UV-Vis spectra with respect to phosphate removal process by Zr-cluster. ………… 185

Figure 7-10. Uptake efficiency of anionic pollutants – arsenate, chromate, fluoride and

phosphate, with the existence of common ions. ……….…………..…………………… 186

Figure 7-11. Uptake capacities after three consecutive regeneration cycles with respect to

respective anionic pollutants by Zr-cluster. ………..….…………..…………………… 186

Figure 7-12. Zirconium elemental residual in post-remedy water recoveries, in comparison

with initial dosage of Zr clusters. ………..…………….…………..…………………… 187

Figure 7-13. Mechanisms of anionic pollutants removal by Zr-cluster. (a) FESEM-EDX

elemental mapping of aggregated Zr-cluster flocculants that were collected after phosphate

removal. (b) EDX quantitative data together with zirconium and phosphorus elemental ratio.

(c) O K-edge XAS spectra of Zr-clusters before and after capturing different target

compounds. ….………………………………………………………………………… 188

Figure 8-1. Development of anions sorbents: from conventional metal oxides to structured

porous materials and now nano-clusters. ……………………………………………..... 195

Nomenclature

~ xix ~

NOMENCLATURE

Symbol Description

b Langmuir isotherm single component parameter (L/mg)

Ce concentration in the liquid phase, in equilibrium with qe (mg/L)

EDX energy dispersive X-ray spectrometer

FESEM field emission scanning electron microscope

FTIR Fourier transform infrared spectroscopy

K1 pseudo-first-order model constant (h-1)

K2 pseudo-second-order model constant (g mg-1 h-1)

Kf, n Freundlich isotherm constants

NOM natural organic matter

p pressure (pascal)

PSF polysulfone

PVA polyvinyl alcohol

PZC point of zero charge

Q adsorption uptake (mg/g)

qe concentration in the solid phase, in equilibrium with Ce (mg/g)

qmax maximum adsorption capacity (mg/g)

qt adsorption capacity at time t (mg/g)

RO reverse osmosis

Nomenclature

~ xx ~

S effective area of membrane in filtration study (m2)

t time (s, m, h)

T temperature (oC)

TGA thermal gravimetric analysis

TOC total organic carbon

XPS X-ray photoelectron spectroscopy

XRD powder X-ray diffraction

ΔpH difference of solution pH

Chapter 1

1

CHAPTER 1 INTRODUCTION

Chapter 1 provides some background knowledge of anionic pollutions, adsorption

technologies as well as metal-organic materials, followed by the objectives for each

chapter and an overview for the thesis.

1.1 Background

Water, one of the prime elements responsible for life on earth, represents one of the

most valuable resources to the current and future societies of mankind (Shannon et

al., 2008). However, owing to the continuing growth of human population and

industrialization, the exploitation, mistreatment and contamination of the natural

heritage of water (rivers, lakes, seas and oceans) has also followed in parallel (Fu

and Wang, 2011). Technologic and economic developments are filling the various

water bodies with toxic pollutants that are a major threat to human health.

Nowadays, more than 1.2 billion people in this world lack access to clean and safe

drinking water (Tesh and Scott, 2014). Therefore, water issues in regards to the

increasing water scarcity as well as water pollution are regarded as one of the most

vital topics of environmental concern to human beings.

The ever-increasing level of water pollution augments the water scarcity

issue. Typical water pollutants can be categorized as organic or inorganic (Tesh and

Scott, 2014). They majorly come from the agricultural, industrial, and domestic

activities that leave behind numerous synthetic and geogenic compounds in varying

concentrations. Although most of these compounds are present at low

Chapter 1

2

concentrations, many of them raise considerable toxicological concerns,

particularly when present as components of complex mixtures. This is especially

the case for inorganic pollutants, which are normally referred to as heavy metal

pollutants (Lim and Aris, 2013). Heavy metal pollution is widely detected in

different regions all over the world, and they are extremely dangerous with chronic

or acute toxicity to living organisms. Most heavy metal elements existing as metal

cations could be precipitated in alkaline conditions, whilst some of them forming

anionic metal complexes (e.g. chromate, arsenate/arsenite, and selenate/selenite)

are difficult to remove from water streams (Xu et al., 2016). In addition, another

type of anionic species (nonmetal) including phosphate, fluoride, cyanide, etc.

introduces significant environmental problems to the ecosystems too (Xu et al.,

2016). For instance, the dangerous eutrophication caused by excessive phosphate

has troubling ecological impacts, such as biodiversity damage and aquatic

environment deterioration (Conley, 2009).

Thus far, potentially harmful concentrations of these anions have been

found in numerous drinking water sources leading to the severe health related

problems in humans (Moore and Ramamoorthy, 1984; Tesh and Scott, 2014).

Detailed information (including their permissible concentrations in water, the main

sources of pollution and the potential health/environmental risks, etc.) of these

anionic species can be found in Chapter 2 Literature Review (vide infra). Aiming

to minimize the potential threats rooted in these hazardous anionic species, the

international and national environmental protection agencies including United

States Environmental Protection Agency (USEPA) and World Health Organization

(WHO) have repeatedly established permissible limits (in the range of µg/L to a

Chapter 1

3

few mg/L) for these contaminants in the past few decades to control the quality of

drinking water.

Substantial research and development work has been carried out on the

development of robust technology for the remediation of anionic pollutions (Fu and

Wang, 2011). As compared to the removal of other aquatic pollutants, the removal

of anions is often a challenging task due to their physico-chemical properties, which

play a vital role during their removal from the aqueous phase. The mobility of

anionic species also depends on the speciation and complexation with natural

organic material. Thus far, various treatment approaches including adsorption,

coagulation and precipitation, pressure-driven membrane separation,

electrochemical methods, as well as biological methods have been studied to

various extents to come up with the best process that is efficient, cost-effective and

draws less energy for its operation to remove anionic pollutants from wastewater

(Fu and Wang, 2011). Among the above-mentioned processes, adsorption is one of

the widely used processes that have been employed for a wide variety of aquatic

pollutants including anions. It offers significant advantages such as wide

availability, profitability, simplicity in operation and efficiency (Ali, 2012).

The adsorption of anions at the solid-liquid interface and its effect on the

fate and mobility of anions in the environment is directly controlled by the diverse

properties of the pollutant and adsorbent. Typical adsorbents that have been

extensively studied and developed to date include those permanently porous

materials such as activated carbons, metal oxide nanoparticles, zeolites, etc. (Mohan

and Pittman, 2007). The adsorption of anions onto these adsorbents mostly occurs

through ligand exchange or by ion-pair formation with positively charged surface

Chapter 1

4

sites (Lim and Aris, 2013). Despite some satisfactory performance reported, there

are generally a few drawbacks associated with these adsorbents, including: (1) low

to moderate surface areas that limit the number of sites available for adsorption, and

(2) lack of tunability making specific selectivity difficult to achieve (Mohan and

Pittman, 2007).

Recently, a new type of porous materials, i.e. metal-organic frameworks

(MOFs), has attracted substantial attention over the last decade (Zhou et al., 2012).

They are typically comprised of inorganic metal ions or metal clusters linked by

organic ligands through strong coordination bonds. The formed porous structures

with pores of molecular dimensions are associated with a series of desirable

properties such as low density, high surface area and high porosity (Zhou et al.,

2012). Moreover, MOFs are preferred over other porous materials such as zeolites

and carbon-based materials, owing to their customizable chemical functionalities,

versatile architectures and milder synthesis conditions (Qiu et al., 2014). As a result

of these advantages, MOFs have been proposed by researchers for a range of

applications including gas storage, separation, sensing and catalysis (Kreno et al.,

2012; Li et al., 2012; Suh et al., 2012).

MOFs offer an appealing alternative platform for applications in wastewater

remediation applications, although research on the use of MOFs in wastewater

remediation is still in its infancy (Khan et al., 2013). It can be designed such that

the size, shape, and chemical composition of the pores can be tuned to promote the

uptake of specific target molecules with high affinity or selectivity (Howarth et al.,

2015b). However, the tendency to structurally degrade in a water-containing

atmosphere is a major limitation for MOFs. Since water effects on diverse

Chapter 1

5

applications could be quite vast and complex, development of water stable MOFs

became necessary in order to deliver more potential applications in wastewater

remediation (Canivet et al., 2014a). Despite the scarcity of hydro-stable MOFs in

the early years, they have been evolving recently (Burtch et al., 2014). With the

recent advent of MOFs that are highly stable in water under varying pH conditions,

such as zirconium-based MOFs, research on the use of MOFs in wastewater

remediation is quickly expanding (Howarth et al., 2015b). Owing to their

exceptional physical and chemical characteristics, they possess a great potential in

achieving adequate efficiencies for water decontamination processess.

Following these remarks, this study looks into the development of metal-

organic materials based technologies for anionic species removal from wastewater.

The study is split into three main sections: fundamental single-component

adsorption study on using hydro-stable Zr-MOFs for specific anionic species

removal, the improvement of MOF adsorbents to resolve its inherent problems

(binder and regenerability problems) in adsorptive processes, and finally, a novel

concept of applying metal-organic nanocluster material as molecular robots in

anionic species removal.

(Note: full names, the molecular structural information as well as the ligand

abbreviations with respect to all the MOFs mentioned in this thesis can be found at

the end, Appendix.)

Chapter 1

6

1.2 Objectives

The main aim of this thesis is to study MOF adsorbents with great efficacy in

anionic species uptake from aqueous media. Firstly, Zr-MOF UiO-66 in

nanoparticle form is developed for anionic species removal from wastewater. Two

particular anionic species – arsenate and silicate – were studied respectively. The

knowledge gained from these studies will then be analyzed and transferred to the

next part of the studies, i.e. how to improve the applicability of Zr-MOF adsorbents.

In this part, two major problems such as the binder problem and regenerability

problem will be tackled, to fulfill the feasibility of metal-organic materials in

adsorption processes. At the end, taking one step further from the 3D MOFs, 0D

metal-organic clusters are developed as smart molecular robots for anions uptake.

To elaborate, the detailed objectives of this thesis include:

1. To proper characterize the various Zr-MOFs, including their morphologies,

particle sizes, crystallinities, element composition, functional groups, etc.

2. To understand the adsorptive behaviors of Zr-MOFs for specific anionic

species, via proper experiments and adsorption modellings.

3. To understand the adsorption mechanisms involved in respective cases.

4. To develop a proper ceramic hollow fiber support to combine with

functional Zr-MOFs, providing enhanced performance.

5. To evaluate the breakthrough of contaminated water continuous remediation

using different adsorption processes.

6. To develop amorphous MOFs with excellent reusability and improved

capacities.

Chapter 1

7

7. To characterize the changes in interior porous structures after MOF

amorphization.

8. To develop and study metal-organic nanocluster, together with its

applicability in anion species removal.

1.3 Thesis Structure

This thesis consists of 8 chapters in total; to develop functional metal-organic

materials for anionic species removal from wastewater. Chapter 1 introduces the

general background information, and also includes the main objectives of this study.

Chapter 2 reviews the literature to provide detailed information of targeting anionic

species, currently available adsorption technologies, as well as MOFs and their

adsorptive applications. Following that, Chapter 3 starts with an adsorptive study

using Zr-MOF to effectively uptake arsenic species from aqueous solutions.

Chapter 4 conducts another study using Zr-MOF to reduce aquatic silica, which

could help prevent serious fouling/scaling in industrial processes. After these two

chapters, it shall be realized that particle-form MOF adsorbents are associated with

some applicability problems, i.e. the binder problem and the regeneration problem.

Thus, Chapter 5 intends to combine the functional MOFs with specifically

structured ceramic hollow fiber, which could provide better remediation

performance in a continuous process. On the other hand, Chapter 6 concentrates

on developing amorphous MOFs with enhanced adsorption capacities and excellent

regenerability for anionic species adsorptions. Moving on, Chapter 7 looks into

metal-organic nanoclusters and studies its capability in anions uptake; this proof-

Chapter 1

8

of-concept work could provide an alternative promising platform in anions

decontamination. At the end, Chapter 8 concludes the thesis, with regards to the

achievements made and future works that can be carried out. A flow chart is shown

below for the readability and the clear presentation on this thesis’s organization.

Figure 1-1. Flow chart of thesis organization

Chapter 2

9

CHAPTER 2 LITERATURE REVIEW

Chapter 2 provides a substantial review upon the literature with respect to the three

key elements: (1) representative elements forming anionic species in wastewater,

(2) currently available adsorption technologies, (3) metal-organic materials and

their applications. Regarding each anionic species element, relevant information

such as its basic and water chemistry, occurrence in environment, negative

influence, and outstanding regulation standards will be given. Moreover, the

theoretical concepts of adsorption technology will be studied, together with a

survey of existing adsorbents for water decontamination. At the end, a general

introduction on metal-organic materials and their potential applications that have

been reported in the past few years will be provided.

2.1 Water Contaminants

2.1.1 Arsenic

Chemistry of arsenic

Arsenic, a metalloid element of Group VA in the periodic table, would normally

exist in oxidation states as As(-III), As(0), As(III) and As(V) (Jain and Ali, 2000).

Typically, the most commonly found inorganic arsenic species in environment

would be due to As(V) (arsenate) and As(III) (arenite), which forms arsenious acids

(H3AsO3), arsenic acids (H3AsO4), and their related ionic compounds – As(OH)4-,

AsO2OH2-, AsO33-, and AsO4

3-, HAsO42-, H2AsO4

-, etc. These inorganic species of

arsenic mostly exist in water solutions. In particular, As(V) is prevalent in

Chapter 2

10

oxygenated surface water streams, whilst As(III) is present in groundwater and

other water bodies with reducing conditions. Besides, trace levels of organic arsenic

could be detected, which may be produced by naturally biological activity or

industrial pollution. For instance, methyl-arsenic acid (MMA) and dimethyl-arsenic

acid (DMA) are two of the typical forms of organic arsenic (Habuda-Stanic and

Nujic, 2015). The chemical structures of representative arsenic species are

summarized in Table 2-1 (Habuda-Stanic and Nujic, 2015).

Table 2-1. Chemical structures of key inorganic and organic arsenic species.

Inorganic arsenic Organic arsenic

Name Structure Name Structure

As(V)

MMA

As(III) DMA

Water pH controls arsenic speciation. Simulating the water condition using

the software – MINEQL+4.5, the species distribution of As(V) and As(III) as a

function of solution pH can be obtained and plotted in Figure 2-1. Note that in the

pH range of 6-8 most likely encountered in natural environments, the predominant

inorganic species of arsenic exist as H2AsO4- and HAsO4

2-, as well as the uncharged

As(III) species H3AsO30.

Chapter 2

11

Figure 2-1. Distribution of arsenic species in aqueous solution. Up: As(V). Down:

As(III). (Simulated by MINEQL+4.5)

Occurrence of arsenic

Arsenic is ubiquitous in our environment. It is a component of more than 245

minerals, including elemental arsenic, arsenides, arsentates, arsenites, etc. (Mohan

and Pittman, 2007). A variety of natural activities like weathering of arsenic

Chapter 2

12

containing rocks and sediments, volcanic emissions, atmosphere deposition,

geochemical reactions as well as biological activities could mobilize arsenic species

across minerals, atmosphere and water bodies. With the ever-increasing

industrialization, anthropogenic activities such as mining and agricultural activities

would contribute to the discharge of arsenic. Typically, arsenic could arise from

pesticides, herbicides, crop desiccants, combustion of fossil fuels, mining and

smelting in semi-conductor industries, and then rapidly accumulate to act as a

severe threat to the environment and human health. As estimated, approximately

62,000 tons of arsenic is emitted into the environment per annum, of which 80%

are coming from the copper smelters (Bissen and Frimmel, 2003).

Nowadays, the episode of arsenic pollution has been found in many regions

all over the world, especially in South-west America and Southern Asia

(Ravenscroft et al., 2009). Globally, it was reported that ca.150 million people are

exposed to arsenic contamination from drinking water, and this figure continues to

climb up. More than 45 million people majorly in Asia (Bangladesh and India) still

drink severely arsenic-contaminated water. To elaborate, nearly 16% of the tube-

wells in Bangladesh were unsafe due to the high arsenic level, and 20 million people

in Bangladesh are still using these tube-wells as water sources and suffering a

considerable risk of cancer rooted from the arsenic poisoning. In India, 50 million

people living in regions such as West Bengal are directly exposed to arsenic

containing water and food. Moreover, the threat caused by arsenic contamination

could easily spread owing to globalization nowadays. For instance, enormous

quantities of rock and cement materials from Indonesia are exported to other Asian

Chapter 2

13

countries like Singapore to be used as building materials. These building materials

have the potential to leach arsenic and may lead to arsenic pollution in the new areas.

Health effects and regulation

Arsenic in natural waters is a global threat. Its toxicity has been well analyzed and

clinically studied (Jomova et al., 2011). In general, the seriousness of arsenic

toxicity is dependent upon the mobility and chemistry of particular arsenic species.

Inorganic arsenic compounds are considered significantly more toxic than organic

forms; arsenite is considered as the more soluble and mobile species, and therefore

more toxic in comparison to arsenate.

As a dangerous carcinogen, arsenic could induce severe poisoning on

human health, with acute poisoning that causes vomiting, esophageal and

abdominal pain, and bloody diarrhea. Moreover, long term exposure owing to

arsenic polluted (even at a low concentration) drinking water could lead to skin,

lung, bladder, and kidney cancer as well as pigmentation changes, skin thickening

(hyperkeratosis), neurological disorders, muscular weakness, loss of appetite, and

nausea. The ingestion of high-concentrations of arsenic may lead to encephalopathy

with symptoms such as headache, lethargy, mental confusion, hallucination,

seizures and coma (Bissen and Frimmel, 2003).

Rooted from arsenic’s substantial toxicity, the International Agency for

Research on Cancer (IARC), USEPA and WHO have all classified them as Group

A carcinogen. These international regulation authorities have established a series of

stringent standards for controlling arsenic residuals in drinkable water. In 1975, the

US EPA requested a standard of 50 μg/L as the maximum arsenic level in drinking

Chapter 2

14

water according to the public health service standards. Moving forward, in the year

of 1993, a provisional guideline of 10 μg/L was recommended by the WHO based

on the increasing awareness of arsenic’s toxicity and the progress on analysis

techniques. Following that remark, Germany and US EPA have lowered the

permissible limit of arsenic to 10 μg/L in the year of 1996 and 2006, respectively.

Nowadays, 10 μg/L is the most widely accepted standard concentration allowed for

arsenic in drinking water. Further to that, some regions required even stricter

regulating standards, for instance, arsenic concentration in drinking water must be

controlled as less than 7 and 5 μg/L in Australia and Denmark, respectively (Hashim

et al., 2014).

2.1.2 Chromium

Chemistry of chromium

Chromium is a transition metal that exhibits a complex chemistry. It exists in

oxidation states ranging from +6 to -2, whilst the most common oxidation states are

found in the form of trivalent Cr(III) and hexavalent Cr(VI) (Sharma et al., 2008).

The distribution of compounds containing Cr(III) and Cr(VI) depends on the redox

potential, the pH, and the total chromium concentration, as shown in Figure 2-2. In

surface waters, the ratio of Cr(III) to Cr(VI) varies widely, and relatively high

concentrations of the latter are detected. In general, Cr(VI) salts are more soluble

than those of Cr(III), making Cr(VI) relatively mobile (WHO, 2011).

Chapter 2

15

Figure 2-2. Predominance diagram of chromate in aqueous solution. Distribution

of chromium-related species is complicated, and is dependent on the total dosing

centration of chromium-related species.

Specifically, Cr(VI) exists in solution as monomeric species/ions: H2CrO40,

HCrO4- (bichromate) and CrO4

2- (chromate); or as the dimeric ion Cr2O72-

(dichromate – only exists in very strongly acidic solution). In the pH range of 1-10

and at low concentrations, chromium is present in groundwater as either

monovalent HCrO4- or divalent chromate CrO4

2-. The monovalent form

predominates in acidic water while the divalent form predominates at neutral pH or

above. The monomeric species renders a yellow color to water when Cr(VI)

concentration is greater than 1 mg/L (Owlad et al., 2008; Sharma et al., 2008).

Occurrence of chromium

Chromium is naturally found and mined as oxides: principally as chromite

(FeO∙Cr2O3), crocoite (PbO∙CrO3) or chromic oxide (Cr2O3). In particular, chromite

Chapter 2

16

is widely used for the production of chromium (Slooff et al., 1989). The occurrence

of chromium in natural groundwater has been found in many places (US,

Netherland, Canada, Italy, etc.) all over the globe. Naturally occurring chromium

concentrations in groundwater are generally less than 2 mg/L, but in some areas the

concentration detected reached as high as 120 mg/L (WHO, 2011).

Moreover, chromium is one of the most widely utilized metals in today’s

world and industrial processes, to produce numerous consumer goods as a raw

material. It has been used in the leather tanning and textile dyeing industries, the

manufacture of catalysts, laundry chemicals, pigments and paints, fungicides, the

ceramics and glass industry, and in photography, and for chrome alloy and

chromium metal production, chrome plating and corrosion control (Slooff et al.,

1989). Uncontrolled emissions or waste discharges from industrial sites, landfills or

roadways have great potential for contaminating the fresh waters with relatively

toxic forms of chromium


Chromium as a heavy metal is toxic. Its toxicity is dependent on chemical speciation

and thus the associated health effects are influenced by chemical forms of exposure

(Sharma et al., 2008). Cr(VI) compounds are much more soluble than Cr(III) and

are much more toxic (mutagenic and carcinogenic) to microorganisms, plants,

animals and humans. It can lead to liver and kidney damage, internal hemorrhage

and respiratory disorders. An oral dose of 2-5 g of soluble hexavalent chromium

compound would be fatal to an adult human (Katz and Salem, 1994). Cr(VI) has

been reported to cause cancer in humans and animals through inhalation exposure,

Chapter 2

17

e.g. lung cancers occurred amongst factory workers due to the Cr(VI) compounds.

In contrast, Cr(III) is a nutritionally essential trace element, nontoxic and poorly

absorbed (Sharma et al., 2008). The daily chromium requirement is estimated to be

0.5–2 mg of absorbable Cr(III). However, an excess quantity of chromium would

become toxic to human health. Ingestion of 1-5 g of chromate results in severe acute

effects and death may occur following cardiovascular shock (WHO, 2011).

Owing to the toxic nature of chromium, it brings about many problems to

the environment via producing wastewater, mine wastes and the final ash. The

contaminated soils and aquifers would cause the mortality of habitat creatures and

aquatics. The chromium contamination in groundwater has been found in Mexico,

India and even the USA, including areas such as California, Washington, Indiana

and New Jersey (USEPA, 1997).

To control the risk of chromium contamination, various international

authorities including USEPA, WHO, European Union water directives as well as

Canadian and Australian drinking water quality guidelines have proposed the

guideline for maximum allowable concentration of total chromium in water as 100

µg/L (WHO, 2011). Particularly, the USEPA has classified chromium as group A

human carcinogen (USEPA, 1997).

Chapter 2

18

2.1.3 Fluorine

Chemistry and occurrence of fluorine

Fluorine is a natural trace element and exists in almost all sorts of environments. In

elemental form, it exists as a flammable, irritating and toxic halogen gas, which is

one of the most powerful oxidizing agents known (Jadhav et al., 2015). Besides, as

a highly electronegative element, fluorine often occurs as the reduced form, i.e.

fluoride (F-), which exhibits tendency to conjoin with positively charged ions like

calcium and sodium. The speciation of fluoride species in water is analyzed by the

software MINEQL+4.5 and shown in Figure 2-3.

Figure 2-3. Distribution of fluoride species in aqueous solution. (Simulated by

MINEQL+4.5)

Fluoride is found in plants and animals in trace quantities, as well as being

naturally present in minerals (fluorite, biotites and topaz) and rocks (granite, syenite

and shale) (Bhatnagar et al., 2011). These minerals and rocks are the chief source

Chapter 2

19

of fluoride in the groundwater due to weathering and leaching. Fluoride could

accumulate and mobilize very quickly in groundwater (maximum concentrations

reaching 30-50 mg/L) when the geological, hydrological and climatic conditions

are favorable for dissolution.

Further to that, another source of fluoride is due to the anthropogenic

activities. It could be generated via the agricultural field run-off and infiltration

owing to the use of fertilizers that contain high concentrations of fluoride, and the

industrial waste discharge from industrial sectors like aluminum smelting, glass and

ceramic production, semi-conductor manufacturing, coal-fired power plants, and

beryllium extraction plants (Bhatnagar et al., 2011). The effluents from these

sources have been reported to cause more than 10 to 100 times of the natural

fluoride background concentration in receiving water bodies (Camargo, 2002), with

concentrations ranging from tens to thousands of mg/L (Bhatnagar et al., 2011).

Today, it is estimated that more than 200 million people all over the world

consume drinking water that contains fluoride concentration exceeding the WHO

guidelines of more than 1.5 ppm (WHO, 2011). More than 20 countries have been

identified being affected by excessive fluoride concentration in groundwater,

including India, China, Central Africa and South America (Mohapatra et al., 2009;

Meenakshi and Maheshwari, 2006).


It has been known that minor doses of fluoride can be beneficial, e.g. to prevent the

dental caries amongst children (Harrison, 2005). Nevertheless, this beneficial

concentration range is extremely narrow, and excessive intake could result in

Chapter 2

20

adverse health problems, such as dental and skeletal fluorosis (WHO, 2011).

Fluorosis is a common symptom of high fluoride ingestion, revealed by teeth

mottling in mild cases as well as bone deformities and neurological damage in

severe cases (Harrison, 2005). Furthermore, some studies suggest that fluoride may

hamper the deoxyribonucleic acid (DNA) synthesis, and high concentrations of

fluoride can also affect carbohydrates, lipids, proteins, vitamins and mineral

metabolism (Bhatnagar et al., 2011).

Moreover, fluoride toxicity could take place via numerous ways within

human body. If ingested, fluoride firstly affects the intestinal mucosa, and later in

stomach it can form hydrofluoric acid, followed by gastrointestinal irritation

(Bhatnagar et al., 2011). It would also affect numerous other enzymes, disrupting

oxidative phosphorylation, glycolysis, coagulation and neurotransmission

(Bhatnagar et al., 2011). In addition, it has been reported that a lethal dose of

fluoride at once could disrupt kidney function over short-term exposures both in

humans and in animals (Harrison, 2005), as fluoride can impact on brain and pineal

gland functions. Fluoride exposure can also cause bladder cancer, predominantly

among the workers exposed to high concentration of fluoride in the workplace

(Harrison, 2005).

Having been aware of this, the WHO has established a guideline

concentration of 1.5 mg/L as the maximum contaminant level for fluoride in

drinking water (WHO, 2011). Excessive concentrations of fluoride residuals

detected in water bodies will then require proper treatment to reduce the availability

of fluoride species to a level that is safe for human consumption.

Chapter 2

21

2.1.4 Phosphorus

Chemistry and occurrence of phosphorus

Phosphorus is one of the essential elements for life. As it is highly reactive,

phosphorus is seldom found as a free element form, but rather in the maximally

oxidized state as inorganic phosphate (PO43-) (Huang et al., 2017; Li et al., 2016a).

Phosphate has a chemical structure of tetrahedral arrangement, and normally exists

in water as a result of the speciation of phosphoric acid (H3PO4). In specific, the

pKa values of the phosphate species (H3PO4, H2PO4-, HPO4

2-) are 2.12, 7.21 and

12.67, respectively. The speciation was simulated using the software MINEQL+4.5

and plotted versus the water pH conditions in Figure 2-4. At very acidic conditions,

the trihydrogen phosphate presents as the predominant species; from pH 2.12 to pH

7.21, the dihydrogen phosphate takes over; from pH 7.21 to 12.67, the

monohydrogen phosphate becomes major; and when water pH is more than 12.67,

the phosphate appears to be significant.

Figure 2-4. Distribution of phosphate species in aqueous solution. (Simulated by

MINEQL+4.5)

Chapter 2

22

Phosphate naturally exists in a variety of minerals and rocks in the inorganic

form. Both natural and human activities contribute in the release of phosphate into

the environmental systems. Biological activities by plants, algae and photosynthetic

bacteria could uptake phosphate from water and soils, during which inorganic

phosphate would be immobilized as organic phosphate species. The phosphate

returns to the soil via dead plants and animals as well as animal wastes, which can

be decomposed by microorganisms. In this way, phosphate is recycled in the eco-

system (Falkowski et al., 2008).

Within human bodies, phosphate is a crucial element to the structure of

bones, teeth, many proteins and nucleic acids (DNA and RNA) of animals.

Phosphate is also a constituent of ADP and ATP, which are primarily involved in

the energy production system and energize many body functions including nervous

system, brain cells and muscles. Therefore, it is widely present in food and drinks

to provide nutritional value to living organisms.

Furthermore, the nutritional value of phosphate is used for agricultural

activities (Jiao et al., 2012). With respect to soils without sufficient level of

phosphate availability, additional source of phosphate (fertilizers) must be

introduced so as to sustain proper crop production. Besides, it has been a common

measure for decades in human society to introduce proper pond fertilization with

phosphate for increasing fish growth and controlling water plants and mosquitoes

(Swingle et al., 1963). Studies demonstrated that fish yield could increase by more

than 77% in comparison with that in unfertilized ponds.

In addition to the utilization of its nutritional value, phosphate is also being

used in chemical applications. For instance, phosphate salts are used for the

Chapter 2

23

preparation of pH buffering solutions. Moreover, it is widely used nowadays as

detergents for household washing as well as industrial cleaning (Falkowski et al.,

2008). However, enormous amount of phosphate containing post laundry and dish

washing wastewater enters the domestic sewage system. Without proper treatment

and being discharged into the natural water bodies like rivers, lakes and oceans, the

excessive phosphate may become detrimental to the environment. Typically, 50%

of phosphate wastewater comes from domestic detergents in India (Rao et al., 1998),

whilst in the United States, 20-30% of phosphate in wastewater is due to detergent

use (ReVelle and ReVelle, 1992).

Harmful effects and regulation

Technically, although phosphorus is the mineral nutrient essential for all living

species, excessive presence of phosphorus in water bodies would still lead to severe

problems, i.e. eutrophication in rivers, lakes and seas. Eutrophication normally

induces overgrowth of phytoplankton. The enormous level of nutrition increases the

growth speed of plants and algae, resulting in the overwhelming consumption of

dissolved available oxygen in the water bodies. The resulting algal bloom would

not only cause an aesthetic issue to the communities, but some species of algae may

even be toxic to the environment. This depopulates other aquatic species and thus

deteriorates water quality (Falkowski et al., 2008). In addition to the episodes on

lakes, eutrophication could as well happen in oceans. This is known as red tide

owing to the overgrowth of zooplanktons. The colored toxic tides caused by ocean

eutrophication have been reported for several centuries, which resulted in a serious

deterioration in water quality.

Chapter 2

24

The phenomena of dangerous eutrophication could be found in many

countries all over the world. For instance, in 1993, the anabaena and microcytic

blooms occurred and even polluted the drinking water in Brazil. Approximately

2000 people were affected, and 88 persons died in the accident (Pouria et al., 1998).

Moreover, in 1981, cylindrospermopsis blooms caused more than 141

hospitalizations in Australia (Saker and Neilan, 2001).

To prevent eutrophication, environmentally friendly fertilizers and

detergents without phosphate are promoted nowadays. More importantly, excessive

phosphate should be carefully removed in wastewater effluents before discharging

to water bodies. The criteria for controlling total phosphorus are recommended by

the US EPA and the Australian Water Quality Guidelines for Fresh and Marine

Waters. Specifically, no more than 0.1 mg/L phosphorus contaminant level can be

maintained in rivers and streams, whilst no more than 0.05 mg/L is allowed for

lakes and reservoirs (Cothern and Lappenbusch, 1983).

2.1.5 Selenium

Chemistry and occurrence of selenium

Selenium is a naturally occurring trace element, present under the forms as

elemental selenium Se0, selenide Se(-II), selenite Se(IV), selenate Se(VI) and

organic selenium (Santos et al., 2015; Sharma et al., 2014). The different oxidation

states are associated with different chemical and toxicological properties.

Specifically, selenate Se(VI) is the fully oxidized selenium form and can be present

in aqueous media as biselenate (HSeO4−) or selenate (SeO4

2−), with a pKa value of

1.8 (Seby et al., 2001). Selenate predominates under oxidizing conditions, with

Chapter 2

25

great solubility and low adsorption potential. Further to that, selenite Se(IV) is

present in moderate redox potential range and neutral pH environments (Fernádez-

Martínez and Charlet, 2009). In aqueous solution, Se(IV) exists as a weak acid

under the forms of selenious acid (H2SeO3), biselenite (HSeO3−), or selenite

(SeO32−), with corresponding pKa values of 2.70 (H2SeO3/HSeO3

−) and 8.54

(HSeO3/SeO32−) (Seby et al., 2001). In the pH conditions typically found in natural

waters, selenium species will be predominantly HSeO3− or SeO4

2−, under reducing

or oxidizing environment, respectively. In water and wastewater treatment,

selenium speciation can however be markedly varying, since the other co-existing

metal ions in the water streams may affect its speciation (Torres et al., 2011).

Simulating the speciation using the software – MINEQL+4.5, the species

distribution of Se(IV) and Se(VI) as a function of solution pH can be obtained and

plotted in Figure 2-5.

Chapter 2

26

Figure 2-5. Distribution of selenium species in aqueous solution. Up: Se(VI).

Down: Se(IV). (Simulated by MINEQL+4.5)

Selenium, a natural constituent of the earth's crust, is widespread over all

the earth compartments: in rocks, soil, water, air, vegetation and food. Selenium

concentrations in soils vary substantially around the world. In most soils selenium

content varies from 0.01 to 2 mg/kg (Fernádez-Martínez and Charlet, 2009; Floor

and Roman-Ross, 2012), whilst higher than 5 mg/kg can also be found in some

areas of the world (Western USA, Canada, France and Germany) (Sigrist et al.,

2012). Selenium in soils can be taken up by plants, entering in the food chain and

reaching in this way up to animals and humans. When accumulated by plants,

inorganic Se is transformed into organo-selenium species, which have important

implications on human nutrition and health (Jaiswal et al., 2012). World average

selenium concentration in freshwater is 0.02 μg/L (Fernádez-Martínez and Charlet,

2009) and below 0.08 μg/L in seawater (Mitchell et al., 2012). Groundwater

Chapter 2

27

generally contains higher selenium levels than surface waters, due to its contact

with rocks. In the atmosphere (non-volcanic areas), natural background levels of

selenium are quite low, ca. 0.01-1 mg/m3 (Fordyce, 2013). Moreover, selenium is

also present in food, especially in protein-rich products such as eggs, meat, chicken,

fish and cereals. This is because selenium presents a similar physicochemical

property as sulfur and can replace it in amino acids.


Environmental contamination by selenium may occur due to natural and

anthropogenic sources. Natural sources include the weathering of selenium-

containing rocks and soils and volcanic eruptions. Human sources include coal

combustion, mining, agriculture, oil refining, insecticide production, glass

manufacture and photocells (Fernádez-Martínez and Charlet, 2009). Typically,

selenium is a highly volatile element in coal and can be largely released in the vapor

phase, mainly as SeO2 and SeO gases (Yan et al., 2001). Furthermore, most

industrial wastewater contains selenium, in a typical concentration of 1-20 mg/L

(Vance et al., 2009). Recently, seleniferous agricultural drainage wastewater has

become a relevant diffuse pollution source of selenium around the world (Tuzen

and Sari, 2010).

Although a controlled dose of selenium as micronutrient is of biological

importance for animals and humans, the boundary between toxicity and deficiency

is very narrow (Thiry et al., 2012). Once the intake turns excessive, selenium

species, especially the inorganic ones (mainly selenite and selenate), could induce

acute toxicity to living cells (Mézes and Balogh, 2009).

Chapter 2

28

Several situations of overwhelming Se concentrations in mammals, fish,

waterfowl and birds have been observed worldwide (Lemly, 2014). For instance,

pollution episodes were early documented in Kesterson Reservoir, California's San

Joaquin Valley (Ohlendorf, 2002). In British Columbia, Canada, high Se levels

were measured in trout tissues due to Se mobilization from a surface coal mining to

the rivers (McDonald and Strosher, 1998). More recently, teratogenic effects, spinal

and craniofacial malformations were reported in fish living in a lake receiving

selenium contaminated wastewaters by coal-fired power plants (Lemly, 2014).

Selenium risks to aquatic life derive from food and from the direct exposure to

contaminated water. It bioaccumulates in the aquatic food chain and becomes a

source of selenium in fish feeding (Lemly, 2014). As a result, the hazard assessment

for aquatic organisms of European Chemicals Agency indicates the predicted no-

effect concentration with respect to selenium shall be limited as 2.67 and 2 μg/L,

considering freshwater and marine water, respectively.

2.1.6 Silica

Chemistry and occurrence of silica

Silica is the most prevalent substance on Earth (Sheikholeslami and Zhou, 2000).

In much of the world, silica is the major constituent of sand and is found throughout

the Earth's continental crust in a crystalline form named quartz (Sheikholeslami and

Tan, 1999). Other crystalline forms of silica exist including tridymite and

cristobalite, both of which can be interchangeably formed from quartz by altering

temperature (Iler, 1979). In addition to that, silica could exist in water through

Chapter 2

29

dissolution. The initial dissolution of silica may be represented by the chemical

equilibrium (Sheikholeslami and Tan, 1999): SiO2 + 2H2O ↔ Si(OH)4.

Since Si(OH)4 is deemed monomeric, the compound is commonly referred

to as monosilicic (or orthosilicic) acid. Monosilicic acid is a relatively weak acid

with a first and second pKa value of 9.9 and 12.6 respectively (Hamrouni and

Dhahbi, 2001). Its speciation across water pHs are plotted in Figure 2-6, according

to the simulation results of MINEQL+4.5

Figure 2-6. Distribution of silica species in aqueous solution. (Simulated by

MINEQL+4.5)

Different water streams, including wastewater, tend to contain different

concentrations of silica. In natural waters, the silica content typically ranges

between 1 to 30 mg/L. The silica content of well water is said to be between 20 to

Chapter 2

30

100 mg/L, whilst in brackish waters, the concentration can still remain as high as

100 mg/L (Iler, 1979).

Furthermore, it was found that if the concentration remains below 100 mg/L

at standard conditions, monosilicic acid could exist exclusively in solution for long

periods. Nonetheless, in more concentrated solutions, monosilicic acid will

polymerize via a SN2 mechanism to form polysilicic acids of different shapes and

increasing molecular weights (Neofotistou and Demadis, 2004). Highly

polymerized forms of silica (larger than 50 Å) are referred to as colloidal silica,

with even larger species being called particulate silica (Iler, 1979).

The rate of polymerization is highly dependent on pH, with the process

believed to be catalyzed by hydroxyl ions. In particular, the rate is very slow

between pH 2 and 3, but between pH 2 and pH 7, monosilicic acid molecules would

polymerize into dimers and cyclic silica, which go on to form large nuclei (Iler,

1979). The nuclei have a great tendency to aggregate into long chains, known as gel

networks, which would cause severe industrial problems (see next section). This

phenomenon is believed not to occur to a great extent at higher pH values, with the

nuclei continuing to grow to larger sizes. An explanation for this is that at higher

pH values the surface of each silica molecule is covered with hydroxyl ions, causing

the nuclei to repel each other, and thus, grow independently. Nevertheless, it has

been found that certain salts supplying cations like Ca2+ and Mg2+ to solution that

could neutralize the charged surfaces of the nuclei thus enabling aggregation.

Therefore, it is important to investigate the silica behavior in water chemistry with

co-existing Ca2+ and Mg2+ cations.

Chapter 2

31


Silica exhibits a great tendency to form particulates through the polymerization of

monosilicic acid or by the coagulation of existing colloidal particles. These particles

tend to deposit onto vacant solid surfaces, which therefore leads to the

fouling/scaling of heat and mass transfer surfaces in industrial units (Ning, 2010).

The phenomenon is detrimental, as even when the entire surface becomes covered,

more silica could still deposit onto the silica already in place, thus forming thicker

deposits. Within industry and research, there has been a concerted effort to

understand and quantify the severity of this phenomena on several industrial process

units, e.g. reverse osmosis (RO) membranes and cooling water towers.

RO membrane technology has been commonly used to treat aqueous

effluent streams within the desalination and water purification industry. Their

advantages stem from their good scale-up ability and relatively low energy

consumption (Koo et al., 2001). However, these and other such positives are

undermined by the costs and other losses associated with membrane fouling. For

instance, as silica deposits onto the membrane surface and thickens it, the ever-

increased pressure drop would result in higher energy costs. Significant production

losses have to be borne due to plant shutdowns that are required for scale removal.

Cleaning the membrane may also bring about early damage, thus shortening its

lifetime (Malaeb and Ayoub, 2011).

Besides, when enough water is recovered through the membrane, the feed

would become sufficiently concentrated. For instance, a solution with an initial

concentration of 120 ppm silica reportedly became supersaturated (300 mg/L) at a

water recovery of around 70% (Sahachaiyunta et al., 2002). Normally, to avoid

Chapter 2

32

further damage to the membranes, the filtration can be stopped at the onset of

supersaturation. However, doing so will lead to large quantities of high-silica water

being discarded. Disposing of this unprocessed water represents the most

unattractive option for those in drought stricken areas, which highlights the need

for effective silica removal, or control strategies.

Even though the silica causes no fouling problem on RO membranes, it was

reported that the concentration of the permeate for some RO membranes remains as

high as 5.5 ppm. This may be sufficient to foul downstream process units such as

high-temperature boilers. In another example, freshwater is used in various

industrial sectors for cooling purposes and this cooling is traditionally carried out

within heat exchangers. Upon exiting these units, the temperature of the cooling

water is increased, and for the fluid to be reused it must be first cooled itself. For

this purpose, many facilities use cooling towers. Water-owing downwards from the

top of the tower comes into contact with the upcoming colder air, which provides

evaporative cooling. For decades, industry have incorporated "fills" within cooling

towers to facilitate this process (Dubin, 1991).

If during evaporative cooling, the water contains silica that exceeds the limit,

scaling will occur onto the fill. This phenomenon reduces the surface area for heat

transfer, increasing the temperature of the water as it enters the heat exchanger and

the fluid supplied to cool. Similar to the case of reverse osmosis membranes, this

results in a need to frequently clean the effected units, which causes unnecessary

costs and potential damage.

Before silica has the opportunity to foul surfaces, a common idea is to pre-

emptively replace the water with a fresh supply, which will again come from natural

Chapter 2

33

sources. This option may not be economically viable for those in the vicinity of only

brackish waters, or if located in dry areas such as deserts. The facilities at Xinjiang

oilfield in China are examples of such places where operations are made more

difficult due to inadequate local water supplies (Zeng et al., 2007). Even if a supply

of freshwater is readily available, having to replace cooling water continuously

presents a heavy operational burden on any facility. Consequently, it is important

to be able to efficiently remove silica from the water to allow it to be continuously

recycled through the process without the threat of precipitation. To that end, there

is significant research need for effective methods by which silica’s adverse effects

on systems can be mitigated.

2.2 Adsorption Technologies

2.2.1 Adsorption

In theory, adsorption is a phase process that is widely used in practice to remove

substances from fluid phases (gases or liquids) (Dąbrowski, 2001). It also produces

an enrichment of chemical species from a fluid phase on the surface of a liquid or a

solid. In the context of water treatment, adsorption has been proved as an efficient

removal process for an array of solutes. Basically, molecules or ions are removed

from the aqueous solution onto solid surfaces. The solid surface is characterized as

the active, energy-rich sites that are capable of interacting with solutes in the

adjacent aqueous phase owing to the specific physical or chemical properties.

The basic terms used in adsorption studies are shown in Figure 2-7 (Samuel

and Osman, 1987). The solid material that provides the surface for adsorption is

Chapter 2

34

referred to as adsorbent; the species that are to be adsorbed are named adsorbates.

By changing the properties of the liquid phase, e.g. concentration, temperature, pH,

etc., the adsorbed species can be released from the surface and transferred back into

the liquid phase. This reverse process is called desorption.

Figure 2-7. Basic terms and illustration of adsorption.

Since adsorption is a surface process, the surface area is a key quality

parameter of adsorbents. Engineered adsorbents are typically porous materials with

surface areas in a range of 100-1000 m2/g (Ali, 2012). Such large surfaces are due

to the internal surfaces constituted by the pore walls rooted in the material’s high

porosities.

Moreover, depending on the adsorption enthalpy, adsorption can be

categorized as physical adsorption (physisorption), chemical adsorption

(chemisorption) or in-between complexation (Dąbrowski, 2001). Generally, physi-

sorption is dependent on the van der Waals forces (dipole-dipole interactions,

dispersion forces, induction forces), which are fairly weak interactions. Chemi-

sorption is based on chemical reactions between the adsorbate and the adsorption

Chapter 2

35

sites. It should be noted that the differentiation between physisorption and

chemisorption is very much arbitrary and the boundaries are fluid.

The practice-oriented adsorption theory consists of three main elements:

equilibrium, kinetics, and dynamics (Dąbrowski, 1999). To briefly elaborate,

adsorption equilibrium describes the dependence of the adsorbed amount on the

adsorbate concentration at a specific temperature, which can normally be expressed

in the form of an adsorption isotherm. Adsorption kinetics describes the time

dependence of the adsorption process, i.e. the increase of uptake with respect to

time, or alternatively the decrease of liquid-phase concentration versus time.

Typically, the adsorption rate is determined by the slowest mass transfer process

from the liquid to the solid phase. Moreover, as adsorption is frequently realized

within a column bed, the dependence is not only on time, but space is also referred

to in adsorption dynamics.

In general, the adsorption equilibrium makes the basis of all adsorption

models (Samuel and Osman, 1987). Knowledge about the adsorption equilibrium is

a precondition for the application of both kinetic and dynamic adsorption models.

To simulate adsorption dynamics, information regarding adsorption equilibrium as

well as adsorption kinetics is essential. As a consequence, in academic research

studies, adsorption equilibrium is always the first to-be-investigated parameter, in

order to evaluate the capability of developed adsorbents. In this thesis, only lab-

scale adsorption processes in batch mode are within the scope of study, for the

understanding of material capabilities.

Chapter 2

36

2.2.2 Functional adsorbent for water decontamination

When employing adsorption for water decontamination, the adsorbent materials

play a key role in determining the efficacy of treatment. Materials with high surface

area, multiple functionalities and porous structures are believed to be promising

ones (Ali, 2012). In regards to anionic species removal, a great variety of materials

have been developed in the past decades, including carbon-based materials,

biological materials, metal oxides, and synthetic functional materials (layered

double hydroxides and zeolites). Herein, a highly general survey on the respective

categories of materials is provided, whereas more detailed and relevant evaluations

on the adsorbents can be found in the discussion sections of each studies (vide infra).

Carbon-based material

Carbon-based materials such as charcoals and activated carbons must be the oldest

adsorptive materials ever used in history. It normally works as a universal adsorbent

that has been widely used as an all-purpose adsorbent since 1930s (Du et al., 2009).

Very simply, activated carbon can be made from coconut shells, wood char, lignin,

petroleum coke, bone-char, peat, sawdust, carbon black, rice hulls, sugar, peach pits,

fish, fertilizer waste, waste rubber tire and so on (Pollard et al., 1992). The large

micro- and meso-pore volumes and the resulting high surface area are the major

advantages associated with the activated carbon adsorbents.

Extensive studies have been done to evaluate the capability of activated

carbon (lab-derived and commercial ones) for water decontamination. One classic

study by Eguez and Cho (1987) examined the adsorption of both As(V) and As(III)

onto activated charcoal as functions of pH and temperature. The results suggested

Chapter 2

37

that physisorption due to weak Van der Waals forces occurred during the adsorption

process.

Moreover, novel carbon-based materials such as graphene, graphene oxide

and carbon nanotubes have been developed in recent years, and they have been

explored for anionic species removal from wastewater. Mishra and Ramaprabhu

(2011) synthesized the graphene sheets by hydrogen induced exfoliation of

graphitic oxide followed by functionalization. These functionalized graphene sheets

could simultaneously remove high concentration of inorganic arsenic species – both

As(III) and As(V) – from aqueous solutions using supercapacitor based water filter

(capacity ca. 130 mg/g). Besides, Kumar et al. (2014) reported that the hybrids of

single-layer graphene oxide with manganese ferrite magnetic nanoparticles

demonstrated effective removal of arsenic from contaminated water. Combining the

reusability, ease of magnetic separation, high removal efficiency, high surface area,

and fast kinetics do these nanohybrids make attractive candidates as cost-effective

adsorbents for anionic species removal from contaminated water. In addition, an

amorphous alumina-impregnated carbon nanotube was prepared for defluoridation

(Li et al., 2001). The results showed that the adsorption capacity of Al2O3/carbon

nanotubes was 13.5 times higher than that of pristine carbon nanotubes.

Nevertheless, the production cost for these novel carbon materials is considered

relatively high for wide applications in wastewater treatment.

Chapter 2

38

Biomaterial

Biomass-based materials were reported to be promising as a type of cost-effective

adsorbent for the removal of anionic pollutants. Researchers have looked into chitin,

chitosan, cellulose, water hyacinth and different biomasses in various studies.

Chitin is a long, unbranched polysaccharide derivative of cellulose where

the hydroxyl groups are replaced by the acetyl amino groups. Chitosan is further

derived from chitin by deacetylation process using concentrated base at high

temperature. The wide application of chitin and chitosan for the uptake of anionic

species is mainly due to their high content of hydroxyl and amino groups, the high

reactivity of primary amino groups, and the polymer chain for efficient

complexation with ions. One example by Chen et al. (2008) studied the adsorption

of arsenic on molybdate-impregnated chitosan beads in both batch and continuous

modes. It was found that the optimal removal of arsenic species can be obtained at

pH 5, and the maximum adsorption capacities for As(III) and As(V) were 1.98 and

2.00 mg-As/g, respectively.

Open celled cellulose sponge with anion-exchange and chelating properties

has been developed. The adsorption of inorganic arsenic from water using cellulose

sponge with and without Fe(III) loading was investigated by Muñoz et al. (2002).

As(V) was effectively adsorbed by both the virgin and the Fe(III)-loaded sponges

across the pH range of 2-9 (optimal at pH 7), whilst only the Fe(III)-loaded sponge

can slightly adsorb As(III) in the pH range of 5-10 (optimal at pH 9). The maximum

adsorption capacities of As(V) and As(III) by the Fe(III)-loaded adsorbent were

1.83 mmol-As/g (pH∼4.5) and 0.24 mmol-As/g (pH∼9.0), respectively.

Chapter 2

39

The water hyacinth (Eichornia crassipes) is a member of the pickerelweed

family (Pontederiaceae). The plants, as one of the most productive plant groups on

earth, have varied sizes ranging from a few centimeters to over a meter in height.

Al-Rmalli et al. (2005) utilized dried roots of the water hyacinth for the rapid

removal of arsenic. More than 93% of As(III) and 95% of As(V) can be removed

from a solution containing 200 μg/L arsenic within the contact time of 60 min. The

residual arsenic concentration was less than the regulated maximum value (10 μg/L)

for drinking water recommended by the WHO and US EPA. It was also found that

the arsenic removal capability by water hyacinths is dependent upon the initial

arsenic concentration, the amount of water hyacinth used, the exposure time and the

presence of air and sunlight (Misbahuddin and Fariduddin, 2002).

In addition, Sari and Tuzen (2010) studied the biosorption characteristics of

the macrofungus (Inonotus hispidus) biomass for arsenic removal from aqueous

solution using. The biosorption capacities of I. hispidus for As(III) at optimum

conditions of pH 6 and As(V) at pH 2 were 51.9 mg/g and 59.6 mg/g, respectively.

They (Tuzen and Sari, 2010) also presented that the Se(IV) biosorption from

aqueous solution by dead green algae (C. hutchinsiae) biomass. The maximum

biosorption capacity of C. hutchinsiae biomass for Se(IV) was found to be 74.9

mg/g at pH 5.0 and 20 °C.

Metal oxide

More importantly, metal-based materials owing to their specific affinities have been

extensively studied for anions uptake. These materials can be obtained from the

nature or synthesized in the lab, typically including different forms of iron-based,

Chapter 2

40

aluminum-based, zirconium-based, and rare-earth-metal-based materials, as well as

some binary mixed-component metal oxides.

First of all, many studies have been conducted using iron oxides,

oxyhydroxides and hydroxides. For instance, it was reported that iron oxide

exhibited an adsorption capacity of 8.21 mg/g for phosphate removal (Zeng et al.,

2004). Badruzzaman et al. (2004) investigated the performance of granular ferric

hydroxide on arsenic removal in potable water systems. The BET study indicated a

specific surface area of 235 m2/g. The obtained pseudo-equilibrium adsorption

density of As(V) was 8 µg-As/mg-dry material with the As(V) concentration at

liquid phase as 10 µg/L. Further to the performance investigation, researchers also

explored the interaction between arsenic and ferric hydroxide using density

functional theory methods (Zhang et al., 2005). It was found that bidentate and

monodentate corner-sharing complexes were formed between As and Fe(III)

octahedra through the comparison of calculated and experimental measurement of

As-O and As-Fe bond distances. Similarly, manganese oxides (MnO2) with its

oxidation potentials and adsorptive activities were applied for anionic species

removal. It is used for the oxidization of As(III) to As(V), and the subsequent

adsorption of As(V) at pH below 7 (Deschamps et al., 2005; Bochkarev et al., 2010).

Deschamps et al. (2005) identified that the adsorption of As(V) by Mn-minerals

was maximum at pH 3.0 of 8.5 mg/g for As(V).

Secondly, various phases of aluminum oxides, hydroxides and

oxyhydroxide are increasingly being employed as functional adsorbents for the

detoxification of water and wastewater contaminated with anionic pollutants. These

materials are present abundantly as minerals, and normally possess a great surface

Chapter 2

41

area and porosity. In particular, activated alumina is one effective aluminum

compound that has been categorized by US EPA as the Best Available Technology

(BAT) for the removal of various aquatic pollutants including arsenic, fluoride,

uranium and selenium. It was reported that α-Al2O3 can be loaded with selenite

species with greater than 95% adsorption (Peak, 2006). The X-ray absorption

spectroscopy (XAS) study unveiled that selenate forms outer-sphere surface

complexes at pH 3.5 but inner-sphere monodentate surface complexes at pH 4.5

and above. Moreover, the potential of α-Al2O3 for the adsorption of fluoride anions

has also been tested (Valdivieso et al., 2006). It was found that fluoride adsorption

followed a Langmuir-type isotherm and was influenced by the surface density of

hydroxyl groups. Besides, the interaction of oxyanions including selenate, selenite

and chromate with the surface of hydrated γ-Al2O3 was systematically studied

(Elzinga et al., 2009). The results suggested that pH governs the uptake of

oxyanions onto γ-Al2O3 as it affects the surface charge, concentration of OH- ions

that could compete with oxyanions for surface sites and oxyanion protonation state.

The adsorption of the oxyanions on γ-Al2O3 decreases with the increase of pH

values. Selenite showed complete uptake at pH < 6.0, while selenate uptake

decreased with increasing pH and chromate showed maximum uptake at pH 5.0 (89%

uptake). The formation of inner- and outer-sphere complexes respectively in case

of selenite and selenate has been confirmed by the X-ray absorption fine structure

(EXAFS) results.

Thirdly, zirconium-based nanoparticles prepared by Ma and coworkers

demonstrated extremely efficient uptake for arsenic species (Ma et al., 2011). The

maximum adsorptive capacities were reported to reach more than 200 mg/g for

Chapter 2

42

As(V) at pH 3.2, and 138 mg/g for As(III) at pH 8~9, respectively. The uptake was

far better than most adsorbents reported in the literature (Ma et al., 2011). The

nanoparticles also demonstrated efficiency for defluoridation with a maximum

uptake of up to 97.48 mg-fluoride/g at pH 4.0. Moreover, synthetic amorphous

zirconium oxide nanoparticles were applied for the adsorptive removal of arsenic

species from wastewater (Cui et al., 2012). The am-ZrO2 nanoparticles had a high

specific surface area of 327 m2/g, large meso-pore volume of 0.68 cm3/g, and a

dense amount of hydroxyl groups on the surfaces. The particles exhibited excellent

adsorption performance on both As(III) and As(V) without pre-treatment at near

neutral conditions. The inner-sphere complex mechanism was proposed to describe

the adsorption behavior. Furthermore, Bang et al. (2005b) evaluated the

performance of granular titanium dioxide (TiO2) on arsenic removal from

groundwater. Like zirconium composites, the adsorbents worked better in acidic

conditions for arsenate removal. The excellent performance of TiO2 for arsenic

removal can be attributed to its high surface area and the presence of high-affinity

surface hydroxyl groups. The inner-complexes between arsenic and Ti atoms were

formed during the arsenic adsorption process (Pena et al., 2006).

In addition to the transition metals, rare-earth metal oxides have exhibited

even more promising ability in anions uptake, due to the chemical stability, non-

toxicity and high adsorption capacity. Tokunaga et al. (1997) investigated the As(V)

removal using lanthanum hydroxide (LH), lanthanum carbonate (LC), and basic

lanthanum carbonate (BLC). Two mechanisms were proposed being involved at

different pH conditions. In neutral to alkaline pH, La would not dissolve and the

exchange between CO32- or -OH groups with the arsenic species took place. On the

Chapter 2

43

other hand, in acidic pH, the dissolved La ion would precipitate out in the form of

insoluble lanthanum arsenate (LaAsO4). Moreover, Li et al. (2012) synthesized

hydrous cerium oxide (HCO) nanoparticles through a facile precipitation method

and investigated their adsorption performance. It was found that, at neutral pH, the

arsenic adsorption capacity of HCO reached more than 170 mg/g for As(III) and

107 mg/g for As(V). Further to that, Yu et al. (2015a) combined the hydrous cerium

oxide onto graphene, which demonstrated an extremely rapid adsorption rate for

arsenic removal. More than 88% of the equilibrium adsorption capacity was

realized in the initial 20 min. This can be ascribed to the great extent of

dispersion/distribution of cerium oxide nanoparticles on the thin graphene sheet,

which avoids the aggregation phenomenon that always occurred for metal oxide

nanoparticle adsorbents due to their high surface energy and inhibited the efficient

mass diffusion. The 2D graphene did provide a great surface for the attachment of

active metal ions or metal oxides, facilitating a rapid adsorption rate and potential

to be applied in practical applications.

Besides single component of metal oxides, researchers tried to develop

some binary mixed-component metal oxides to improve the materials’ usability. For

instance, they incorporated ferric content into various materials to facilitate the

separation of the spent materials through magnetic forces. Zhang et al. (2007)

developed a novel Fe-Mn binary oxide adsorbent for arsenic removal. The

adsorbent was prepared by a simultaneous oxidation and co-precipitation method.

The synthetic adsorbent provided the maximum adsorption capacities of 132.75

mg-As/g for As(III) and 69.75 mg-As/g for As(V), respectively. Zhang et al. (2005)

reported a Fe-Ce composite for effective water decontamination. The quantitative

Chapter 2

44

analysis of the XPS narrow scan results of O 1s spectra indicated that the bimetal

composite adsorbent had higher content of hydroxyl groups (30.8%) than CeO2 and

Fe3O4 (12.6% and 19.6%), which was responsible for the enhanced removal of

anionic contaminants such as arsenic and fluoride. In specific, it has been reported

in the literature that Fe-Ti oxide nanoparticle, sulphate-doped Fe3O4/Al2O3

nanoparticle, zirconium (IV)-metalloporphyrin grafted Fe3O4 nanoparticle, etc. are

efficient for fluoride removal from wastewater (Mohapatra et al., 2009).

With regards to these studies, a quick summary can be made at this stage.

Basically, metal oxides are generally synthesized with a specific surface area of

several hundred square meters per gram. The higher the surface area, the quicker

the anticipated adsorption process. Moreover, functional groups such as hydroxyl

groups are important for anionic species binding. Owing to the advantageous

affinity, metal-based materials are regarded as one of the most effective materials

for anions removal. However, it must be emphasized that some of these metals are

heavy metal elements at the same time. They can be toxic if being released into the

treated effluent. It is therefore extremely vital to constantly monitor the

concentrations of these metal elements. Toxicity studies are required to fully

understand the leaching behaviors of the metal elements whether it could lead to

risks to the safety of drinking water.

Chapter 2

45

Synthetic mineral materials

Recently, scientific communities are fascinated about synthetic functional materials

and their promising potential in adsorption processes. Researchers reference to

natural materials as a platform to design, synthesize and optimize the materials

based on the requirements of specific adsorption functions. Typically, two main

categories of functional materials have attracted substantial attention for adsorptive

separations in both scientific and industrial sectors: layered double hydroxides

(LDHs) as well as zeolites (Ali, 2012). They are both naturally occurring but also

economical to be synthesized and functionalized.

LDHs are lamellar mixed hydroxides containing positively charged main

layers and undergo anion exchange chemistry (Goh et al., 2008). The structure of

LDHs is based on positively charged brucite-like sheets and the positive charges

are balanced by intercalation of anions in the hydrated interlayer regions. LDHs

have relatively weak interlayer bonding and, as a consequence, exhibit excellent

ability to capture organic and inorganic anions. The most appealing properties of

LDHs include the large surface area and good thermal stability. In recent years,

many studies have been devoted to investigating the ability of LDHs to remove

inorganic contaminants, such as oxyanions (e.g. arsenite, arsenate, chromate,

phosphate, selenite, selenate, borate, nitrate, etc.) and monoatomic anions (e.g.

fluoride, chloride, bromide, and iodide), from contaminated waters by both surface

adsorption and anion exchange to the interlayer anions in LDH structure (Goh et al.,

2008).

As reported in literature, the affinities of LDHs for oxyanions can be

generally summarized into the following ranges: 0.1-80 mg/g LDHs for arsenite

Chapter 2

46

As(III); 5-105 mg/g LDHs for arsenate As(V); 9-160 mg/g LDHs for chromate

Cr(VI); 5-50 mg/g LDHs for phosphate; 30-270 mg/g LDHs for selenite Se(IV);

10-20 mg/g LDHs for borate; and 1-5 mg/g LDHs for nitrate. It is also evident that

the oxyanion adsorption on LDHs is strongly influenced by a calcination process

during LDH synthesis. For instance, the adsorption of As(V) can be increased from

105 to 615 mg/g if LDHs are calcined (Lazaridis et al., 2002; Kiso et al., 2005). For

Cr(VI), the adsorption capacities of the calcined LDHs are generally reported to be

more than 50 mg/g (Ye et al., 2004; Alvarez-Ayuso and Nugteren, 2005), whereas

the Cr(VI) adsorption capacities of the uncalcined LDHs are usually reported to be

less than 25 mg/g (Lazaridis et al., 2004; Terry, 2004; Alvarez-Ayuso and Nugteren,

2005). In the case of phosphate adsorption on LDHs, the calcined LDHs also show

generally higher adsorption capacities (34–82 mg/g) than the uncalcined LDHs (29–

47 mg/g). After all, the greater adsorption capacities of the calcined LDHs may be

attributed to their larger surface areas of up to 200 m2/g, compared to less than 100

m2/g for the uncalcined LDHs.

Furthermore, zeolites are also an important class of functional adsorbents

that comprise of a broad range of porous crystalline solids (Wang and Peng, 2010).

Natural zeolites are hydrated aluminosilicate minerals of a porous structure with

valuable physicochemical properties, such as ion exchange, molecular sieving,

catalysis and adsorption. Their structures are based essentially on tetrahedral

networks which encompass channels and cavities. Although previously, zeolites

were thought to be consisting only of open and fully crosslinked framework

structures of corner-sharing SiO4 and AlO4 tetrahedra, in recent years extensive

isomorphous substitution of framework atoms and numerous structural analogues

Chapter 2

47

of aluminosilicate zeolites have also been researched on and used as adsorbents for

a range of inorganic pollutants.

Natural zeolite has been tested for defluoridation. Diaz-Nava et al. (2002)

evaluated the fluoride adsorption on a natural Mexican heulandite–clinoptilolite. It

was found that retention of fluoride was similar for the untreated material and

treated samples with sodium, calcium, lanthanum, and europium. The fluoride

retention was proposed through occlusion and adsorption of fluoride on zeolite.

Samatya et al. (2007) prepared metal ion (Al3+, La3+ and ZrO2+) exchanged zeolites

for fluoride removal from water on a Turkish clinoptilolite. The percent removal of

fluoride aqueous solution containing 2.5mg F/L was found to be 94% using the

metal loaded zeolite at an adsorbent concentration of 6.00 g/L.

Moreover, it has been known that metal chromium is a highly toxic metal.

Its presence in water is generally in Cr(III) and Cr(VI). Compared with Cr3+, Cr(VI)

state is of particular concern due to its higher toxicity. Ghiaci et al. (2004) modified

the clinoptilolite with surfactants and tested the resultant materials in chromate

removal from aqueous solutions. It was found that the maximum chromate

adsorption could reach 20 µmol/g. Cordoves et al. (2008) also reported a study of a

surfactant-modified clinoptilolite for the removal of Cr(VI). It has been

demonstrated that the affinity distribution analysis combined with the Freundlich

binding model allows the characterization of the material’s binding properties for

Cr(VI).

Furthermore, Dousova et al. (2006) studied the adsorption of arsenate from

aqueous solution on three adsorbents: metakaoline, clinoptilolite-rich tuff, and

synthetic zeolite, in both untreated and Fe2+-treated forms. It was found that the

Chapter 2

48

adsorption capacity of Fe2+-treated adsorbents increased significantly from about

0.5 to more than 20.0 mg/g, which represented more than 95% of the total As

removal. Combined with other studies, the results in general suggested that the

arsenic uptake by synthetic zeolite adsorbents is dependent upon the precedence of

zeolitic material, the nature of arsenic chemical species, pH as well as the

characteristics of modified-natural zeolites.

2.3 Metal-Organic Materials

2.3.1 General introduction

Over the last at least three decades, the science of porous solid materials has become

one of the most intense areas of study for chemists, physicists, and materials

scientists. These materials have found a large number of applications in many fields,

such as adsorption, separation and purification, as well as catalysis. Porous solids

acting as adsorbents or membrane materials are playing key roles in separations and

purifications of various chemicals that we encounter in our daily activities, directly

or indirectly (Ali, 2012).

However, there are a few drawbacks associated with the traditional porous

adsorbents, including: 1) low to moderate surface areas that limit the number of

sites available for adsorption, 2) lack of tunability making specific selectivity

difficult to achieve (Khan et al., 2013). Explorations of advanced porous materials

for these applications are therefore an intense subject of scientific research.

Metal-organic frameworks (MOFs), a new class of porous solid materials,

emerged approximately two decades ago and have since quickly developed into a

Chapter 2

49

fruitful research field (Zhou and Kitagawa, 2014). MOFs are generally defined as

the crystalline materials formed by bridging the inorganic metal ions or metal

clusters and the organic linkers through metal-ligand coordination bond with great

uniformity over three dimensions (Zhou and Kitagawa, 2014; Zhou et al., 2012).

Figure 2-8. One typical example of MOF, UiO-66: (a) theoretical cluster unit, (b)

SEM morphology of crystals.

In the history of MOF studies, because of the lack of a generally accepted

definition during the development of this new type of hybrid material, several other

parallel appellations have appeared and are currently being used (Zhou et al., 2012).

Among them, porous coordination polymer (PCP) seems to have been the most

widely adopted, followed by porous coordination network (PCN). Others include

MCP (microporous coordination polymer), ZMOF (zeolite-like metal-organic

framework), ZIF (zeolitic imidazolate framework), MPF (metal peptide framework),

MAF (metal azolate frameworks), meso-MOF (mesoporous metal-organic

framework), and bio-MOF or MBioF (metal-biomolecule framework). Moreover,

following the tradition of zeolite science, some researchers have also used an

acronym of the laboratory, in which the material was developed, to name their

Chapter 2

50

materials. For example, in the series of MILs (materiauxs de l’Institut Lavoisier),

HKUST (Hong-Kong University of Science and Technology), SNU (Seoul

National University), JUC (Jilin University China), CUK (Cambridge University-

KRICT), POST (Pohang University of Science and Technology) and so on. Using

the empirical formula of the material expressing metal, ligands, and their

stoichiometry is also popular and used in many publications.

Despite the varying opinions, it is generally accepted that the work of

Hoskins and Robson reported in 1990, where they introduced the construction of

3D MOFs using organic molecular building blocks (ligands) and metal ions,

symbolizes a new chapter in the studying of MOFs. After about 10 years, two

milestone MOFs, MOF-5 (Zn4O(bdc)3, bdc = 1,4-benzenedicarboxylate) and

HKUST-1 (Cu3(btc)2, btc = 1,3,5-benzenetricarboxylate) further promoted the

development of this field, mainly due to their robust porosity (Furukawa et al.,

2013). Shortly thereafter, another representative MOF, MIL-101 (Cr3OF(bdc)3),

with high stability emerged (Ferey et al., 2005). It is clear that the rapid

development of this field was mainly promoted by the observation of various

exciting properties and the promise of potential applications for this type of porous

solid materials. As a nascent field, the complexity in composition and structures of

MOFs is continually increasing, and novel applications are continuously being

explored.

The formed porous structures of MOFs with pores of molecular dimensions

are associated with a series of desirable properties such as low density, high surface

area and high porosity (Furukawa et al., 2013). For instance, its highest Brunauer-

Emmett-Teller (BET) surface area to date can reach up to more than 10000 m2/g,

Chapter 2

51

which is much larger than conventional porous materials and even zeolites.

Furthermore, scientists believe that MOFs are preferred over the conventional

porous materials such as zeolites and carbon-based materials in certain areas, owing

to their customizable chemical functionalities, versatile architectures and milder

synthesis conditions (Cohen, 2012; Deria et al., 2014; Evans et al., 2014; Li et al.,

2014; Zhang et al., 2015). This is because, in essence, MOFs can be assembled from

the varieties of building blocks, which accommodates an infinite number of special

structures and potential applications. To date, tens of thousands of different MOFs

structures have been developed and identified, according to the Cambridge

Structural Database (CSD). Moreover, the mild synthesis conditions of MOFs allow

for the introduction of a variety of delicate functionalities into the framework. By

taking advantage of their crystallinity, rigidity/flexibility, variety, and designability

in both structure and properties, MOFs are being regarded as advanced porous

materials capable of reaching or surpassing a number of traditional porous materials.

However, due to the lability of ligand-metal bonds, most of the earlier

reported MOFs are sensitive to water content (Huang et al., 2003; Schoenecker et

al., 2012). For instance, one of the milestone MOFs, MOF-5 (Li et al., 1999),

decomposes gradually when the environment contains moisture (Kaye et al., 2007).

The instability in water has considerably limited these MOFs’ further application

and commercialization, since water or moisture is usually present in most industrial

processes as mentioned. Hence, water stable MOFs have been on great demand in

the scientific community.

Chapter 2

52

2.3.2 Water stable metal-organic materials

Water stability is a crucial property for any materials to be industrially applicable

since water is abundant in the preparation, storage, transportation and application

processes. Without sufficient hydro-stability, MOF materials would be limited for

further applications and industrializations. Therefore, water stable MOFs have ever

since been on great demand in the scientific community.

Water stable MOFs by definition are classified as those that do not exhibit

structural breakdown under exposure to water content (Burtch et al., 2014; J.

Canivet et al., 2014b). In principle, the key criterion to determine if a MOF structure

stays stable in the water stability test is through the comparison of the typical

chemical characteristics between post-exposure samples and pristine samples. The

chemical characteristics can be the powder X-ray diffraction (PXRD) pattern and

BET surface area on the basis of gas adsorption capacity, which could well suggest

whether the MOF loses its crystallinity or structural porosity after the exposure to

water content. Generally, MOF structures are susceptible to the attack by water

molecules, which would lead to ligands displacement, phase changes, and structural

decomposition. A water stable MOF structure must be strong enough to prevent the

intrusion of water molecules into the framework, and the consequent losses in

crystallinity and overall porosity. Thus, MOF structures with a great stability

normally possess strong coordination bonds (thermodynamic stability) or

significant steric hindrance (kinetic stability), to prevent the detrimental hydrolysis

reaction which breaks the metal-ligand bonds. With the improved understanding

towards MOF structural stability in water system and constant efforts, a number of

research publications on water stable MOFs are now experiencing a surge, and

Chapter 2

53

plenty more water stable MOFs are reported every year. Thus far, a consolidated

database of water stable MOFs has been established, which is summarized in Table

2-2. Basically, water stable MOFs could be categorized into three major types: (1)

metal carboxylate frameworks consisting of high-valence metal ions; (2) metal

azolate frameworks containing nitrogen-donor ligands; (3) MOFs functionalized by

hydrophobic pore surfaces or with blocked metal ions (Bosch et al., 2014).

When all the coordination environments remain the same, high-valence

metal ions with high charge density could form a stronger coordination bond

towards the ligands. This trend has been widely observed by MOF material

researchers, and rationalized by the hard/soft acid-base principle (Bosch et al.,

2014). On the other hand, high-valence metal units with higher coordination number

normally result in a greatly rigid structure, making the metal sites less susceptible

to water molecules (Qadir et al., 2015). Thus, with the most commonly used

carboxylate-type ligands, high-valence metal ions, such as Fe3+, Cr3+, and Zr4+, have

been exploited to synthesize water stable MOFs. For instance, Ferey and his co-

workers developed the famous Fe-based MIL-100 and Cr-based MIL-101, which

could provide decent chemical stability, staying robust for months in ambient

environment and various solvents (Ferey et al., 2005). In addition, MOFs

containing high-valence Zr4+ cations, like the well-known UiO-66 and PCN family,

demonstrate remarkable hydro-stability even at acidic and some basic conditions

(Bai et al., 2016; Cavka et al., 2008).

Besides the utilization of high-valence metals as hard acids for constructing

water stable MOFs, exploiting the azolate ligands (such as imidazolates, pyrazolate,

triazolates, tetrazolates, etc.) is another strategy in water stable MOF synthesis (J.

Chapter 2

54

P. Zhang et al., 2012). As these nitrogen-containing ligands are generally softer

ligands, when they interact with the softer divalent metal ions, stronger MOF

structures can be formed as a result. The most representative example of this

category is the zeolitic imidazolate frameworks (ZIFs), using Zn2+/Co2+ together

with imidizolate linkers to construct a variety of stable crystals analogous to zeolite

topology (Banerjee et al., 2008; Huang et al., 2006; Park et al., 2006a). Also,

Colombo et al. developed the microporous pyrazolate-based MOFs, M3(BTP)2 (M

= Ni, Cu, Zn, Co), which exhibited a great hydrothermal stability compared to most

carboxylate-based MOFs (Colombo et al., 2011b).

In addition to increasing metal-ligand bond strength, MOFs could be

specifically functionalized for steric hindrance to sustain robustness in an aqueous

medium. Through introducing hydrophobic pore surfaces or blocked metal ions,

water molecules can be excluded from approaching the lattice and attacking the

framework structure. Plenty of case studies have been reported for the enhanced

hydrothermal stability of MOFs: (1) Taylor et al. showed that nonpolar alkyl

functional groups in CALF-25 allow the structure to adsorb appreciable amounts of

water but remain structurally stable due to functional group shielding around the

metal center (Taylor et al., 2012). (2) Omary and his co-workers developed a series

of fluorinated MOFs (FMOFs), which are super-hydrophobic and exhibit

remarkable water stability (Nijem et al., 2013; Yang et al., 2011). (3) Post synthetic

approaches (e.g. ligand modification (Nguyen and Cohen, 2010), metal (Zhu et al.,

2016) and ligand exchange reactions (Liu et al., 2013)) were developed to

considerably enhance the hydrophobicity and hydrothermal stability of the MOF

structures that were already available.

Chapter 2

55

On top of these three main types of water stable MOFs, the unceasing efforts

to develop more and more water stable MOFs expand the applications of this unique

class of porous material. With the advantage of being stable in water-involved

environment, water stable MOFs can be effectively applied in a wide range of areas.

Classical examples include applying the water stable MOFs for adsorption in both

gaseous and liquid phases (He et al., 2015; Khan et al., 2013; Lin et al., 2006) for

proton conduction with the aid of water (Canivet et al., 2014b; Horike et al., 2013;

Sun et al., 2016; Tominaka et al., 2015; Yoon et al., 2013), as well as for sensing

and catalysis when water content is present (Alaerts et al., 2006; Cirujano et al.,

2012; Hwang et al., 2008; Kreno et al., 2012; Yoon et al., 2012); besides,

assembling the water stable MOF materials to thin films or membranes has a

promising potential to further improve the effectiveness and efficiency of many

industrial processes like water involved separation and waste water

decontamination (Qiu et al., 2014). Promising performance has been observed

owing to the undeniable advantages of MOF-type materials, such as huge porosity,

easy tunability of their pore size, and multiple shapes from micro- to meso-porous

scale through modifying the connectivity of inorganic moieties and the nature of

organic linkers.

Table 2-2. List of water stable MOFs under aqueous solution conditions

MOFs Metal Ligands Stability

test

duration^

Type of

water

solutions

Test

temp.

Ref.

ZIF-8 Zn

(II)

Methylimidizolate 24 h 0.1 and 8 M

aqueous

100 °C (Park et al.,

2006b)

Chapter 2

56

sodium

hydroxide

H3 [(Cu4Cl)3

(BTTri)8]

Cu

(II)

Triazolate-bridged

(BTTri)

24 h HCl solution

(0.001 M pH

= 3)

Up to

270 °C

(Demessence

et al., 2009)

PCN-222

(Fe)

Zr

(IV)

Porphyrin (TCPP) 24 h Concentrated

HCl (8M)

Room

temp

(Feng et al.,

2012)

PCN-224

(no metal,

Ni, Co, Fe)

Zr

(IV)

Metalloporphyrins

(MTCPP)

24 h pH = 0 to pH

= 11

aqueous

solutions

Room

temp

(Feng et al.,

2013)

PCN-59 Zr

(IV)

TPDC-

4CH2N3

24 h pH=11

aqueous

solution

(with NaOH)

Room

temp.

(Jiang et al.,

2012)

PCN-225 Zr

(IV)

Porphyrin

(H2TCPP)

24 h Aqueous

solutions

with pH

from 1 to 11

Room

temp

(Jiang et al.,

2013)

MIL-100

(Fe)

Fe

(III)

Benzene-

tricarboxylate

24 h Phosphate

buffer

aqueous

solution (pH

= 7.4)

37 °C (Cunha et

al., 2013)

MIL-127 Fe

(III)

BTC 24 h Phosphate

buffer

aqueous

solution (pH

= 7.4)

37 °C (Cunha et

al., 2013)

MIL-53 (Fe) Fe

(III)

BDC 24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

MIL-53 (Fe) Fe

(III)

BDC 24 h Phosphate

buffer

aqueous

solution (pH

= 7.4)

37 °C (Cunha et

al., 2013)

MIL-53-Br Fe

(III)

BDC 24 h Phosphate

buffer

aqueous

solution (pH

= 7.4)

37 °C (Cunha et

al., 2013)

Chapter 2

57

MIL-53 (Cr) Cr

(III)

BDC 24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

MIL-96 (Al) Al

(III)

BTC 24 h Extremely

acidic

solution (pH

= 1) and up

to pH = 8

Room

temp.

(Sindoro et

al., 2013)

CAU-6 Al

(III)

2-amino-

terephthalate

24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

UiO-66 (Hf) Hf

(IV)

Terephthalate

(BDC)

24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

UiO-66 (Zr) Zr

(IV)

Terephthalate

(BDC)

24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

UiO-66-NH2 Zr

(IV)

NH2-BDC 24 h Phosphate

buffer

aqueous

solution (pH

= 7.4)

37 °C (Cunha et

al., 2013)

ZIF-7 Zn

(II)

PhIM 24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

ZIF-8 Zn

(II)

Methylimidizolate 24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

ZIF-8 Zn

(II)

Methylimidizolate 24 h 0.1 and 8 M

aqueous

sodium

hydroxide

100 °C (Park et al.,

2006b)

ZIF-9 Zn

(II)

PhIM 24 h 100 mg/L

fluoride

solution

303 K (Zhao et al.,

2014)

Cu2L (L=

3,3’,5,5’-

tetraethyl-

4,4’-

bipyrazolate)

Cu

(II)

Pyrazolate 24 h 0.001m HCl

or 0.001m

NaOH

aqueous

solutions

Room

temp.

(Wang et al.,

2014)

PCN-56 Zr

(IV)

TPDC-2CH3 24 h

pH=11

aqueous

Room

temp.

(Jiang et al.,

2012)

Chapter 2

58

solution

(with NaOH)

PCN-58 Zr

(IV)

TPDC-

2CH2N3

24 h pH=2

aqueous

solution

(with HCl)

Room

temp.

(Jiang et al.,

2012)

ZrMOF–

BDC

Zr

(IV)

Terephthalate

24 h 0.1 M HCl Room

temp.

(DeCoste et

al., 2013)

ZrMOF–

NH2

Zr

(IV)

2-amino-

terephthalate

24 h 0.1 M HCl Room

temp.

(DeCoste et

al., 2013)

Pb2 (ptptp)2

(H2O)2

Pb

(II)

H2ptptp 36 h 3.0 M HCl

solution and

0.2 M NaOH

solution

Room

temp.

(Jia et al.,

2013)

PCN-56 Zr

(IV)

TPDC-2CH3 48 h pH=2

aqueous

solution

(with HCl)

Room

temp.

(Jiang et al.,

2012)

PCN-57 Zr

(IV)

TPDC-4CH3 48 h

pH=11

aqueous

solution

(with NaOH)

Room

temp.

(Jiang et al.,

2012)

La (BTB)

H2O

La

(III)

BTB 3 days Hot (60 °C

and 100 °C),

aqueous HCl

(pH = 2),

aqueous

NaOH (pH =

14)

60 °C-

100 °C

(Duan et al.,

2013)

PCN-57 Zr

(IV)

TPDC-4CH3 7 days pH=2

aqueous

solution

(with HCl)

Room

temp.

(Jiang et al.,

2012)

Ni3(BTP)2 Ni

(II)

Pyrazolate 2 weeks Boiling

aqueous

solutions of

pH 2 (HCl /

HNO3) to 14

(NaOH) for

two weeks

100 °C (Colombo et

al., 2011a)

Fe2(BDP)3 Fe

(III)

1,4-

benzenedipyrazolate

2 weeks Aqueous

solutions at

pH = 2 to 10

100 °C (Herm et al.,

2013)

Chapter 2

59

UMCM-150 Cu

(II)

Tricarboxylate 21

Months

Aqueous

solvent

(water :

DMF = 3 :

40, up to 9 :

2)

Room

temp.

(Cychosz

and Matzger,

2010b)

MOF-505 Cu

(II)

Biphenyl-

tetracarboxylate

21

Months

Aqueous

solvent

(water :

DMF = 7 :

1)

Room

temp.

(Cychosz

and Matzger,

2010b)

HKUST-1 Cu

(II)

Benzene-

tricarboxylate

21

Months

Aqueous

solvent

(water :

DMF = 7 :

1)

Room

temp.

(Cychosz

and Matzger,

2010b)

^ Stability test duration: the durations here do not signify the longest duration that the MOF

could withhold its robustness before structural damage. It is the time frame that was used

in the stability test as reported. After this test duration, the crystalline structure of MOF is

well retained.

2.3.3 Metal-organic materials in adsorption

As a class of recently developed porous materials, MOFs have shown huge potential

in adsorption-related applications. The unique structural characteristics, facile

functionalization and tunable porosities render MOFs to be superior over other

conventional porous materials like conventional activated carbon, metal oxides and

aluminosilicate zeolites. Besides, as a hybrid of inorganic and organic materials,

MOFs are associated with a milder synthesis condition. With a great availability of

various configuration and structures, as well as higher porosity and surface area,

MOF are expected to be a high-capacity adsorbent. Surveying the current literature,

some researchers have managed to employ water stable MOFs in both water

adsorption/dehumidification and adsorptive removal of various harmful pollutants

in the presence of water. Although this research using MOFs in wastewater

Chapter 2

60

remediation is still in its infancy, but with the recent advent of MOFs that are highly

stable in water (listed in Table 2-2) under varying pH conditions, such as Zr- and

Hf-based MOFs as well as MILs and azolate-based frameworks, this area of

research is quickly expanding. Generally, they provided a better performance in

comparison with the conventional porous materials. On the basis of these studies, it

was suggested that water stable MOFs could work as promising adsorbents in the

field of gas or liquid phase adsorptions, which allows for a widespread applicability

of MOF materials.

Adsorption of harmful gases

MOF-based adsorbents have shown promising results in capturing specific

compounds from water environments. Water stable MOF materials could be applied

to effectively uptake unfavorable gases in humid conditions for reducing the

harmful effects. Harmful gases including sulphur-containing compounds (SCCs),

nitrogen-containing compounds (NCCs), greenhouse gases, volatile organic

compounds (VOCs) are normally released as waste by-products from various

industries into the environment. It is critical to capture these harmful gases using

appropriate water stable sorbents, meaning that they must be able to withhold their

structure robustness during the adsorption process when residual moisture is present.

Thus, it is necessary to consider the effect of the trace amounts of water on the

capacity and selectivity of the sorbent material. For instance, Glover et al. (2011)

studied the adsorptive removal of several harmful gases including NH3, SO2, and

octane vapor using M-MOF-74 (M: Zn, Co, Ni, or Mg) in both dry and humid

conditions. The experimental breakthrough results revealed that all the prepared

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MOFs, with open metal sites, were capable of adsorbing the toxic gases in dry

conditions, while in humid conditions the adsorption capability was reduced due to

the competitive adsorption of water. The exception was in the case of NH3 gas,

where the decrease in adsorption capacity was negligible, suggesting that ammonia

could be removed by the MOF in both dry and humid conditions.

In particular, intensive studies have been carried out regarding carbon

dioxide due to the strong interest in utilizing MOFs as adsorbents for reducing

greenhouse gas emissions. Although water content is often detrimental for CO2

capture if using MOF materials, there are cases where water has minimal impact.

Zhang et al. (2015) highlighted that their developed Zn-pbdc-12a(bpe) and Zn-

pbdc-12a(bpy) exhibit CO2 uptakes of 98 and 78 cm3/g, respectively, very close to

the uptake values prior to water vapor treatment. Furthermore, Stavitski et al. (2011)

reported that amino-functionalized MIL-53(Al) exhibited little change in its

breakthrough profiles in a CO2/CH4 mixture in the presence of 0.042 bar water

vapor. Pirngruber et al. (2012) reported a minor impact on the dynamic CO2

capacity using UiO-66 across 3-40% RH conditions in CO2/N2 mixtures. Zhang et

al. (2013) reported that the post-synthetic modification of ZIF-8 using

ethylenediamine not only greatly improves its adsorption capacity of CO2, but also

significantly enhances its adsorption selectivity for CO2/N2 when water is present.

Li et al. (2013) reported a core-shell MOF comprising a porous bio-MOF-11/14

mixed core and a less porous bio-MOF-14 shell. The resultant core–shell material

exhibited 30% higher CO2 uptake than pure bio-MOF-14 as well as a more water

stable structure to prevent core degradation in aqueous environments. Moreover,

the breakthrough performance of SIFSIX-2-Cu-i and SIFSIX-3-Zn materials were

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62

tested by Nugent et al. (2013) in various CO2/N2 and CO2/H2 binary mixtures and

exhibited only a slight decrease in performance in the presence of 74% RH. Also,

McDonald and co-workers (2015) highlighted that the mmen-M2(dobpdc) (M = Mg,

Mn, Fe, Co, Zn) compounds, designated as ‘phase-change’ adsorbents, possess

highly desirable characteristics for the efficient capture of CO2. The Langmuir-type

CO2 adsorption behavior can be very well maintained after exposure to water at

different temperatures.

In addition to CO2 studies, Ebrahim et al. (2013) used two zirconium-based

MOFs, UiO-66 and UiO-67, as adsorbents for NO2 at ambient temperatures in either

dry or moist conditions (71% RH). It was found that UiO-67 had a better NO2

breakthrough performance than that of UiO-66 under humid conditions and this was

attributed to the greater ability of NO2 to dissolve and form acidic species in the

larger pore space of UiO-67.

Sava et al. (2013) reported that HKUST-1 could perform the competitive

sorption of molecular iodine gas from a mixed stream containing iodine and water

vapor. Molecular iodine, a long-lifetime product that is released during the

processing of spent nuclear fuel, was found to be preferentially adsorbed over water

under the 1:1 I2:H2O conditions, despite the hydrophilic nature of HKUST-1.

Moreover, both vapor phase and liquid phase adsorption of benzene over MIL-

101(Cr) was studied by Jhung et al. (2007). The adsorption performance of benzene

using MIL-101(Cr) in vapor phase was outstanding and much larger than that of

commercial sorbents like SBA-15, H-ZSM-5 and activated carbon.

Besides, the capture of the volatile organic compound (VOC), diethylsulfide

– a surrogate for the mustard gas chemical warfare agent bis(2-chloroethyl)sulfide,

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was explored by Padial et al. (2013) in a series of seven MOFs based on Ni2+

hydroxo-clusters bridged by different pyrazolateand carboxylate-based ligands.

These MOFs could capture harmful VOCs even under extremely moist conditions

(80% RH). Mito-oka et al. (2013) investigated the breakthrough performance of the

Zn4O(BDC)(BPZ)2 and DUT-4 structures in 50% RH air streams containing the

biogas impurity octamethylcyclotetrasiloxane. It was identified that these two

MOFs significantly outperformed the commercial activated carbon in removing the

biogas impurity from the mixture.

Adsorption of dyes

The contamination of dyes in water has been considered as a great issue of concern

in recent decades since dyes are stable, toxic and even potentially carcinogenic, and

their release into the environment causes serious environmental, aesthetical, and

health problems. A range of water stable MOFs have been studied and identified as

promising adsorbents to effectively capture common dye pollutants.

First of all, owing to the giant cell volume, extra-large pore size, and unique

structure characteristics, the water stable MIL-101 has been extensively studied for

dye removal. In 2010, Haque et al. (2010) applied MIL-101 for the adsorption

removal of methyl orange (MO) and xylenol orange (XO) from aqueous solution.

This is the first work regarding the adsorption of dye material by MOFs. The

adsorption mechanisms for MO and XO on MIL-101 were found to be related to

the electrostatic interactions and -SO3- group of dye, respectively. Comparative

study was conducted using another Cr-BDC MOF (MIL-53) for the adsorptive

removal of MO. Both the adsorption capacity and adsorption kinetic constant of

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MIL-101 were found to be greater than those of MIL-53, showing the importance

of porosity and pore size for the adsorption. Further to that, the authors modified

MIL-101 for more efficient adsorption of MO through charge interaction. The

adsorption capacity and kinetic constant are in the order of MIL-101(Cr) <

ethylenediaminegrafted MIL-101(Cr) (ED-MIL-101(Cr)) < protonated

ethylenediamine-grafted MIL-101(Cr) (PED-MIL-101(Cr)). The performance of

MIL-101 improves with modification even though the porosity and pore size are

slightly decreased with grafting and further protonation. In addition, Leng et al.

(2014) studied the adsorption interaction between MIL-101 and uranine dye in

aqueous solution. It was found that electrostatic interactions as well as the large

pore aperture of MIL-101 contributed to the uranine removal process. Based on

these studies, MIL-101 was suggested to be potential re-usable adsorbents to

remove dyes because of their high porosity, facile modification and ready re-

activation.

Next, Huo et al. (2012) applied MIL-100(Fe) to uptake malachite green

(MG). Evidence from zeta potential and X-ray photoelectron spectroscopic data

suggested that electrostatic attraction was the driven force and interaction between

the Lewis base –N(CH3)2 in MG and the water molecule coordinated metal sites of

MIL-100(Fe). The adsorption isotherms followed the Freundlich model, implying

that MIL-100(Fe) possessed heterogeneous surface caused by the presence of

different functional groups on the surface. The adsorption capacity of MIL-100(Fe)

for MG is comparatively higher than other conventional adsorbents such as

activated carbon and natural zeolite. Alongside good solvent stability and excellent

reusability, MIL-100(Fe) can be considered favorable for dye capture in aqueous

Chapter 2

65

solutions. In addition, Tong et al. (2013) reported that MIL-100(Fe) demonstrated

large adsorption uptakes for both MO and methylene blue (MB), while MIL-100(Cr)

can selectively adsorb MB from a MO-MB mixture. The study highlights that

framework metal ion replacement could be an efficient way to tailor MOFs for

specific applications in liquid.

More studies were carried out with respect to MO and MB as the typical

anionic and cationic dyes. Haque et al. (2010) reported that MOF-235 (an iron

terephthalate MOF) could be used for the removal of both MO and MB from

contaminated water. The adsorption capacities of MOF-235 were found to be much

higher than those of activated carbon; and the adsorption rates were also much faster.

This study is insightful as both dye pollutants are adsorbed in liquid phase even

though MOF-235 is regarded as nonporous as nitrogen can hardly be adsorbed at

low temperatures. Moreover, Tan et al. (2014) presented water-stable zeolite-like

MOF, AgIn(ina)4, to rapidly adsorb MO over methylene blue MB from water within

6 minutes; meanwhile the desorption of MO could easily be accomplished. In

addition, Lin et al. (2014) applied HKUST-1 to adsorb MB from aqueous solution.

The MOF mainly possessed mesopores, high surface area and big pore volume

which is beneficial for the adsorption capacity. It was found that the maximum

removal has been achieved at neutral pH 7.0, and the adsorbent could be easily

regenerated after washing with ethanol. These experimental results suggested that

some MOFs like HKUST-1 are kinetically but not thermodynamically water stable,

but still have the potential for wastewater treatment application.

Regarding other typical dye materials, Li et al. (2013) studied the potential

application of a copper coordination polymer with dithiooxamide (H2dtoaCu) in the

Chapter 2

66

adsorption removal of crystal violet (CV) from aqueous solution. The adsorption of

CV on H2dtoaCu can be best described by the Langmuir isotherm model with

outstanding monolayer adsorption capacity at various temperatures. The kinetics of

CV adsorption followed pseudo-second-order model and the chemisorption was

proved to be the rate-limiting step. Also, Jin et al. (2014) developed an indium-

based coordination polymer (In-CPPs) particles via a facile solvothermal synthesis

without any template or surfactant. Owing to their high BET surface area and pore

volume, In-CPPs exhibited excellent adsorption capability for Congo red, which

was higher than that of most adsorbents previously reported. It was proposed that

the driving force of Congo red adsorption over In-CPPs was mainly through

electrostatic interaction.

Adsorption of harmful organics

Nowadays, pharmaceuticals and personal care products (PPCPs) have become an

essential and indispensable element of life. The demand of PPCPs is constantly

increasing, and PPCPs are produced with long shelf-life to meet the customers’

demand making them highly persistent in the environment even after these products

have been spent. It was reported that the accumulation of these contaminants could

lead to serious environmental pollutions and safety concerns. Without active

regulations, they can cause endocrine disruptions and consequently endanger

human lives. Hence, the removal of these emerging contaminants from potable

water and aquatic systems remains a critical issue. This was noted by Cychosz et al.

(2010) along with a water stability study of various MOF structures. They identified

that MIL-100 was able to adsorb the pharmaceuticals furosemide and sulfasalazine

Chapter 2

67

from water with large uptakes achievable at low concentrations, indicating that the

adsorption of wastewater contaminants may be a feasible application of water stable

MOFs.

Further to that, Hasan et al. (2012) applied both MIL-100(Fe) and MIL-

101(Cr) for the liquid phase adsorption of naproxen and clofibric acid which are

two typical PPCPs. The experiment suggested a removal efficiency order that MIL-

101(Cr) > MIL-100(Fe) > activated carbon in terms of the adsorption rate and

adsorption capacity. Large surface area or pore volume was found to be beneficial

for the adsorption process. It was proposed that the adsorption mechanism was

mainly due to a simple electrostatic interaction between PPCPs and the MOF

adsorbents. The removal efficiency can be further improved by introducing the

ethylenediamine (ED) to the framework, within which the basic (-NH2) groups were

generated. Regeneration was feasible by washing the functionalized basic ED-MIL-

101 (-NH2) with ethanol, and at least three cycles with little change in the

adsorption performance can be accomplished.

Other MIL-family MOFs were also applied for organic pollutants removal

from water. Jung et al. (2013) studied the applicability of water stable MIL-53 in

adsorptive removal of 2,4-dichlorophenoxyacetic acid (2,4-D), a hazardous

herbicide, from contaminated water. It was found that MIL-53 had a very fast

adsorption within one hour and the adsorption capacity of MIL-53 was much higher

than that of activated carbon or zeolite. Han et al. (2015) introduced carbon

nanotubes to composite with MIL-68(Al) for enhanced adsorption of phenol from

aqueous solutions. Moreover, Maes et al. (2011) reported the MIL-53 was also able

to adsorb phenol and p-cresol from contaminated water as well as the monomeric

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sugar fructose. They also reported that in contrast to the aluminum or chromium

analogues previously reported, the iron MIL-53(Fe) solid having a characteristic

breathing property showed a noticeable effect in the vapor phase adsorption of

alkanes.

Next, with regard to ZIF materials, Khan et al. (2015) has applied ZIF-8 for

the removal of phthalic acid (H2-PA) from aqueous solutions via adsorption. It was

found that the adsorption capacity of ZIF-8 framework was much higher than that

of a commercial activated carbon and most reported adsorbents. The adsorption was

due to an electrostatic interaction between the positively charged surface of ZIF-8

and the negatively charged PA anions; also, acid-base interactions had a favorable

effect on the adsorption of H2-PA especially at low pH conditions. Moreover, Jiang

et al. (2013) applied ZIF-8 for fast removal of 1H-benzotriazole (BTri) and 5-

tolyltriazole (5-TTri) in aqueous solution. Again, ZIF-8 provided much larger

adsorption capacity and faster adsorption kinetics in comparison to activated carbon

and ZIF-7. The hydrophobic and π–π interaction between the aromatic rings of the

BTri and the aromatic imizole rings of the ZIF-8, as well as the coordination of the

nitrogen atoms in BTri to the Zn2+ ions in ZIF-8 was responsible for the efficient

adsorption.

Moving forward, for UiO-family materials, Seo et al. (2015) applied UiO-

66 to investigate the adsorptive removal of methylchlorophenoxypropionic acid

(MCPP) from water. Compared with activated carbon, UiO-66 had a very high

adsorption rate. Besides, the adsorption capacity of UiO-66 was higher than that of

activated carbon especially at low MCPP concentrations. It was proposed that

electrostatic and π-π interactions were essential in the adsorption process.

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69

Furthermore, Zhu et al. (2015) investigated the removal of two representative

organophosphorus pesticides (OPs), glyphosate (GP) and glufosinate (GF), by

another exceptionally stable Zr-based MOFs of UiO-67. The abundant Zr−OH

groups, resulting from the missing-linker induced terminal hydroxyl groups and the

inherent bridging ones in Zr−O clusters of UiO-67 particles, served as natural

anchorages for efficient GP and GF capture. Owing to the strong affinity towards

phosphoric groups and adequate pore size, the adsorption capacities in UiO-67 were

much higher than those of many other reported adsorbents.

In addition, several comparison studies on adsorptive removal of common

organic compounds from water were conducted. Kim et al. (2013) investigated the

adsorption behavior of typical chloroaromatic compounds (chlorobenzene, 2-

chlorotoluene, 1,3-dichlorobenzene, and 2-chloroanisole) over a series of MOFs

(MIL-125, NH2-MIL-125, UiO-66, MIL-101, and HKUST-1). NH2-MIL-125

showed the highest adsorption capacity at compound concentration of 0.1 M,

whereas MIL-101 showed the highest adsorption at 1.0 M, which was significantly

higher than that of activated carbon under the given conditions. Moreover, Xie et

al. (2014) conducted a comprehensive study to screen a series of MOFs for

nitrobenzene capture from water. The results suggested that the adsorption

capacities of two aluminum-based MOFs, CAU-1 and MIL-68(Al), greatly

outperform most of the previously reported porous materials. In addition, the

regeneration of CAU-1 and MIL-68(Al) could be fully achieved using methanol

without secondary pollution. The great stability and reusability of these MOFs

indicate that they are promising adsorbents for efficient capture of organic

pollutants from wastewater. In addition, Jin et al. (2015) investigated three ZIFs

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70

(ZIF-8, ZIF-90 and ZIF-93) for adsorption of 5-hydroxymethylfurfural (HMF) from

aqueous solution. It was found that the equilibrium uptake of HMF decreased

following the order of ZIF-8 (465 mg/g) > ZIF-90 (307 mg/g) > ZIF-93 (279 mg/g),

in accordance with the hydrophobicity of the frameworks. The finding confirms that

ZIF-8 can be employed as an effective and reusable adsorbent for HMF recovery

from aqueous solution.

Adsorption of ionic pollutants

Ionic pollutants have been a major global threat to the environment. These

pollutants enter the water from various dyes. Removal of heavy metal ions from

aqueous solution is crucial as they are mostly toxic even at very low concentrations

and could lead to serious health effects on human beings. To achieve that,

appropriate materials are on demand. Compared with the conventional adsorbents,

MOFs are associated with higher accessible surface area and more active sites for

adsorption to take place. They lead to a new strategy that conquers the dilemma

between the excellent properties from nanoscale effect and the aggregation of small

size particles in the adsorption application of nanoparticle materials, as shown in

Figure 2-9. Nevertheless, to be suitable in such applications, MOFs as porous

coordination materials must possess great chemical stabilities under different ionic

conditions.

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71

Figure 2-9. Schematic illustration of the new strategy for efficient adsorbent (Zhu

et al., 2012).

A series of newly developed MOF structures were reported with expansive

water stability and heavy metal ion removal capabilities. Yee et al. (2013)

developed two typical frameworks Zr-DMBD and Al-DMBD analogous to the

UiO-66 and CAU-1 topologies, respectively. The MOF materials were

functionalized through installing the free-standing, accessible thiol (-SH) groups in

robust and porous coordination networks to provide wide-ranging reactivity and

properties in the solid state. The resultant frameworks provided the carboxyl bonded

to the hard Zr(IV) or Al(III) center and the thiol groups decorating the pores. The

thiol-laced Zr-DMBD crystals were able to lower the Hg(II) concentration in water

below 0.01 ppm and effectively take up Hg from the vapor phase. Furthermore,

Meng et al. (2014) developed a 3D pillar-layer framework, formulated as

[Zn(trz)(H2betc)0.5]∙DMF, with uncoordinated carboxyl groups exhibiting

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72

exceptional stability. It can effectively and selectively adsorb Cu2+ ions and has

been applied as a chromatographic column for separating Cu2+/Co2+ ions. Also,

Zhang et al. (2015) applied the water stable UiO-66(Zr)-2COOH for selective

removal of Cu2+ over Ni2+ from aqueous solution. According to them, the unique

chelation effect of two carboxyl groups on the adjacent organic ligand as well as

the Jahn-Teller effect significantly elevate the performance. Moreover, Fang et al.

(2010) synthesized two isostructural mesoporous MOFs designated as PCN-100

and PCN-101, using Zn4O(CO2)6 as secondary building units and two extended

ligands containing amino functional groups, TATAB and BTATB. The TATAB

ligand that comprises PCN-100 was employed to capture heavy metal ions (Cd2+

and Hg2+) by constructing complexes within the pores with a possible coordination

mode similar to that found in aminopyridinato complexes. In addition, Carboni et

al. (2013) prepared and functionalized stable and porous phosphorylurea-derived

MOFs with the UiO-68 network topology as novel sorbents to extract actinide

elements (uranium) from aqueous media. Promising performance was obtained with

saturation sorption capacities as high as 217 mg-U/g. Their results indicate that

porous MOF materials with phosphorylurea functional groups are good candidates

for uranium sorption from nuclear waste and acid mine drainage.

Further to cationic heavy metal ions, anionic contamination in water could

be effectively removed by MOFs as well. Howarth et al. (2015) applied NU-1000

to effectively adsorb and remove selenite and selenate from aqueous solutions. Fu

et al. (2015) synthesized two water stable MOFs, FIR-53 and FIR-54, to efficiently

trap chromate inorganic pollutant ions. Similarly, the capability of removing

aquatic arsenic species was realized by some other water stable MOFs, e.g., MIL-

Chapter 2

73

100(Fe) (Zhu et al., 2012). The mechanism study confirmed that the adsorption took

place via formation of Fe-O-As bonds and arsenate was preferentially adsorbed onto

the interior of the MIL-100(Fe) rather than the outer surface. As a result, porous

MIL-100(Fe) provided more interior spaces compared to Fe2O3 nanoparticles,

which resulted in a six-fold higher adsorption capacity.

Besides, another typical anionic pollutant – fluoride – was investigated

comprehensively. Zhao et al. (2014) conducted a study towards the stability of

MOFs in fluoride solutions based on 11 water-stable MOFs: MIL-53(Fe, Cr, Al),

MIL-68(Al), CAU-1, CAU-6, UiO-66(Zr, Hf) and ZIFs-7, -8, -9; factors including

central metal activity, pore topology and coordination number were found to have

noteworthy influence. In particular, the defluoridation performance of UiO-66 was

examined, which showed an adsorption capacity that is higher than most of the

conventional adsorbents. On the basis of the systemic study, it was suggested that

increasing the number of -OH groups is an efficient strategy to improve the

defluoridation performance of MOFs. Further to that, Zhang et al. (2014) applied a

typical aluminum-based MOF, MIL-96, for defluoridation of drinking water using

a batch experiment. The results indicated that the defluoridation efficiency and

aluminum residual of MIL-96 were far superior to that of activated alumina (AA)

or nano-alumina (NA). Moreover, there were no major influence on fluoride

removal by MIL-96 in the presence of chloride, nitrate, sulfate, bicarbonate and

phosphate. Results based on these studies demonstrated MOFs are promising

defluoridation materials for wastewater treatment.

Chapter 2

74

Summary and perspectives

Since the discovery of water stable MOFs and their favorable attributes for

adsorption, studies that explored the viability of applying this novel class of

materials in various water-related processes have been developed extensively.

Rooting from the rational design of crystal structures as well as proper

functionalization, MOFs as adsorbents have achieved a great level of both

thermodynamic and kinetic performances accompanying great stabilities in

applications such as: water retention, selective capture of CO2, separation of organic

components and removal of ionic species from water solutions. Moving forward, it

is worthy to study the capability of MOF materials in removing the particular group

of pollutants – the anionic contamination in wastewater. The significance is due to

the severe toxicity of these contaminants and they are the imminent threat to the

local communities. Understanding on the basis of current literature, it was

anticipated that water stable MOFs especially those contain active sites with strong

affinities to anionic pollutants would exhibit adequate removal efficiency. The

potential MOF materials can be considered include: UiO-66 family, any Zr-based

water stable MOFs, Fe/Al-based MIL-family, etc.

In order to further apply water stable MOFs as novel functional porous

solids for adsorptive applications, several questions must be answered before

embarking on the road to industrialization. The development of even more powerful

MOFs is needed with novel topologies incorporated to provide plenty of effective

adsorption sites in unit space. Moreover, whether the material could fully maintain

its functions and critical structure across multi-cycles applications remains a

questionable challenge. In the past, researchers have mainly focused on studying

Chapter 2

75

the hydrothermal stability of pristine MOFs; their stability after the MOFs were put

into applications and re-activation needs a more detailed assessment, although a few

pioneering studies have been working on this. In addition, prevailing application of

certain materials normally requires them to entail multifunctionality. To prepare

MOF materials with multifunctionality is not easy but definitely feasible due to the

customizable and versatile structure provided, which requires significant efforts to

take full advantage of the designability of MOFs.

Considered holistically, there is a promising future for MOF applications as

functional adsorbents. Continuing efforts in both academic and industrial sectors

are strongly required in order to achieve a scale-up and cost-effective synthesis and

operation process.

Chapter 3

76

CHAPTER 3 SUPERIOR REMOVAL OF ARSENIC

FROM WATER WITH ZIRCONIUM METAL-

ORGANIC FRAMEWORK UIO-66

Chapter 3 studies the capability of hydro-stable Zr-MOF as functional adsorbent

to remove aquatic arsenic species for water decontamination

ABSTRACT

In this chapter, a water stable zirconium metal-organic framework (UiO-66) has

been synthesized and for the first time applied as an adsorbent to remove aquatic

arsenic contamination. The as-synthesized UiO-66 adsorbent functions excellently

across a broad pH range of 1 to 10, and achieves a remarkable arsenate uptake

capacity of 303 mg/g at optimal pH, i.e., pH = 2. To the best of our knowledge, this

is the highest arsenate As(V) adsorption capacity ever reported to date, much higher

than that of currently available adsorbents (5-280 mg/g, generally less than 100

mg/g). The superior arsenic uptake performance of UiO-66 adsorbent could be

attributed to the highly porous crystalline structure containing zirconium oxide

clusters, which provides a large contact area and plenty of active sites in unit space.

Two binding sites within the adsorbent framework are proposed for arsenic species,

i.e., hydroxyl group and benzenedicarboxylate ligand. At equilibrium, seven

equivalent arsenic species can be captured by one Zr6 cluster through the formation

of Zr-O-As coordination bonds.

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3.1 Introduction

Arsenic contamination is a global threat due to its toxicity and carcinogenicity

(Jomova et al., 2011). Typical arsenic concentration in contaminated groundwater

ranges from 0.5 to 2.5 ppm, and is much higher (usually >100 ppm) in industrial

waste water. Exposure to arsenic-polluted water would result in such severe health

problems as liver, lung, kidney, and skin cancers. Hence, arsenic has been

categorized by WHO as the first priority issue among the toxic substances (WHO,

2011). Although aquatic arsenic possesses different oxidation states, the inorganic

arsenic is usually oxidized to arsenate As(V) in various water bodies. Due to the

high mobility of arsenate species in water streams as well as its ease in accumulation

in human body and food chain, effective removal of aquatic arsenate has been an

important topic in water treatment.

Adsorption is considered as one of the most promising techniques for

wastewater decontamination owing to the high efficiency, low cost and ease in

operation (Mohan and Pittman, 2007). Intensive studies have been carried out to

develop various adsorbents for arsenic removal and some commercial adsorbents

are available. Despite that, the arsenic adsorption capacity of conventional

adsorbents like activated carbons, activated alumina and powdered zeolite is

unsatisfactory (Mohan and Pittman, 2007). In order to further improve the

adsorption capacity, strategic methods including reducing the particle size of

adsorbents or preparing materials with hierarchically ordered structures were

employed. These approaches may increase the surface area of adsorbent for

efficient contact, however, they could complicate the synthesis process and

Chapter 3

78

consequently raise the production cost (Yang et al., 2014). Moreover, although a

few recently reported adsorbents exhibited enhanced adsorption capacity, such as

γ-Fe2O3 nanoparticles embedded silica and yttrium–manganese binary composite,

their applicable pH ranges are quite limited (Yu et al., 2015c). Hence, adsorbents

with better performance are on demand for arsenic decontamination from water.

Metal-organic framework (MOFs), a new class of hybrid porous materials

built from organic linkers and inorganic metal (or metal-containing cluster) nodes

through coordination bonds, have attracted tremendous attention in recent years

(Zhou et al., 2012). Benefitting from their versatile architectures and customizable

chemical functionalities, MOFs have been widely applied in gas storage, sensing,

catalysis, separation, etc. However, the hydrothermal stability of MOFs remains a

challenge as most MOFs are sensitive to water; very few of them stay chemically

stable in an acidic or basic aqueous solution (Cychosz and Matzger, 2010a). This

restricts the practical applications of MOFs in water treatment. Recently, some

water stable MOFs have been developed and applied for heavy metal ions

decontamination. In particular, ZIF-8, MIL-53 and Fe-BTC MOF materials were

put into aquatic arsenic removal tests, but no outstanding performance was observed

in comparison with other commercial and synthetic adsorbents (Vu et al., 2015; Yu

et al., 2015a; Zhu et al., 2012).

Since zirconium based adsorbents such as amorphous zirconium oxide

nanoparticles and zirconium immobilized nano-scale carbon demonstrated strong

affinity towards arsenic species, a porous crystalline material containing zirconium,

which provides larger contact area and more active adsorption site, may deliver a

better arsenic uptake performance (Mahanta and Chen, 2013). Recently, a series of

Chapter 3

79

zirconium MOFs (Zr-MOFs) with exceptional chemical and thermal stability has

emerged. UiO-66 framework (UiO stands for University of Oslo) is one

prototypical Zr-MOF, constructed with Zr6O4(OH)4 clusters and terephthalate (1,4-

benzenedicarboxylate, BDC) linkers (Cavka et al., 2008). As shown in Figure 3-

1(a), the octahedral cluster of UiO-66 contains six-centered Zr cations, as well as

eight μ3-O bridges, four of which are protonated. Moreover, each cluster unit is

connected to 12 neighboring clusters by BDC linkers to establish an expanded face-

centered-cubic (fcu) arrangement, as shown in Figure 3-1(b). The high degree of

topological connectivity together with the strong coordination bonds between

zirconium and oxygen renders UiO-66 to be greatly hydro-stable, even under acidic

or some alkaline conditions. This provides a theoretical basis of applying UiO-66

in water treatment. Thus far, a few researchers have employed UiO-66 framework

to capture contaminants in water solution, but no reports appeared in any journals

on arsenic removal.

Figure 3-1. (a) Six-center octahedral zirconium oxide cluster. (b) fcu unit cell of

UiO-66; blue atom – Zr, red atom – O, white atom – C, H atoms are omitted for

clarity.

Chapter 3

80

In this study, water stable Zr-MOF (UiO-66) with particle sizes in the

micrometer range was synthesized and applied as an adsorbent to uptake arsenic

species, specifically aquatic arsenate As(V). To the best of our knowledge, this is

the first work of applying Zr-MOF in arsenic pollutant removal from water. Proper

characterizations, adsorption studies and mechanism analyses were carried out to

examine the arsenic adsorption performance of UiO-66 adsorbents. pH applicable

range and adsorption capacity as two of the key operational parameters were

assessed in detail. The adsorbent structure as well as adsorption mechanisms were

studied by analyzing the scanning electron microscopy coupled with energy-

dispersive X-ray spectroscopy (SEM-EDX), powder X-ray diffraction (PXRD) and

Fourier transform infrared spectroscopy (FTIR). This study unveils the excellent

performance of UiO-66 adsorbent in arsenic removal from water, which would

provide significant new insights to the application of MOFs in water treatment and

lead to an advanced adsorbent material in arsenic decontamination industry.

3.2 Methods

Materials

Unless otherwise stated, all the chemicals in this study were used as received

without further purification. The reagents including zirconium(IV) chloride (ZrCl4,

99.5%), 1,4-benzenedicarboxylic acid (BDC, 98%), and sodium arsenate dibasic

heptahydrate (Na2HAsO4•7H2O, 98%) were purchased from Sigma-Aldrich.

Moreover, ethanol (99.9%), dimethylformamide (DMF, 99.9%), sodium nitrate

(99%), sodium chloride (99%), sodium sulfate, anhydrous (99%), sodium carbonate

Chapter 3

81

anhydrous (99.8%), nitric acid (68%), and sodium hydroxide (99%) were purchased

from VWR. The stock solution of 1000 mg/L arsenate was obtained by dissolving

Na2HAsO4•7H2O in 1 L deionized (DI) water (Analytic lab, ACEX, Imperial

College London). The solutions of required concentrations used in this study were

prepared by diluting the arsenate stock solution with DI water. pH adjustment was

conducted using nitric acid or sodium hydroxide.

Synthesis of UiO-66

The Zr-MOF material, UiO-66, was prepared by mixing the chemicals: DMF,

deionized water, BDC and ZrCl4 in a 500:1:1:1 molar ratio. This was followed by

ultrasonication for 15 min to ensure full dissolution of the solid particles. The

solution was then transferred to an autoclave that had been left in a 98% sulfuric

acid solution for 24 h to dissolve any residual impurities, washed with deionized

water and dried with compressed air. The autoclave was tightened with a spanner

and transferred to a convection oven (UF30, Memmert) where the temperature was

set to 120 oC and the fan to 100% open to ensure that the temperature inside the

oven was homogeneous. After 48 h, the autoclave was cooled down to room

temperature, then opened and agitated to disperse the solid particles (MOFs) that

had settled at the bottom. The solution was then transferred to a centrifuge tube and

placed in the centrifuge (Thermo Scientific Legend X1R), which was set to 15000

rpm, and centrifuged for 10 min. This resulted in the sedimentation of the solid to

form a layer at the bottom of the tube with a DMF solution containing unreacted

chemicals and residual impurities above it, which was disposed of and replaced with

ethanol. The centrifugation was repeated three to four times with ethanol washing,

Chapter 3

82

and in each cycle approximately 100 mL ethanol was used for the washing of a

yield of 0.2 g MOF particles. After that, to ensure the complete activation of MOF

particles, the collected MOFs were immersed in ethanol solutions for three to four

times, with each wash lasting three days, and finally dried in a vacuum oven

(Fistreem Vacuum Oven) at 120 oC for 24 h to obtain the as-synthesized UiO-66

materials for following studies.

Characterizations of UiO-66.

The surface morphology of the UiO-66 adsorbent was studied by using a scanning

electron microscope (SEM, LEO Gemini 1525) coupled with Energy-dispersive X-

ray (EDX). Moreover, the crystal structure of adsorbent was analyzed by a powder

X-ray diffractometer (PXRD, Panalytical Xpert). The X-Ray diffractometer is

operated with Ni-filtered Cu Kα radiation at a voltage of 40 kV and a current of 40

mA. The scanning range (2θ) is between 5o to 50o. To be ready for XRD study, the

samples were dried at 120 oC overnight under vacuum condition and positioned on

a silicon plate. Furthermore, the Fourier transform infrared (FTIR) spectrum was

employed to study the structure characteristics of samples and determine the

vibration frequency changes due to the adsorption process. The adsorbent materials

before and after adsorption were analyzed by a FTIR spectrometer (Spectrum 100,

PerkinElmer) equipped with diamond ATR (attenuated total reflection) crystal. The

FTIR spectra were recorded in a wavenumber range of 4000-500 cm-1 by

accumulating 8 scans at a resolution of 2 cm-1.

In addition, the surface charges of UiO-66 adsorbents at different pH were

measured by a zeta potential analyzer (ZetaPALS, Brookhaven Instruments), in

Chapter 3

83

order to identify the point of zero charge (PZC). The specific surface area as well

as the inner porous structure of adsorbent was determined by N2 adsorption–

desorption isotherms which was measured by a gas adsorption analyzer instrument

(3Flex, Micrometrics) at 77 K. The samples were dried under vacuum and purged

with nitrogen overnight before the tests. The specific surface areas as well as pore

size distributions were carried out using BET surface area analysis.

Lastly, the spent UiO-66 samples after arsenic adsorption were collected

using centrifuge and then washed thoroughly with DI water before drying in the

vacuum oven for proper characterization.

Arsenate adsorption experiments

The adsorption tests were investigated at room temperature (25 ± 1 oC). In the pH

effect experiment, a series of 50 mL arsenate solutions with initial concentration of

50 ppm was prepared using the stock solution. UiO-66 adsorbents with a dosage of

0.5 g/L were added into the solutions that were going to be constantly shaken with

the rate of 220 rpm. The solution pH ranging from 1 to 11 was respectively

controlled throughout the test. The pH of solutions was measured by an ORION

525A pH meter. According to the preliminary experiment, the adsorption reaches

equilibrium within 48 hours. Hence, after 48 hours of contact time, the solutions

were then filtered through a 0.45 µm filter and the residual arsenic concentration of

the filtrate was measured by an inductively coupled plasma emission spectrometer

(ICP-OES, Optima 2000 DV, PerkinElmer). Moreover, similar testing procedures

were employed in the test on coexisting ions effect. Using sodium salts such as

NaCl, NaNO3, Na2CO3, and Na2SO4, common anions (Cl-, NO3-, CO3

2-, and SO42-)

Chapter 3

84

with an exceptionally high concentration of 1 g/L were introduced into the 50 mL

solutions (50 ppm arsenate) with the adsorbent dosage of 0.5 g/L at pH 2, in order

to investigate the respective influence of these coexisting anions towards the arsenic

adsorption process. Furthermore, in the adsorption isotherm study, 0.025 g

adsorbent was added to a series of 50 mL arsenate solutions with different initial

concentrations from 10 to 200 ppm. Two sets of experiment at pH 2 and 7 were

conducted, and the solution pH was maintained throughout. Other procedures were

the same with those in the pH effect experiment.

The adsorption capacity was calculated in terms of the equation as below:

𝑄 = (𝐶0 − 𝐶𝑓)𝑉/𝑚 (3-1)

where Q is the adsorption capacity (mg/g); C0 and Cf are the initial and residual

concentrations (mg/L) of pollutant, respectively; V is the volume of solution (L);

and m is the mass of the original adsorbent (g).

3.3 Results and discussion

3.3.1 Characterization of adsorbent

The PXRD pattern as well as FTIR spectrum of as-synthesize UiO-66 materials is

shown in Figure 3-2(a). It can be observed that the main XRD peaks and the IR

bands matched well with those in literature (Cavka et al., 2008). Representative

vibrations like peaks at 1590 and 1390 cm-1 associated to the carboxylate groups

and peaks at 730 and 680 cm-1 corresponding to Zr-(μ3)O can all be observed in the

FTIR spectrum. The characterization data indicate that the UiO-66 framework has

been successfully prepared. The surface morphology of UiO-66 adsorbents is

Chapter 3

85

presented in Figure 3-2(b). The UiO-66 material’s particle size was in the

micrometer scale, and the crystals were well intergrown with sharp edges. Besides,

the porosity as well as the BET surface area of UiO-66 was measured to be 0.56

and 569.6 m2/g, respectively, based on the N2 adsorption–desorption isotherms at

77 K, as shown in Figure 3-2(b).

Figure 3-2. (a) PXRD pattern and FTIR spectrum of pristine UiO-66 adsorbent.

(b) Nitrogen adsorption (filled circles)-desorption (open circles) isotherms and

SEM image of pristine UiO-66 materials.

3.3.2 Arsenate adsorption

pH effect

pH value is one of the key operational parameters in practical water treatment, as it

may influence both the adsorbent structure and the distribution of pollutant species.

The pH effect on the arsenate removal process using UiO-66 adsorbents was

investigated and shown in Figure 3-3(a). The UiO-66 adsorbent demonstrated an

outstanding arsenate uptake efficiency across a very broad pH range of 1 to 10.

With the initial arsenate concentration of 50 ppm, the adsorbents can accomplish

generally more than 75 mg/g decontamination performance in this pH range.

Chapter 3

86

Moreover, at very acidic conditions of pH 1 to 3, more than 95 mg arsenate can be

removed by one gram of UiO-66 adsorbents; especially at pH 2, the best adsorption

performance of nearly 100 mg/g was achieved. Further increasing the water pH to

11, however, the adsorption performance decreases considerably to 52 mg/g. This

could be due to the onset of structural decomposition of UiO-66 under too basic

condition.

Figure 3-3. (a) pH effect on arsenate adsorption. (b) pH effect on As(V)

speciation, adsorbent surface charge and adsorption performance. (c) Coexisting

anion effects on arsenate adsorption at pH 2. [UiO-66] = 0.5 g/L, [As(V)]0 = 50

mg/L, [coexisting anions] = 1 g/L, T = 25±1 oC.

Chapter 3

87

To better understand the relationship between water pH and adsorbent

performance, zeta potential as well as arsenate speciation analyses were conducted

and illustrated in Figure 3-3(b). The point of zero charge was identified to be pH =

3.9, which indicates a positively charged outer surface of UiO-66 adsorbent when

pH is below 3.9 and a negatively charged outer surface when pH is above 3.9. In

addition, the predominant species of arsenate in water bodies exist as: H3AsO4 at

pH below 2.1, H2AsO4- at pH from 2.1 to 6.7, and HAsO4

2- at pH from 6.7 to 13.4,

respectively. It can be found that electrostatic interaction played a certain role in the

adsorption process, e.g., at pH 3 anionic arsenate species could be effectively

attracted to the proximity of positively charged adsorbents, which resulted in a

better adsorption performance compared to those when pH is higher than 3.9.

However, electrostatic interaction did not solely control the adsorption process,

since the best arsenate uptake performance appeared at pH 2 where the dominant

arsenate species (H3AsO4) present as zero valence and deliver no electrostatic

attraction. The proposed adsorption mechanism (as discussed in Section Adsorption

mechanism) suggests that arsenic species were bound to the UiO-66 adsorbents

through two coordination processes, which are similar to an acid-base interaction.

Thus, despite electrostatic force, the increasing abilities of arsenate species

(H3AsO4) to release H ions and bind to the hydroxyl sites in UiO-66 adsorbents at

very acidic conditions (pH 1-2) facilitate the arsenic uptake process, which resulted

in the best adsorption efficiency in this pH range.

In addition, it should be noticed that with initial arsenate concentration of

50 ppm the arsenate decontamination performance at pH 7 is more than 80 mg/g.

The decent arsenate uptake efficiency of UiO-66 adsorbent at neutral pH favors its

Chapter 3

88

application in the remediation of surface and ground contaminated water that are

normally associated with a neutral pH condition (pH = 7 ± 1). Furthermore, arsenic

contaminated industrial wastewater normally varies in pH and contains different

coexisting ions. As shown in Figure 3-3(a) and 3(c), the UiO-66 adsorbent could

effectively capture arsenic across a broad pH range (1-10), and its arsenic uptake

capability can hardly be inhibited by some commonly coexisting anions. Less

operational cost is required as any pre-treatment or additional pH adjustment steps

could be avoided. Therefore, UiO-66 is considered as a promising arsenic adsorbent

for industrial wastewater treatment.

Adsorption kinetics

The adsorption kinetics between UiO-66 and arsenate pollutants in water solution

are studied and summarized in Figure 3-4(a) and (b). Two typical pH conditions (2

and 7) were selected as the testing conditions. It is noted that adsorption proceeded

faster at pH 2 compared to pH 7. In the case of pH 2, more than 90% of equilibrium

adsorption capacity was achieved within the first 5 h and the equilibrium was

reached at 10 h; regarding the neutral pH condition, it required 10 h to complete 90%

of equilibrium adsorption capacity and the equilibrium was reached at 20 h. The

adsorption rate in both cases is fair since the UiO-66 samples used in the current

study are in the micrometer size range; if a faster adsorption process is required,

smaller size UiO-66 samples down to nanometer order could be prepared through

revising the synthesis conditions.

Chapter 3

89

Figure 3-4. Adsorption kinetics of arsenate adsorbed onto UiO-66 adsorbent: (a)

[UiO-66] = 0.3 g/L, [As(V)]0 = 60 mg/L, pH = 2.0, T = 25±1 oC; (b) [UiO-66] =

0.3 g/L, [As(V)]0 = 60 mg/L, pH = 7.0, T = 25±1 oC.

To better understand the adsorption kinetics, the experiment data were

further analyzed using the adsorption kinetics models – the pseudo-first and pseudo-

second order models. The mathematical equation of the pseudo-first-order model

and the pseudo-second-order model are expressed as Equation 3-2 and 3-3,

respectively. In particular, the pseudo-second-order model is based on the

assumption that the occupation rate of adsorption sites is proportional to the square

of the number of unoccupied sites.

ln(𝑞𝑒 − 𝑞𝑡) = ln𝑞𝑒 − 𝑘1𝑡 (3-2)

𝑡

𝑞𝑡=

1

𝑘2𝑞𝑒2 +

𝑡

𝑞𝑒 (3-3)

where qe (mg/g) and qt (mg/g) are the amount of arsenate adsorbed by adsorbent at

equilibrium and time t; k1 (h-1) and k2 (g mg-1 h-1) are the equilibrium constant of

Chapter 3

90

the pseudo-first and pseudo-second models, respectively; t is the adsorption time

(h).

As shown in both Figure 3-4(a) and (b), the aforementioned model can well

describe the experimental data. Their respective parameters are listed in Table 3-1.

Compared between the two empirical models, the pseudo-second-order one is better

for describing the experimental data with the higher correlation coefficient (r2 =

0.99).

Table 3-1. Kinetics parameters with respect to pseudo-first-order and pseudo-

second-order models, [UiO-66] = 0.1 g/L, [As(V)]0 = 60 mg/L, and T = 25±1 oC.

Pseudo-first-order model

Pseudo-second-order model

pH qe

(mg/g)

k1 (h-1) r2

qe (mg/g) k2 (g mg-1 h-1) r2

2.0 42.35 3.18 0.91

44.062 0.124 0.98

7.0 31.47 0.46 0.97

33.765 0.019 1.00

Adsorption isotherm

The arsenate adsorption isotherms of UiO-66 were studied at pH 2 and 7. pH 2 was

opted as it is the optimal condition at which the UiO-66 adsorbent could perform

the best; neutral pH 7 was also selected to represent most natural water. The

isotherms were analyzed using the Langmuir and Freundlich models

In particular, the Langmuir model is applicable for uniform adsorption

processes, and is normally described as monolayer adsorption. The equation for the

Langmuir model can be expressed as Equation 3-4.

𝑞𝑒 = 𝑞𝑚𝑏𝐶𝑒

1+𝑏𝐶𝑒 (3-4)

Chapter 3

91

where qe (mg/g) and Ce (mg/L) are the amounts of analyte adsorbed and the

equilibrium concentration of analyte in solution, respectively; qm (in mg/g)

represents the maximum adsorption capacity of adsorbents (mg/g); and b is a

constant related to the affinity of the binding sites (L/mg).

Moreover, the Freundlich isotherm is based on a multilayer adsorption

model and adsorption occurred on heterogeneous surfaces. The equation is

expressed as Equation 3-5.

𝑞𝑒 = 𝐾𝐶𝑒1/𝑛

(3-5)

where K and n are the Freundlich constants representing relative adsorption capacity

and affinity.

The experimental results together with both Langmuir and Freundlich fitting

lines are plotted in Figure 3-5(a), and the best fitted parameters are summarized in

Table 3-2. The comparatively higher correlation coefficients (r2) of Langmuir

model indicates a monolayer adsorption process in this case. Besides, the arsenate

adsorption capacity of UiO-66 adsorbent, according to the Langmuir isotherms, is

as high as 303.34 mg/g and 147.71 mg/g at pH 2 and 7, respectively.

Figure 3-5. (a) Adsorption isotherm of arsenate onto the UiO-66 adsorbent at pH =

2 and 7; Langmuir fitting model is in red solid lines, Freundlich fitting model is in

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92

blue dash lines; [UiO-66] = 0.5 g/L, pH = 7.0, T = 25±1 oC. (b) Comparison on

arsenic adsorption performance among prevalent adsorbents. This figure was

made based on Table 3-3; working pH range length is defined as how many

integral pH values the working pH range covers.

Table 3-2. Langmuir and Freundlich isotherm parameters for arsenate adsorption

onto UiO-66 adsorbents, [UiO-66] = 0.5 g/L and T = 25±1 oC.

Langmuir isotherm Freundlich isotherm

pH qmax

(mg/g)

b

(L/mg) r2 K n r2

2.0 303.34 6.13 0.92 217.47 9.16 0.83

7.0 147.71 0.42 0.99 62.31 4.74 0.89

Compared to previously reported adsorbents shown in Table 3-2 and Figure

3-5(b), the UiO-66 adsorbent delivers the best arsenic adsorption capacity, much

higher than that of commercial adsorbents (approximately 50 mg/g) and synthetic

adsorbents (5-280 mg/g, generally less than 100 mg/g). Most prevalent adsorbents

can seldom achieve 100 mg/g even at optimal pH. A few recently developed

adsorbents, e.g., γ-Fe2O3 embedded silica and yttrium-manganese binary composite,

exhibited satisfactory arsenic adsorption capacity of more than 200 mg/g. However,

their synthesis methods are quite complicated and costly, and the working pH

ranges are rather limited. With reference to the highest adsorption capacity, the

broadest pH applicable range, as well as the relatively facile method for scalable

synthesis, the UiO-66 adsorbent is regarded as a prospective material for arsenic

removal from water.

Chapter 3

93

Table 3-3. Comparison of arsenate adsorption among prevalent adsorbents.

Sorbent Max. adsorption

capacity (mg/g)

Working pH

range

Ref.

Aluminium-loaded Shirasu-zeolite 5.63 at pH 7 3-10 (Xu et al.,

2002)

Fe-BTC 12.3 at pH 4 2-10 (Zhu et al.,

2012)

Commercial TiO2 14.2 at optimal pH Unknown (Mohan

and

Pittman,

2007)

Activated alumina grains 15.9 at pH 5 2-7 (Lin and

Wu, 2001)

MIL-53(Fe) 21.3 at pH 5 3-6 (Vu et al.,

2015)

Activated carbon 30.5 at pH 7 6-8 (Mohan

and

Pittman,

2007)

Amended SilicateTM adsorbents

(ADA Technologies)

40 at pH 7 6-9 (Frazer,

2005)

ZIF-8 60 at pH 7 6-8 (Yu et al.,

2015a)

Fe–Mn binary oxide 69.8 at pH 5 4-8 (Zhang et

al., 2007)

Nanostructured iron(III)-copper(II)

binary oxide

82.7 at pH 7 3-7 (Zhang et

al., 2013)

Amorphous zirconium oxide

nanoparticles

95 at pH 2 2-7 (Cui et al.,

2012)

Zirconium immobilized nano-scale

carbon

110 at pH 2 2-6 (Mahanta

and Chen,

2013)

γ-Fe2O3 nanoparticles encapsulated

in macroporous silica

248 at pH 6 2-6 (Yang et

al., 2014)

Zirconium based nanoparticle 256.4 at pH 3 2-6 (Ma et al.,

2011b)

Yttrium−manganese binary

composite

279.9 at pH 7 4-7 (Yu et al.,

2015d)

UiO-66 303.3 at pH 2 1-10 This study

Chapter 3

94

Moreover, the used UiO-66 samples after adsorption tests at optimal pH

were examined by SEM-EDX. It can be clearly observed in Figure 3-6 that the

framework morphology was reserved after the adsorption process. The elemental

mapping of used adsorbents verifies the presence of arsenic species within the UiO-

66 framework. Furthermore, the quantitative elemental analysis suggests that the

molecular ratio between Zr and As is approximately 6 to 7.5, based on which the

uptake of arsenic by UiO-66 adsorbents can be calculated. As the chemical formula

of UiO-66 is Zr6O4(OH)4(CO2C6H4CO2)6, one gram of UiO-66 is equivalent to

(1/1662 = 0.60) mmol. Approximately, one UiO-66 cluster containing six Zr atoms

could capture seven As species. Thus, one gram of UiO-66 should be able to capture

(0.60*7 = 4.20) mmol As, which is equivalent to (4.20*75 = 315) mg. This value

agrees well with the isotherm analysis result that specifies an arsenic adsorption

capacity of 303.34 mg/g.

Figure 3-6. SEM image (a) and corresponding EDX data (b-d) of UiO-66 sample.

The green and red signals in (b) and (c) represent Zr and As, respectively. The

Chapter 3

95

quantitative composition of C and O in (d) is not accurate as the carbon tape was

employed as background.

Adsorption mechanism

To better understand the mechanism of arsenate adsorption on the UiO-66 adsorbent,

PXRD and FTIR experiments were conducted to characterize the used materials, as

shown in Figure 3-7(a) and (b). No change was found in the PXRD patterns before

and after adsorption, as all the characteristic peaks are present without the rise of

any new peaks. This confirms the good stability of UiO-66 framework throughout

the test and no damage of the crystal structure. Furthermore, compared the FTIR

spectrum of used UiO-66 sample to that of the pristine material, a significant new

band centered at 830 cm-1 appeared. The 815 cm-1 peak corresponding to the

Zr−O−As group proves the binding of arsenic onto UiO-66 adsorbents (Pena et al.,

2006). Moreover, the peak rising at 865 cm-1 is related to the combination of both

symmetric and asymmetric stretching vibrations of the As–O bond (Mahanta and

Chen, 2013). In addition, a small peak at 660 cm-1 is identified, which would be due

to the presence of As–OH asymmetric stretching (Mahanta and Chen, 2013). The

above findings confirm the formation of arsenic complexes within UiO-66

framework via establishing Zr-O-As coordination bonds.

Chapter 3

96

Figure 3-7. PXPRD patterns (a) and FTIR spectra (b) of UiO-66 samples before

and after use. In (b), the spectra from 600-1200 cm-1 is enlarged in the lower right

corner. Proposed adsorption mechanism of arsenate onto UiO-66 through

coordination at (c) hydroxyl group and (d) BDC ligand. In (d), H atoms in the

cluster are omitted for clarity; (OOC) is part of the BDC linker (-OOC-benzene-

COO-) and linked to another Zr6 cluster.

In a unit cell of UiO-66 framework, there are two different Zr-O linkages:

one is Zr-O(μ3)-Zr bridge in between Zr centers, and the other is Zr-O-C connection

between Zr and BDC linkers. As reported, the hydroxyl groups on adsorbent (e.g.,

Chapter 3

97

metal oxides) surface are primarily responsible for the adsorption of arsenic (Ma et

al., 2011b). Moreover, it can be found that the peak at 1055 cm-1 related to the

bending vibrations of hydroxyl groups on metal oxide clusters (Zr–OH) became

much less obvious after adsorption, as shown in Figure 3-7(b). Thus, the first likely

adsorption site on UiO-66 is the μ3-O, specifically the protonated oxygen

connecting to Zr, which provides four Zr-OH groups in a unit Zr6 cluster to attract

maximum four equivalent arsenate species. As illustrated in Figure 3-7(c), the

arsenate species, e.g., H3AsO4, acted as acid binding to the hydroxyl groups in Zr-

containing clusters, after which the releasing H ions and hydroxyl groups formed

water to maintain charge balance in the solution. Furthermore, the molar ratio

between Zr and As in the used UiO-66 adsorbent was found to be around 6:7

(isotherm study in Section Adsorption isotherm), which implies another possible

adsorption site existing in the UiO-66 framework, i.e., Zr-O-C connection between

Zr and BDC. The adsorption could take place by exchanging some BDC ligands

with arsenate species as illustrated in Figure 3-7(d). The adsorption induced

hydroxyl and BDC ligand exchanges would lead to the formation of arsenic

complexes in the UiO-66 framework, while the aforementioned coordination

processes did not disintegrate the main crystal structure of UiO-66 adsorbent. The

framework remains intact throughout the test according to the PXRD results shown

in Figure 3-7(a).

Furthermore, compared to nanoparticle adsorbents in Table 3-3, Zr-MOF

(UiO-66 in this study) performs better in adsorption attributed to the specific

structural features, i.e. 3D porous framework containing zirconium oxide clusters.

Conventional nanoparticles are generally associated with non-accessible bulk

Chapter 3

98

volume, of which the active sites are only present on outer surface (Zhu et al., 2012).

Amorphous nanoparticles with irregular porous structures may provide larger

contact areas and more active sites, but the improvement is restricted. Generally,

strategic methods to enlarge the adsorbent’s surface area and consequently improve

adsorption performance include reducing the particle size and preparing

hierarchically ordered materials or core shell materials. However, these approaches

would complicate the adsorbent synthesis process and substantially increase the

production cost. MOF, as a highly porous host material with regular crystallinity,

renders a large contact area for the diffusion and interaction of pollutant species.

Howarth and co-workers (2015) reported that Zr-based MOFs are effective for

selenium remediation; NU-1000 in particular, provided the highest adsorption

capacity and fastest uptake rate towards aqueous selenium compounds, owing to

the large apertures and substantial numbers of node-based adsorption sites. With

regard to the UiO-66 adsorbent developed in this study, arsenic as pollutant species

could attach to seven active sites in one unit cluster and the dimension of one unit

cluster is less than unit nanometer. This exposes more active sites on the UiO-66

adsorbent to coordinate with arsenic species compared to most conventional

nanoparticles in unit space.

3.4 Conclusions

In this study, water stable Zr-MOF (UiO-66) with particle size in micrometer order

was synthesized and applied as an adsorbent to uptake arsenate species. To the best

of our knowledge, this is the first work of applying Zr-MOF in arsenic pollutant

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99

removal from water. The UiO-66 adsorbent functioned excellently across a broad

pH range, from very acidic 1 to basic 10, with the best adsorption performance at

pH 2. The presence of some common anions had little influence on the arsenic

adsorption process. Furthermore, the UiO-66 adsorbent achieved a remarkable

arsenate uptake capacity of 303.34 mg/g at optimal pH. This is the best arsenate

adsorption capacity ever reported, much higher than that of other commercial and

synthetic adsorbents (5-280 mg/g, generally less than 100 mg/g). The mechanism

study proposed two binding sites within the adsorbent framework for arsenic

species, i.e., hydroxyl group and BDC ligand. At equilibrium, seven equivalent

arsenic species can be captured by one Zr6 cluster through the formation of Zr-O-

As coordination bonds. To conclude, this study provides significant new insights to

the application of MOFs in water treatment. The enhanced adsorption capacity of

UiO-66 adsorbent compared to most conventional nanoparticle adsorbents was due

to the highly porous structure containing zirconium oxide clusters, which provides

a larger contact area and more active sites in unit space. With the superior

adsorption performance towards aquatic arsenic species, UiO-66 could work as a

promising advanced adsorbent in the arsenic decontamination industry.

Chapter 4

100

CHAPTER 4 USE OF WATER STABLE METAL-

ORGANIC FRAMEWORK UIO-66 FOR EFFECTIVE

UPTAKE OF AQUEOUS SILICA

Chapter 4 is another study of using the hydro-stable Zr-MOF for anionic species

removal from aqueous phase; in this case, aquatic silica is the targeting compound

to be reduced to prevent severe fouling/scaling in industrial processes.

ABSTRACT

Aquatic silica is seldom removed from water prior to its entry into process systems.

Upon its rapid polymerization, it has a tendency to foul heat and mass transfer

surfaces, resulting in the formation of hard, thick scale deposits. Presently, this is a

serious cause for concern amongst the water treatment industries, compounded by

the fact that an efficient remediation method has yet to be implemented. Herein, a

hydro-table zirconium-based metal-organic framework (MOF), UiO-66, was used

as a functional adsorbent for silica adsorption from aqueous solutions. The highest

uptake achieved for UiO-66 was found to be as high as 50 mg-Si per gram of

adsorbent; achieved at pH 10. The presence of common ions – such as calcium,

magnesium and chloride – had negligible impact on the hindrance of the adsorption

process. The monolayer Langmuir model showed to be the best fit for the

equilibrium isotherms and the pseudo-second order kinetics models demonstrated

the best fit for the kinetics data. Through proper characterization and analysis pre-

and post-adsorption, two potential mechanisms were proposed as a result for the

Chapter 4

101

adsorption process. These were the one-to-one and one-to-two binding of silicate

species towards the Zr-hydroxyl groups within the adsorbent’s framework. This is

the first reported study investigating the water chemistry between silica species and

a MOF material. The finding presented herein suggests that the removal of aquatic

silica and fouling prevention through MOF adsorbents have immense potential for

industrial use.

4.1 Introduction

Silica is one of the most abundant elements on Earth, and is found in both crystalline

and amorphous form (Sahachaiyunta et al., 2002). In natural and industrial waters,

amorphous silica is found either in its soluble, colloidal or particulate form (Iler,

1979). In aqueous solutions, soluble (or dissolved) silica is largely present as

monosilicic acid. Silica is seldom removed from water prior to its entry into process

systems. Therefore, at sufficiently high concentrations, it may accumulate and

rapidly polymerize, resulting in the formation of hard, thick scale on membrane and

metallic surfaces (Tokoro et al., 2014). In industry, this scaling/fouling increases

the operating costs associated with running several process units, namely osmosis

driven membranes (both forward osmosis and reverse osmosis) and cooling towers

(Dubin, 1991; Sahachaiyunta et al., 2002). For this reason, there is motivation to

develop effective methods for silica removal from aqueous feeds.

Moreover, there are economic and environmental benefits for the removal

of silica from wastewater. Its recovery can be used for the production of functional

materials and devices manufacturing. For instance, there are significant quantities

Chapter 4

102

of powdered silica waste produced by the semiconductor industry (Lin and Bai,

2013). Silica powder is typically recycled in the alkaline fusion process where it is

reacted with caustic soda and cethyltrimethylammonium bromide (CTAB) to

produce mesoporous silica material (Kim et al., 2011). The material has

applications in CO2 capture and other adsorption processes. If the silica contained

within, say, heavy oil wastewater could be extracted and re-dissolved as part of this

process then one could reduce the amount of waste produced by the chosen

pretreatment process. The advancements made in this area could help improve the

economic viability of the aforementioned pretreatment processes and of silica’s

recycling.

Thus far, several silica removal methods have been proposed, including the

use of antiscalants, softening chemicals and ion-exchange (Dubin, 1991;

Sheikholeslami and Bright, 2002). Although some of these technologies have been

reported, they possess certain disadvantages that contribute to their low economic

viability and operational difficulties (Neofotistou and Demadis, 2004). In contrast,

adsorption-based processes have developed into a favorable option for water

impurities removal due to their general ease of operation and cost-effectiveness

(Mohan and Pittman, 2007). Nonetheless, there are few reports in the current

literature on adsorptive removal of aqueous silica. The search for highly efficient

adsorbents is an ongoing challenge within the scientific communities.

Metal-organic frameworks (MOFs) have been intensively studied as a new

class of hybrid porous materials within the past few years. It has since been

proposed that those MOFs that are water stable could function as promising

adsorbents for wastewater treatment due to their exceptional chemical and physical

Chapter 4

103

properties, properties such as high porosity and surface area, stability over a wide

range of conditions, active functionality and structural versatility (Furukawa et al.,

2013). The emergence of water stable MOFs has provided another potential silica

removal strategy, which has remained unexplored.

Zirconium-based MOFs have been found to exhibit ion exchange behavior

in addition to an affinity for various oxyanions (Howarth et al., 2015a). Typically,

UiO-66 is one prototypic Zr-based MOF with a chemical formula of

Zr6O4(OH)4(CO2C6H4CO2)6 formed into a face-centered-cubic 3D structure. In one

crystal unit, each inorganic cluster is connected to 12 other clusters contributing to

the high stability that is characteristic of UiO-66 (Valenzano et al., 2011). Each

cluster is a Zr6O4(OH)4 octahedron that is linked to the other clusters in the lattice

through the organic BDC (benzenedicarboxylate) linkers (Valenzano et al., 2011).

It has been reported that silicates exhibit a tendency to react with hydroxyl ions that

are directly bonded to transition metals. The similar hydroxyl groups could be

observed as part of the characteristic Zr-O-Zr bridges in UiO-66 framework.

Therefore, we hypothesized that UiO-66 would be an effective adsorbent for

aqueous silica owing to its high hydro-thermal stability as well as the availability

of active adsorption sites.

The aim of this study was to investigate UiO-66's ability to remove silica

from aqueous solutions. To the authors’ best knowledge, this is the very first report

on using MOFs for aqueous silica uptake. Multiple adsorption tests were performed

to determine the effect of pH and co-existing ions on adsorption. The

thermodynamic capacity of the process was investigated through the analysis of

adsorption isotherms. Additionally, studies investigating the adsorption kinetics

Chapter 4

104

was performed. Post-synthesis characterization was performed using powder X-

Ray diffraction (PXRD), scanning electron microscopy (SEM), Fourier transform

infrared microscopy (FTIR), and X-ray photoelectron spectroscopy (XPS).

Performing this particular study would provide an insight into the surface structure

of pristine and spent UiO-66 as well as the adsorption mechanism that is taking

place within the MOF structure.

4.2 Materials and methods

4.2.1 Materials and UiO-66 synthesis



99.5%), 1,4-benzenedicarboxylic acid (BDC, 98%), 2-propanol (99.5%), calcium

chloride (CaCl2, 99.99%), magnesium chloride hexahydrate (MgCl2∙6H2O, 98%),

and sodium metasilicate (Na2SiO3, analytical grade) were purchased from Sigma-

Aldrich. Ethanol (99.9%), dimethylformamide (DMF, 99.9%), nitric acid (HNO3,

68%), sulfuric acid (H2SO4, 98%) and sodium hydroxide (NaOH, 99%) were

purchased from VWR. The synthesis of UiO-66 can be referred to as shown in

Section 3.2 (see Chapter 3).

4.2.2 Characterization techniques

X-Ray Diffraction (XRD)

The crystallinity of the as-synthesized UiO-66 was analyzed using Powder XRD

(PXRD, Panalytical Xpert) to ensure that the MOF had the same structure as that

Chapter 4

105

found in the literature. Spent UiO-66 (preparation see below) was also examined to

verify whether silica adsorption has any effect on its crystal structure. To be ready

for XRD study, the samples were dried at 120 oC overnight under vacuum condition.

The diffractometer generates X-rays of known frequency (monochromatic) that

diffract upon interaction with the crystalline sample as a result of the periodicity of

the framework. Herein, it is operated with Ni-filtered Cu Kα radiation at a voltage

of 40 kV and a current of 40 mA. The diffraction pattern, which contains key

information about the structure of the sample, is analyzed by the PXRD to allow

the crystallinity of the sample to be determined.

Fourier Transform Infrared Spectroscopy (FTIR)

The chemical properties of pristine, as well as spent UiO-66 (preparation see below),

were analyzed using FTIR (Spectrum 100, PerkinElmer) equipped with diamond

ATR (attenuated total reflection) crystal. The samples were prepared by drying

under vacuum for 24 h prior to the analysis. This was to ensure that moisture on the

samples did not result in unnecessary spectral peaks. Background measurements

were taken at the onset to make sure that these were not attributed to sample

characteristics. Sample measurements were taken by covering the sample holder

completely with UiO-66 and lowering the pressure arm until the Force Gauge

displayed a value of about 80. The sample holder was cleaned with isopropanol to

remove any residual sample.

Chapter 4

106

Scanning electron microscopy (SEM)

SEM was used to determine the morphology of pristine UiO-66. Metallic sample

holders were covered with double-sided tape on which a layer of MOF was

deposited and immobilized using air spray. This was followed by a layer (10 nm)

of chromium coating to ensure that the MOF was covered with a conductive layer,

which prevents charge accumulation on the sample, giving an improved image

quality. Finally, the samples were analyzed in the LEO Gemini 1525 microscope

coupled with Energy-dispersive X-ray (EDX).

X-ray photoelectron spectroscopy (XPS)

The chemistry of virgin and adsorbed materials was studied by the XPS (Kratos

XPS System-AXIS His-165 Ultra, Shimadzu, Japan) with a monochromatic Al Kα

X-ray source (1486.6 eV). The high-resolution scans were conducted according to

the peak being examined with a pass energy of 40 eV and step size of 0.05 eV. The

C 1s signal of an adventitious carbon was used as reference to compensate the

charging effect at a binding energy (BE) of 281.6 eV. The XPS results were

collected in binding energy form and fit using a non-linear least-square curve fitting

program (XPSPEAK41 Software). During peak processing, a linear background

subtraction was opted for non-metal elements, whilst a Shirley type background

subtraction was selected for transition metals. The peak's full width half maximum

(FWHM) was fixed during the fitting, normally between 0.8-2 eV.

Chapter 4

107

4.2.3 Adsorption studies

Preparing stock solution

After the UiO-66 synthesis and prior to further experimentation, a 1L stock solution

was prepared. The solution was comprised of sodium silicate (Na2SiO3) dissolved

in deionized water, and was made such that the soluble (and total) silica

concentration was 100 ppm. As experiments were performed, volumes of the

solution were taken and diluted as appropriate with additional deionized water.

Optimal pH investigation

As part of the adsorption studies, experiments were performed to determine the

optimal pH for silica adsorption by UiO-66. Using the stock solution, a series of

other solutions (silica concentrations of 20 ppm) were prepared within plastic

bottles. The original pH of each solution took a value between 11 and 12. Therefore,

the pH was altered (1 to 10) prior to the addition of any UiO-66. pH adjustment was

conducted using a series of nitric acid or sodium hydroxide with concentrations

ranging from 1 M to 0.001 M. The pH of solutions was measured by an ORION

525A pH meter. Due to the small volumes required, the acid/base was introduced

using a calibrated micropipette. Upon altering the pH, an initial sample of 5 ml was

taken from each solution. This was to provide a dosage of 0.2 mg/L once 0.01 g of

dry UiO-66 was weighed and added. The adsorption tests were investigated at room

temperature (25 ± 1 oC). After four days (96 h), i.e. well after the time required to

reach equilibrium, the pH of each solution was recorded and a sample was taken

using a disposable syringe and Millipore filter (purchased from Sigma Aldrich). As

Chapter 4

108

with all samples, those from this experiment were analyzed using an inductively

coupled plasma emission spectrometer (ICP-OES, Optima 2000 DV, PerkinElmer).

Effect of co-existing ions

To determine the effect of co-existing ions on the uptake performance of UiO-66,

various concentrations of Mg2+ and Ca2+ ions have been added to 20 ppm silica

solutions. Again, the solutions were prepared within plastic bottles and initially

contained 55 ml. One solution contained 100 ppm of Mg2+ ions and another

contained 500 ppm of Ca2+ ions. A third solution was made with both Mg2+ and

Ca2+ ions at their respective concentrations shown above. The cations were added

through their chlorides namely CaCl2 and MgCl2∙6H2O. Therefore, a fourth solution

was prepared with 500 ppm of Cl- ions and 20 ppm of silica. Subsequently, the pH

of each solution was altered to the newly-found optimum, and an initial sample was

taken as above, before UiO-66 was added. Final samples after a four-day period

were also taken as previously mentioned.

Isotherm and kinetics studies

To obtain the isotherm for silica adsorption, the concentration of silica initially in

solution was varied. The plastic bottles contained 55 ml of solution with silica

concentrations ranging from 1 to 40 ppm. Again, 0.01 g of UiO-66 was added after

taking initial samples and altering the pH to the optimal value. Samples were also

taken after four days and analyzed using ICP. Furthermore, two 500 ml solutions

containing 10 and 15 ppm silica were prepared within plastic bottles with large

volumes. The pH of both solutions was adjusted to the optimal value found for silica

Chapter 4

109

adsorption prior to initial sample taking and the addition of 0.1 g of UiO-66 (0.2

g/L dosage). Samples were routinely taken throughout a four-day period and

analyzed using ICP to ascertain the concentration of silica remaining in solution.


4.3.1 Characterizations of UiO-66

The as-synthesized UiO-66 were examined through basic characterizations. The

results can be referred to as shown in Figure 3-2 (see Chapter 3). The PXRD pattern

and FTIR spectrum indicate that the pristine UiO-66 was correctly synthesized as

the PXRD peaks and the FTIR bands are in agreement with those found in literature.

The FTIR band peaks at 1590 and 1390 cm-1 can be attributed to the carboxylate

groups that connect the Zr-based clusters and the BDC linkers in the MOF’s

structure, as shown in Figure 3-2(a) (see Chapter 3). The band peaks observed at

720 and 620 cm-1 can be ascribed to the characteristic Zr-O bonds in the framework.

The wide band at 3350 cm-1 is present due to the water that is adsorbed from air

during sample measurements. In addition, the SEM image shows a crystalline

material with sharp edges that has been effectively intergrown. The surface features

of the pristine UiO-66 are in agreement with the literature as the SEM image is

similar to that obtained by Cavka et al. (2008).

4.3.2 Optimal pH for adsorption

Identifying how pH influences the adsorption of silica is vital. If an industrial

process using UiO-66 was to be implemented in the future, the operating condition

Chapter 4

110

under optimal pH must be well understood. Moreover, the pH effect could unveil

insightful information with regards to the adsorbent and the adsorption process.

Here, we carried out the silica adsorption tests in batch mode across the pH range

of 1-10. This pH range used was due to the understanding that UiO-66 would not

lose its structural integrity from pH 1 to 10. The respective silica uptake was

summarized in Figure 4-1 with respect to each pH conditions. The UiO-66

adsorbent demonstrated low uptake within acidic environments, which continued

through to neutral and alkaline conditions. The uptake achieved at pH 1 was

particularly poor, with only 1.2 mg of silica (measured as silicon) being adsorbed

per gram of adsorbent. The performance at pH 10 was exceptional and considerably

better than the others obtained. The value obtained was 49.6 mg/g, which is

comparatively higher than other non-adsorption, such as lime softening processes

(Al-Rehaili, 2003). Moreover, from the bar chart, it can also be seen that the level

of uptake increases with pH. The reason for this, and the superior performance at

pH 10, could stem from the dissociation of monosilicic acid. Theoretically,

monosilicic acid is the primary form of amorphous silica at low concentrations.

According to the dissociation of silica (Figure 2-6, see Chapter 2), there is the

indication that only when the pH is above 9.9 do silicate ions represent the major

form of silica in solution. At pH 1, the ratio of monosilicic acid molecules to silicate

ions is over 7 million:1. Hence, there is the possibility that the rising adsorption

capability is due to the increased prevalence of silicate ions at higher pH. This is to

be discussed further later. At this point, the conclusion can be made that the

optimum pH for the uptake of silica by UiO-66 is pH 10.

Chapter 4

111

Figure 4-1. Silica uptake with UiO-66 adsorbent at different pH values.

4.3.3 Effect of co-existing ions

The concentration of Ca2+ and Mg2+ ions used were chosen to replicate those found

in the literature for brackish waters with comparable silica concentrations

(Hamrouni and Dhahbi, 2001). The bar chart presented in Figure 4-2 shows silica

uptake in the presence of other co-existing ions. The horizontal dashed line indicates

the value of 49.6 mg/g obtained at pH 10 (at 20 ppm). The effect of the Ca2+ ions

on the performance of UiO-66 was observed to be minimal. The effect of having

Mg2+ ions and both cations together in solution was also found to not adversely

affect the adsorption process. The additional experiment with chloride ions did

provide a slight decrease in the uptake of silica, which was within the error range,

although the concentration used is significantly larger than that found within most

natural and industrial waters. In addition, the influence of coexisting multivalent

anions such as sulfate and phosphate had also been evaluated. It was found that the

adsorption process was not affected by sulfate species at all, whilst phosphate

species demonstrated a mild competing effect.

Chapter 4

112

Figure 4-2. Silica uptake with UiO-66 in presence of coexisting ions.

4.3.4 Isotherm study

An adsorption isotherm study was performed for the uptake of silica by UiO-66 at

ambient conditions and at pH 10, i.e. the optimal pH found. The study allowed for

the determination of the maximum silica uptake, which represents the

thermodynamic limit at which all the adsorption sites are occupied. Adsorption

isotherms also provide information about the amount of adsorbed silicate that would

be obtained for a particular equilibrium solute concentration. The data collected was

fitted using the Langmuir and Freundlich isotherms.

Figure 4-3 shows the experimental data fitted with both isotherms, along

with the fitting parameters of Langmuir model shown in Table 4-1. it is still

pertinent as it indicates that monolayer adsorption was a significant contributor to

the removal of silica from aqueous solutions. The Langmuir isotherm provides a

maximum monolayer capacity of 54.6 mg(silicon)/g(adsorbent), which is closely

Chapter 4

113

matched by the value of 49.6 mg(silicon)/g(adsorbent) obtained, at pH 10, in this

work. This strengthens the possibility of a primarily monolayer adsorption process.

Figure 4-3. Adsorption isotherm of silicate onto UiO-66 at pH = 10 and room

temperature together with fitted adsorption isotherm.

Table 4-1. Langmuir isotherm fitting parameters for silicate adsorption of UiO-66.

4.3.5 Kinetics study

In order to gain an insight into the adsorption mechanism and its rate-controlling

step in the uptake of silica, adsorption kinetics studies were performed with two

different initial silicate concentrations. The data collected was fitted with the

pseudo-first order and the pseudo-second order kinetics models. The fitting

parameters can be found in Table 4-2.

Chapter 4

114

It can be found that the pseudo-second order kinetics model has a much

better fit for the data compared to the pseudo-first model. This is confirmed by its

r2 value, which is greater than 0.99 for both initial solute concentrations. The poor

fit for the pseudo-first model indicates that diffusion within or at the surface of the

adsorbent is not the limiting step for the adsorption process (Crini and Badot, 2008).

The pseudo-second order model shows a very good fit for the data for the whole

duration of the experiment. This result suggests that the rate-limiting step in the

adsorption process could be the adsorbate-adsorbent surface interactions, which is

indicative of a complexation process involving electron exchange between the

adsorbent and the solute (Crini and Badot, 2008; Febrianto et al., 2009). The

applicability of the pseudo-second order kinetics model is also demonstrated by its

ability predict the equilibrium silica uptake, qe, within 3% of the actual value as can

be seen in Table 4-2. This is not the case for the pseudo-first order kinetics model,

which provides a large underestimation in this regard. Figure 4-4 shows the

experimental data fitted with the pseudo-second order model for the two initial

silica concentrations used in the study. Equilibrium was reached in about 6 h for C0

= 10 ppm (mg/L) and approximately 4 h for C0 = 15 ppm (mg/L).

Chapter 4

115

Figure 4-4. Adsorption kinetics of silicate adsorption onto UiO-66 adsorbents.

Table 4-2. Kinetic models and fitting parameters regarding the silicate adsorption

kinetics using UiO-66 adsorbents.

Kinetics model Parameters

Initial silicate concentration

10 ppm case 15 ppm case

Pseudo-first order

k1 (1/h) 0.0523 0.0205

qe calculated (mg/g) 4.91 6.67

R2 0.636 0.307

Pseudo-second order

k2 (g/mg∙h) 0.0598 0.853

qe calculated (mg/g) 16.2 30.0

R2 0.998 0.996

Experimental qe (mg/g) 15.9 30.8

4.3.6 Post-adsorption analysis

Following the adsorption process, spent UiO-66 was analyzed using XRD, FTIR

and XPS. In particular, no change was found in the PXRD patterns (Figure 4-5), as

Chapter 4

116

all the characteristic peaks were found to still be present without the rise of any new

peaks. This confirms the consistent stability of the UiO-66 framework throughout

the adsorption process and maintenance of the crystal structure.

Figure 4-5. PXRD patterns for pristine and spent UiO-66.

Furthermore, the FTIR spectra that are associated with both pristine and

spent UiO-66 shown in Figure 4-6 were carefully compared and analyzed. By doing

so, the presence of new chemical groups could be identified, and thus, the spectra

could act as supporting evidence for the adsorption of silica and the understanding

of adsorption mechanism. The new broad band centered at 956 cm-1 is indicative of

the stretching vibrations of Si-O-Zr confirming that silica had successfully adsorbed

in the MOF via its zirconium atoms (Kongwudthiti et al., 2003). At 726 cm-1 and

1254 cm-1, new peaks are observed that are similarly attributed to the stretching

mode of the Si-O bond (Kongwudthiti et al., 2003). Furthermore, the new peak

obtained around 3662 cm-1 is attributed to the stretching mode of the O-H bond

(Kongwudthiti et al., 2003). This is likely in reference to the hydroxyl groups within

Chapter 4

117

silicate species; also, it is possible that the peak is an indication of the increased

coordination of the Zr atoms, and the new adsorption sites formed.

Figure 4-6. FTIR spectra for pristine and spent UiO-66.

In addition, the post-adsorption UiO-66 materials were examined by XPS to

further explore the insightful information on the adsorption mechanism. The high-

resolution scan spectra with respect to the key elements – Si (2p), Zr (3d) and O (1s)

– are shown in Figure 4-7. First of all, the Si 2p peak appears at 99 eV, again this

confirms that the silica is adsorbed in the UiO-66. As the literature specifies that

the [ZrSiO4] group presents a Si 2p peak at 99 eV, the interaction between the UiO-

66 and the silica compounds shall form such complexes at the end of the uptake

(Thermo scientific XPS database). Next, as shown in Figure 4-7(b), the high-

resolution scan of O1s spectrum can be divided into three component peaks, of

which the sub-peaks at binding energy of 524.13, 525.42, 525.62 eV can be

assigned to respective oxygen state in O-Zr, O-Si, O-C bonds (Jerome et al., 1986;

Wagner et al., 1979b). Moreover, the high-resolution scan of Zr 3d spectrum

demonstrated three sub-peaks at 176.01, 176.53 and 177.02 eV, which correspond

Chapter 4

118

to the Zr-O-C (Zr-carboxylate), Zr-O-Zr and Zr-O-SiO3, respectively (Bosman et

al., 1996; Jerome et al., 1986). The information of binding energy as well as relative

content in regards to these component peaks has been summarized in Table 4-3, to

serve as a reference for the mechanism study.

Figure 4-7. High resolution scan XPS spectra on spent UiO-66 adsorbent with

respect to: (a) Si 2p, (b) O 1s, and (c) Zr 3d orbitals.

Table 4-3. Binding energy and relative contents of relevant peaks in XPS spectra

of spent UiO-66 sample.

Element

orbital

Proposed

component

Binding energy

(eV)

Relative content

(%)

Si 2p SiO4-Zr 99 100

O 1s

O-Zr 524.13 21.6

O-Si 525.42 53.6

O-C 525.62 24.8

Zr 3d

Zr-O-C 176.01 43.3

Zr-O-Zr 176.53 37.1

Zr-O-SiO3 177.02 19.6

Chapter 4

119

4.3.8 Adsorption mechanism

Based upon the post-adsorption characterizations and analyses, it has been

established that there are new complexes formed in the structure due to the silica

adsorption. It can be deduced from the appearance of the Zr-O-Si bond that the

binding of silica species onto the zirconium unit of UiO-66 is the process that has

taken place. At the end, the [ZrSiO4] complexes should exist in the post-adsorption

UiO-66 structure. Hence, we proposed two mechanisms as shown in Figure 4-8,

which may be responsible for the silica adsorption. Mechanism A involves the one-

to-one complexation with one molecule of silicate onto one hydroxyl group in the

Zr-clusters of UiO-66. Mechanism B relies on the one-to-two complexation of

silicate species with zirconium, of which one silicate molecule replacing two

hydroxyl groups in the zirconium-based clusters of UiO-66. It has been well

understood that, within UiO-66, there are four hydroxyl groups in each zirconium-

based cluster. Therefore, for Mechanism A there would be four adsorption sites per

cluster, while for Mechanism B there would be two adsorption sites per cluster.

Figure 4-8. Proposed adsorption mechanisms (excluding hydroxyl ions and water

molecules released).

Chapter 4

120

Table 4-4. Maximum theoretical silicate uptake for Mechanisms A and B in

comparison to the experimental uptake at pH 10.

Theoretical uptake (mg-Si/g-adsorbent) Experimental

uptake (mg-Si/g-

sorbent)

Mechanism A solely Mechanism B solely

67.2 33.6 49.6

The maximum silica uptake for Mechanism A was calculated through the

following steps: The number of moles of UiO-66 in 1 g = 1/1662 = 0.60 mmol.

Where 1662 is the molar mass of UiO-66 in g/mol, obtained from its molecular

formula; Zr6O4(OH)4(CO2C6H4CO2)6. For Mechanism A, each cluster can capture

up to four silicate molecules, leading to a 1:4 MOF to silicate molar ratio. Therefore,

the amount of silicate adsorbed is 0.60 * 4 = 2.4 mmol = 67.2 mg (Si). This indicates

that if solely Mechanism A was taking place, an uptake of 67.2

mg(silicon)/g(adsorbent) would be expected. Likewise, if only Mechanism B

effects in the process, we shall observe an uptake up to 33.6

mg(silicon)/g(adsorbent). However, when we compare the experimental uptake at

pH 10 with the maximum theoretical silicate uptake with respect to Mechanisms A

and B, as shown in Table 4-4, the experimental uptake is intermediary between the

uptake values for the two mechanisms. Therefore, it can be deduced that during

silica adsorption, both mechanisms contribute to the overall process. Thus, the

possible manifestation of the two mechanisms is believed to lead to the intermediate

experimental uptake that was obtained.

Chapter 4

121

4.4 Conclusions

In this study, UiO-66 has been successfully synthesized and characterized pre- and

post-adsorption. From the results obtained and discussed herein, several insightful

conclusions can be made on the adsorption of silica by UiO-66. Firstly, it has been

successfully demonstrated that the adsorption of silica is greatly optimized at a pH

of 10, achieving an uptake of 50 mg/g. The actual process has been confirmed

through both XPS and FTIR analyses, with the obtained spectra showing the

stretching vibrations of the newly-formed Si-O-Zr bonds and ZrSiO4 complexes.

Along with this, a viable mechanism for the adsorption process has also been

proposed, which offers a suitable explanation for the excellent performance

observed at pH 10. Furthermore, high concentrations of coexisting ions, namely

Ca2+ and Mg2+ ions, do not adversely affect the adsorption of silica by UiO-66,

which bolsters the possibility of its use in treating chemically hard waters.

Chapter 5

122

CHAPTER 5 METAL-ORGANIC FRAMEWORK/α-

ALUMINA COMPOSITE WITH NOVEL GEOMETRY

FOR ENHANCED ADSORPTIVE SEPARATION

Based on the first-stage studies in the previous two chapters, Chapter 5 combines

the functional MOF adsorbents with specifically designed ceramic hollow fibers for

enhanced adsorptive separation. This chapter aims at resolving the typical binder

problem, which is critical when particle-form adsorbents are to be incorporated in

industrial adsorption processes. With this study, it is anticipated that all the

functional MOF adsorbents can be put into effective use with optimized process.

ABSTRACT

UiO-66, as a prototypical zirconium-based metal-organic framework (MOF),

provides a rapid uptake of arsenic from water when compared to other typical

adsorbents with the same order-of-magnitude particle size. This fast kinetics allows

an efficient adsorptive separation to be realized within a micro-space. Moreover, α-

alumina can be specifically structured into a novel hollow fiber geometry:

containing a plurality of open radial micro-channels on the shell side and a very thin

barrier layer at the lumen. Through a facile vacuum filtration method, a MOF/α-

alumina composite with novel geometry is developed and optimized in this study.

The composite leads to a new concept for enhanced adsorptive separation: efficient

adsorption occurs within numerous conical micro-channels with no loss of the

active adsorbents during the process. As a proof of concept, this composite can

Chapter 5

123

effectively remediate arsenic contaminated water producing potable water recovery,

whereas the conventional fixed bed requires eight times the amount of active

adsorbents to achieve a similar performance. Looking forward, different functional

composites can be prepared based on specific adsorptive applications, as a wide

range of adsorbents can be loaded into the α-alumina hollow fiber, of which the

micro-channel size and barrier layer pore size can be easily manipulated during

fabrication.

5.1 Introduction

Separation is a process that divides a mixture of substances into pure constituents,

and it is one of the most crucial processes in most industrial sectors. Among various

separation techniques, adsorptive separation is a process widely applied in most

industrial sectors to achieve purification of liquid or gas mixtures (Ali, 2012). In

particular, it plays a significant role for water quality control through removing

impurities from wastewater streams, owing to its simplicity, efficiency, flexibility

in design and low waste production (Ali, 2012; Nam et al., 2015; Yu et al., 2015b).

Currently, in order to introduce an effective adsorption process for wastewater

remediation, various fixed or fluidized beds are employed in industry (Dąbrowski,

2001). These setups allow fluid stream to contact with the porous adsorbent media

and induce proper adsorption processes along the way. Despite that, certain

disadvantages of using adsorption beds are inevitable (Dąbrowski, 2001). For

instance, the column may cause large pressure drop because of too-dense packing;

also, channeling of fluid stream may occur, leading to nonideal flow in the

Chapter 5

124

adsorption media. In fluidized bed configuration, the problem of channeling can be

suppressed, but it is likely to result in the attrition and break-up of adsorbent pellets

and these unfavorable residuals may escape from the bed reactor, requiring

additional post-treatment of the effluents. Hence, novel concepts and designs on

how to achieve more effective adsorption are imperative (Ali, 2012).

Following the above remarks, the development of adsorption processes

cannot be considered separately from development of adsorbent materials. Metal-

organic frameworks (MOFs), a new type of porous materials constructed by joining

metal-containing units with organic linkers through coordination bonds, has

attracted substantial attention in the scientific communities (Furukawa et al., 2013;

Y.-S. Li et al., 2010; Zhou and Kitagawa, 2014). Owing to their unique properties

like exceptionally high porosity, large surface area and customizable chemical

functionality, MOF materials have exhibited a great potential in adsorption

applications (Fu et al., 2013; Furukawa et al., 2014; Khan et al., 2013).

One of the representative examples is UiO-66 (Cavka et al., 2008; Hu and

Zhao, 2015; X. Liu et al., 2015; Shang et al., 2014; Yee et al., 2013), a prototypical

Zr-MOF constructed with Zr6O4(OH)4 clusters and terephthalate linkers (1,4-

benzenedicarboxylate, BDC) (Cavka et al., 2008). Our previous study unveiled that

UiO-66 can effectively remove arsenic from water with the up-to-date highest

capacity (303 mg/g) and widest pH working range (pH 1-10) (Wang et al., 2015).

Further to the outstanding thermodynamics performance, the UiO-66 adsorbent also

exhibits a rapid uptake profile for arsenic adsorption. Comparing to other typical

arsenic adsorbents (Zr nanoparticle sorbent, Y-Mn binary composite, and Fe-

exchanged zeolite) with particle sizes of several hundred nanometers (Li et al., 2011;

Chapter 5

125

Ma et al., 2011a; Y. Yu et al., 2015c), as shown in Figure 5-1, the UiO-66 adsorbent

with similar particle size could provide a much faster adsorption rate (at least

fivefold faster, in terms of the initial reaction rate constant). This fast kinetics allows

an efficient adsorptive separation process to be realized within a micro-space (i.e.

very short distance).

Figure 5-1. Arsenic adsorption kinetics comparison: UiO-66 and other typical

sorbents with same order-of-magnitude particle size (Z. Li et al., 2011; Ma et al.,

2011a; Y. Yu et al., 2015c).

Despite all the preferable performance of UiO-66, in order to be industrially

applicable, the powder materials need to be specifically shaped or supported (Tesh

and Scott, 2014; Wisser et al., 2015). This is because in practical applications,

dispersed particles could easily leak through the application compartment, resulting

in challenging spent-particles-separation issues and severe safety concerns (J. He et

al., 2014b).

Herein, we developed a MOF/α-alumina composite (composite-1) to take

advantage of both the fast kinetics of UiO-66 adsorbents and the novel hollow-fibre

Chapter 5

126

geometry of α-alumina for enhanced adsorptive separation, as shown in Figure 5-2.

The α-alumina was deliberately structured to work as a ceramic hollow fiber

providing a plurality of micro-channels for efficient adsorptive separation as well

as a thin barrier layer to prevent any loss of the active adsorbents. In comparison

with traditional packed column beds, composite-1 delivered a more effective

adsorption process and consequently better water decontamination performance.

Figure 5-2. Schematic diagram of adsorptive separation by composite-1: for

arsenic contaminated water remediation. The inset demonstrates an enlarged

cross-sectional view of composite-1. Blue molecule: water; green molecule:

arsenic pollutant.

Chapter 5

127


5.2.1 Materials

Unless otherwise stated, all the chemicals were used as received without further

purification. The chemicals including triethyl phosphate (TEP, HPLC grade), acetic

acid (AC, HPLC grade), zirconium(IV) chloride (ZrCl4, 99.5%), 1,4-

benzenedicarboxylic acid (BDC, 98%), and sodium arsenate dibasic heptahydrate

(Na2HAsO4.7H2O, 98%) were purchased from Sigma-Aldrich. Those including

dimethyl sulphoxide (DMSO, HPLC grade), dimethylformamide (DMF, 99.9%),

ethanol (99.9%), nitric acid (68%), and sodium hydroxide (99%) were purchased

from VWR. Moreover, aluminum oxide (Al2O3) (alpha, 99.9% metals basis, surface

area 6-8 m2/g, mean particle size (d50) 1µm, Inframat Corporation) as well as

Polyethersulfone (PESf) (Radal A300, Ameco Performance) and Arlacel P135

(polyethylene glycol 30-dipolyhydroxystearate, Uniqema) were used as supplied.

Besides, the stock solution of 1 mg/L arsenate was obtained by dissolving

Na2HAsO4.7H2O in deionized (DI) water (Analytic lab, ACEX, Imperial College

London).

5.2.2 Methods

UiO-66 preparation

UiO-66 was prepared based on the procedure described by Cavka et al. (Cavka et

al., 2008; Lu et al., 2013; Schaate et al., 2011), with some modifications. Acetic

acid (AC), 1,4-benzenedicarboxylic acid (BDC) and ZrCl4 were dissolved in DMF

one after another under stirring in a glass bottle at room temperature, according to

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128

a specific molar composition: Zr/BDC/AC/DMF = 1:1:160:870. The solution was

then transferred to Teflon-lined stainless steel autoclaves and heated at 120 oC for

24 h in a convective oven (UF30, Memmert). Afterwards, the autoclaves were

cooled down to room temperature. The UiO-66 powders were washed by ethanol

with the assistance of centrifuge (Thermo Scientific Legend X1R) and dried at 120

oC overnight under vacuum condition (Fistreem Vacuum Oven) for further use.

α-Alumina hollow fiber preparation

The α-alumina hollow fibers were fabricated by the combined phase-inversion and

sintering method, described by Lee et al. with some modifications (Lee et al., 2016),

using a triple-orifice spinneret. To start with, a uniform suspension was prepared

via ball milling, which composed of alumina particles (59.9 wt.%), NMP solvent

(33.6 wt.%) and PESf polymeric binder (6.0 wt.%), as well as an additive (Arlacel

P135) acting as a dispersant (0.5 wt.%). This suspension was then degassed under

vacuum with stirring to fully remove bubbles, and then transferred into a 200 mL

stainless steel syringe that was controlled by a syringe pump (Harvard PHD22/200

HPsi and KDS410). NMP solvent was transferred into a 100 mL stainless steel

syringe controlled by another syringe pump. DI water was used as the bore fluid,

and was extruded together with the α-alumina suspension in the center layer and

NMP solvent in the outer layer through the spinneret into the external coagulation

bath (see Table 5-1). When phase-inversion was complete, the hollow fiber

precursors were removed from the external coagulant bath, and were then dried and

straightened at room temperature. Afterwards, they were cut into the required length

for subsequent calcination and sintering (at 1500 °C).

Chapter 5

129

Table 5-1. Spinning parameters for α-alumina hollow fiber

Spinning parameters

Flow rate (mL/min)

Ceramic layer 7

Solvent layer 5

Bore fluid 40

Air gap (cm) 25

MOF/α-alumina composite preparation

0.5 g UiO-66 crystals were suspended in 1 L water, and it was under constant

agitation to ensure a homogeneous distribution. The lumen of α-alumina hollow

fiber was in vacuum condition, and the water solution carrying MOFs flowed from

the shell side into the lumen, as shown in Figure 5-3. Each composite required 5

minute of the vacuum filtration process. Afterwards, the composites were left in

ambient atmosphere for drying. The solid residuals attached to the outer surface of

the α-alumina hollow fibers were carefully wiped off using delicate task wipers

(Kimtech Science KimWipes).

Figure 5-3. Scheme of vacuum filtration process.

Chapter 5

130

Adsorption kinetics experiments

The adsorption kinetics experiment was carried out at initial arsenate concentration

of 20 mg/L with adsorbent dosage of 0.1 g/L, and the solution pH value was

controlled at 2.0 during adsorption process by adding a certain amount of NaOH or

HNO3. After adsorption experiments, the solution was filtered using 0.22 μm

syringe filter and arsenate concentration was measured by an inductively coupled

plasma optical emission spectrometer (ICP-OES, Optima 2000 DV, PerkinElmer).

Breakthrough study experiments

The feed solution used in breakthrough experiments had arsenic concentration of 1

mg/L and a pH of 2.0. It was introduced to both composite-1 and equivalent packed

columns from a syringe pump (Nexus 6000, Chemyx). In the case of composite-1,

one end was sealed and the other end served as the outlet, as shown in Figure 5-4.

In the case of packed columns, active MOF adsorbents were packed and held by the

filter papers, as shown in Figure 5-5. After collecting recovery samples, an aliquot

of each sample was analyzed using ICP-OES for residual arsenic concentration

measurement.

Figure 5-4. Prototype of experiment setup, using composite-1 for arsenic

contaminated water remediation.

Chapter 5

131

Figure 5-5. Prototype of experiment setup, using packed column bed setup for

arsenic contaminated water remediation.


5.3.1 Optimization of composite

Generally, α-alumina (Figure 5-6(a)) is a raw material that is abundant in supply

and able to provide great resistance to various chemical and thermal conditions.

Through controllable spinning and sintering (Lee et al., 2016; Lee et al., 2014), we

specifically prepared α-alumina in a hollow fiber structure. Its novel geometry with

two distinct layers is shown in Figure 5-7: one very thin barrier layer (approximately

20 µm of thickness, and with an average pore size around 450 nm as shown in

Figure 5-8) containing 3D-pore network structure at the lumen, and also one unique

layer containing a plurality of conical micro-channels (approximately 500 µm in

length, 25 µm in opening diameter as shown in Figure 5-9) towards the shell side.

These micro-channels not only reduce the mass transfer resistance, giving rise to

Chapter 5

132

competitive permeation fluxes (Lee et al., 2015; Lee et al., 2014), but also form

pockets within which active adsorbents can be readily deposited. As the density of

formed micro-channels is quite high, the α-alumina hollow fiber offers a

considerable amount of geometric surface area and accessible volume (Lee et al.,

2015).

Figure 5-6. SEM images: (a) Alumina particles constituting the walls of ceramic

hollow fiber micro-channels. (b) Scattered UiO-66 crystal particles. (c) Enlarged

view inside the micro-channel showing UiO-66 crystals stay with alumina

particles. Yellow shades indicate the octahedral UiO-66 crystals.

Chapter 5

133

Figure 5-7. SEM and TEM images: (a) Cross section of α-alumina hollow fiber;

the yellow dashed circle signifies two distinct layers. (b) Enlarged cross-sectional

view showing open micro-channels; yellow lines highlight three examples of

micro-channels. (c) Outer surface morphology of α-alumina hollow fiber, showing

the opening of micro-channels at the shell side. (d) Inner surface of α-alumina

hollow fiber. (e) UiO-66 crystals; the inset with yellow dashed line border shows

the corresponding TEM image. (f) UiO-66 crystals deposited within micro-

channels; micro-channel walls are formed by the packing of alumina particles;

yellow shades indicate the deposited octahedral UiO-66 crystals.

Chapter 5

134

Figure 5-8. Pore size distribution of the 3D pore structure of α-alumina hollow

fiber. (Pore size determination was carried out using a gas-liquid displacement

technique and was undertaken according to an established method with PoroLux

100 Porometer.)

Figure 5-9. Outer surface of α-alumina hollow fiber (micro-channel opening).

UiO-66 used in this study was synthesized via the typical solvo-thermal

method with minor modification in order to render a greater surface area for fast

reactive kinetics (Cavka et al., 2008; Lu et al., 2013; Schaate et al., 2011). Its

characteristic XRD pattern (see Figure 5-10) and N2 adsorption-desorption

Chapter 5

135

isotherms (see Figure 5-11) confirm the crystal structure and porosity of this Zr-

MOF, respectively (Cavka et al., 2008). As shown in Figure 5-6(b) and 5-7(e), the

UiO-66 crystals were octahedrally shaped with the particle size around 600 nm.

Figure 5-10. XRD pattern of as-synthesized UiO-66 sample.

Figure 5-11. Nitrogen adsorption (filled circles)-desorption (open circles)

isotherms of as-synthesized UiO-66 sample.

The formation of composite-1 was achieved via a facile vacuum filtration

method. As shown in Figure 5-3, the vacuum condition was introduced to the lumen

of α-alumina hollow fiber, and the water solution carrying MOFs flowed at the shell

Chapter 5

136

side with the aid of stirring. Because of the established pressure difference, the

water solution would first access and fill the cavities of the micro-channels; and

then pure water permeated through the thin barrier layer entering the fiber lumen,

whereas the MOF crystals cannot escape through the barrier layer and securely

stayed within the conical micro-channels owing to the size-exclusion effect (Figure

5-2 and 5-7(f)). Both FTIR and TGA analyses towards the formed composite

suggested that there was only physical attachment between the incorporated MOF

crystals and α-alumina matrix (vide infra Section 5.3.3). Moreover, the critical

parameters including the particle size of MOFs, MOF concentration in the water

solution, magnetic stirrer speed for dispersing MOF crystals in the water solution,

as well as duration of the vacuum filtration process were comprehensively

investigated (listed in Table 5-2), giving rise to an optimized composite-1 (0.68 mg

MOF per gram composite) for the arsenic contaminated water remediation.

Table 5-2. Optimized parameters for vacuum filtration process

Optimized experimental parameters

Particle size of UiO-66 600 nm

Micro-channels length in α-alumina hollow fibers 500 µm

MOF concentration in the water solution 0.5 g/L

Magnetic stirrer speed for dispersing MOF crystals

in the water solution 160 rpm

Duration of the vacuum filtration process for each

composite 5 min

Chapter 5

137

5.3.2 Performance of composite

Since the arsenic concentration in most contaminated wastewater ranges from 0.1

to 1 ppm (Mohan and Pittman, 2007), the essential arsenic concentration of feed

streams was set as 1 ppm. Both the developed composite-1 and equivalent packed

columns were investigated in terms of their respective kinetic breakthrough

performance for water decontamination.

In the case of composite-1, the arsenic contaminated feed stream was

introduced to the composite from the shell to the lumen side, as shown in Figure 5-

4. In such a manner, the barrier layer at the lumen side could well prevent any active

MOF crystals from escaping the composite, as no UiO-66 was detected for the

liquid outflow (vide infra Section 5.3.3). When the wastewater stream transported

through the passages of micro-channels, it would be in contact with the UiO-66

adsorbents; owing to the adsorbents’ fast uptake kinetics, selective adsorption of

arsenic from water occurred efficiently within this micro-space. With the optimized

operating parameters (listed in Table 5-3), composite-1 was capable of providing

the clean effluent recovery for 60 minutes, as shown in Figure 5-12(a). This clean

recovery meets the drinkable standards made by both WHO and US-EPA (less than

10 ppb) (Mohan and Pittman, 2007), and can be used as potable water supply

without any additional post-treatment. In practical, the contaminated feed normally

contains less than 1 ppm of arsenic, and thus a longer breakthrough time can be

anticipated. Also, the adsorption uptake with regard to the active adsorbent is

calculated as ~23.4 mg/g up to breakthrough. These results specified that the

probability of feed stream leaking through the micro-channel walls was negligible,

as the mass transfer resistance of the walls is orders-of-magnitude larger than that

Chapter 5

138

of the micro-channel passages. Furthermore, to obtain an idea of the capability of

composite-1, we further increased the arsenic concentration of feed streams to 10

ppm and 20 ppm under the same operating conditions. A much shorter breakthrough

time (~ 15min) was noticed for the 10-ppm case, while no clean recovery can be

collected if the contaminated feed is as concentrated as 20 ppm.

Table 5-3. Optimized experimental parameters for arsenic contaminated water

remediation using composite-1

Optimized experimental parameters

Active Loading of UiO-66 in α-alumina hollow

fiber 0.68 mg g-1

Outer/inner diameter of α-alumina hollow fiber 1.8 mm/1.1 mm

Composite length 5 cm

Syringe pump flow rate 0.6 mL min-1

Syringe pump pressure introduced 101347 pascal (1 atm + 22 pascal)

Recovery permeate rate 1.74 L min-1 m-2

Feed concentration 1 mg L-1

Time duration before breakthrough 60 min

Chapter 5

139

Figure 5-12. Breakthrough studies: (a) using composite-1 for arsenic water

decontamination (1 ppm, 10 ppm and 20 ppm as the arsenate concentration in the

feed solution were investigated); (b) using equivalent packed columns for arsenic

water decontamination (1 ppm as the arsenate concentration in the feed solution

was used for comparison). With reference to the quantity of MOF loaded in

composite-1, the columns were packed with: equal (1X), twice (2X), five times

(5X) and eight times (8X) the amount of MOFs, respectively. The data in (b) are

reported as the average of duplicate experiments.

On the other hand, a comparison study under the identical experimental

conditions was carried out using packed column beds, as shown in Figure 5-5 and

experimental conditions listing in Table 5-4. With an equal amount of UiO-66

Chapter 5

140

adsorbents packed into the column (same with the amount loaded in composite-1),

the adsorption efficiency was found to be unsatisfactory as shown in Figure 5-12(b),

while the cleanest recovery contained 40 ppb of arsenic. Even if we doubled the

amount of UiO-66 in the column media, none of the clean recovery can be collected.

Further increasing the quantity of active adsorbents in the column, the column setup

started to provide clean recovery; and when 8 times the amount of UiO-66 adsorbent

was employed, it provided a similar performance with that of composite-1.

Table 5-4. Experimental parameters for arsenic contaminated water

remediation using packed column beds

Experimental parameters for packed columns

Equivalent amount of UiO-66 in the composite

15 mg (1X);

30 mg (2X);

75 mg (5X);

120 mg (8X)

Packed column diameter 3.175 mm

Packed column heights

0.6 cm (1X);

1.2 cm (2X);

3 cm (5X);

4.8 cm (8X)

Recovery outflow rate 0.6 mL min-1

Filter paper pore size 0.45 µm

Feed concentration 1 mg L-1

Chapter 5

141

The inferior performance of packed column beds is associated with the

inherent drawbacks like inefficient packing and non-ideal flow (Dąbrowski, 2001).

Owing to the fact that the packing of adsorbents inside a column is rather random,

contaminated streams tend to bypass the adsorbents and directly join the effluent.

This phenomenon becomes even more serious when limited amount of adsorbents

are used (Kundu, 2004). On the contrary, composite-1 offers an alternative concept

of introducing efficient adsorption within micro-channels. The micro-channels with

the conical shape not only ensure a better distribution and more effective control of

adsorbent materials, but also form a transport network such that the mass transfer

resistance is greatly reduced. Hence, in comparison with the packed column bed, a

more ideal flow can be achieved in composite-1, as well as a more efficient contact

between contaminants and active adsorbents. As a result, composite-1 provides

much more effective adsorptive separation process using a much lower amount of

active adsorbents, which would lead to considerable cost savings.

5.3.3 Additional discussion

The thermal analysis was carried out using a thermogravimetric analyzer (Netzsch

TG 209 F1 Libra). Characteristic patterns (Figure 5-13) of weight change were

obtained with respect to composite-1, alumina, UiO-66, respectively. It shall be

noted that composite-1 only exhibited one obvious weight drop (~ 1%, at 500 oC)

along with an increase in temperature (from room temperature to 1000 oC). This

weight drop is corresponding with the thermal degradation of UiO-66 crystals that

were incorporated within the composite.

Chapter 5

142

Figure 5-13. TGA analyses for weight changes with temperature on composite-1,

alumina and UiO-66.

To fully understand the interaction between UiO-66 and alumina, the

samples were analyzed by an FTIR spectroscope (Spectrum 100, PerkinElmer)

equipped with diamond ATR (attenuated total reflection) crystal. As shown in

Figure 5-14, all the characteristic peaks of composite-1 can be correlated with the

ones of alumina and UiO-66. In other words, the FTIR spectrum of composite-1 is

a simple superimposition of the spectra of alumina and UiO-66. This suggests there

is only physical attachment between alumina particles and UiO-66 crystals in the

composite. The main reason (mechanism) that UiO-66 crystals stay well within the

composite is attributed to the size-exclusion effect provided by the conical shape

micro-channels as well as the thin barrier layer at the lumen side.

Chapter 5

143

Figure 5-14. FTIR spectra of composite-1, alumina and UiO-66.

After the adsorptive separation tests, the outflow from composite-1 was

collected and sent for centrifugation. No appearance of UiO-66 particles was

observed after centrifugation. The outflow samples were then put for ICP analysis

to detect Zr signal, which should be due to the presence and/or decomposition of

UiO-66 particles if there is any. Both visible observation and element detection

together prove that the loss of UiO-66 crystals from the composite throughout the

adsorptive separation tests is negligible.

After all, composite-1 in this study resolves a critical industrial problem:

generally adsorbents to be used in industry must be formed into specific shapes or

pellets by combining with a quantity of binder material (Jeffs et al., 2013), while

the activities, functionalities and effectiveness of the adsorbent become reduced at

the end; incorporating the active adsorbent into the advanced α-alumina matrix

Chapter 5

144

provides a creative approach to use the adsorbent more effectively. It is capable of

working steadily under varying conditions. In practical water remediation

applications, the barrier layer of α-alumina hollow fiber could further serve as a

separation medium to reject suspended solids and micro-organisms (He et al.,

2014a). Moreover, it is feasible to assemble such functional composites as modules

in different scales (Lee et al., 2014; Li, 2007), ranging from a small portable water

purification unit for household use to a large hybrid adsorption-filtration system in

water decontamination plants.

5.4 Conclusions

To conclude, a MOF/α-alumina composite with novel geometry was developed and

effectively applied for water decontamination. The composite was formed by

depositing UiO-66 adsorbents into the unique micro-channels of α-alumina hollow

fiber through a facile vacuum filtration method. When it was applied for arsenic

contaminated water remediation, composite-1 produced potable water recovery. To

achieve a similar performance, the packed column bed required eight times the

amount of active UiO-66 adsorbents. Therefore, as a proof of concept, composite-

1 has exhibited a promising potential to be applied for industrial water

decontamination. Looking forward, based on the specific adsorptive separation

applications, various functional composites could be formed. A wide range of

adsorbents can be selected and loaded into the α-alumina hollow fiber, of which the

micro-channel sizes can be well controlled during fabrication.

Chapter 6

145

CHAPTER 6 AMORPHOUS METAL-ORGANIC

FRAMEWORK UIO-66-NO2 FOR OXYANION

POLLUTANTS REMOVAL: TOWARDS

PERFORMANCE IMPROVEMENT AND EFFECTIVE

REUSABILITY

Chapter 6 is a study revealing proper defect engineering on the hydro-stable Zr-

MOF could lead to functional structures, i.e. amorphous MOFs, with enhanced

adsorptive performance and excellent regenerative capability. This chapter aims at

resolving the critical reusability problem of MOF adsorbents in anions uptake.

ABSTRACT

Water pollution is one of the most significant environmental issues nowadays. The

remediation of oxyanion pollutions is of critical concern due to their recalcitrance

and persistence in the environment as well as acute toxicities even at trace

concentration levels. In this study, a water stable metal-organic framework (MOF),

UiO-66-NO2, was prepared and deliberately amorphized in order for it to assume a

more open and dynamic structure. The resulting amorphous UiO-66-NO2 (am-UiO-

66-NO2) demonstrated a great efficacy for the removal of representative oxyanion

pollutants in wastewater, i.e. arsenic, chromium and selenium containing species. It

was found that the am-UiO-66-NO2 adsorbent exhibited enhanced adsorption

capacities as well as an excellent reusability, which was seldom found in previously

Chapter 6

146

reported MOF adsorbents. Notably, it was found that it could be effectively

regenerated and reused whilst retaining more than 80% of its capacity after 8 cycles

of applications. The amorphized MOF as well as its adsorption behaviors were

thoroughly characterized and analyzed using X-ray photoelectron spectroscopy

(XPS). This confirmed the uptake of oxyanions within the adsorbent material and

the corresponding uptake mechanisms.

6.1 Introduction

Ionic pollutants in water streams have been identified as a serious global threat due

to their acute toxicity, long-term accumulation, persistence, and high mobility (Goh

et al., 2008). Very often, the inorganic pollutants consisting of metal and metalloid

species would be oxidized to form oxyanion compounds in wastewater owing to the

complicated water conditions. Oxyanion pollutants such as the arsenic, chromium

and selenium containing species are highly soluble in water, making their

accumulation in susceptible organisms and bio-systems highly likely. These

oxyanion pollutants are carcinogenic at concentrations as low as the ppm or even

ppb level, as shown in Table 6-1 (Xu et al., 2016). Therefore It is highly imperative

that these pollutants must be prevented from entering our water supply.

Table 6-1. List of toxic contaminants (forming oxyanions) and their health effects.

Contaminant Guideline values by

WHO*

Anthropogenic Sources of

Contamination

Potential Health

effects

Arsenic 0.01 mg/L Sulfide mineral deposits and

sedimentary deposits

Peripheral

neuropathy, skin

Chapter 6

147

deriving from volcanic

rocks

cancer, bladder and

lung cancers and

peripheral vascular

disease, producing

liver tumors

Chromium 0.1 mg/L Discharge from steel and

pulp mills and leather

industries; erosion of natural

deposits

Human carcinogen,

producing lung

tumors, allergic

dermatitis

Selenium 0.04 mg/L Discharge from petroleum,

metal refineries and mines,

erosion of natural deposits

Circulatory problems,

hair or fingernail loss,

numbness in fingers

or toes

* WHO: World Health Organization

As discussed in previous chapters, adsorption has been considered as one of

the most effective and simplest approaches through the utilization of a permanently

porous adsorbent material for oxyanions removal (Howarth et al., 2015c). Common

adsorbents that had been extensively studied include activated carbons, iron oxides,

aluminum oxide and zeolites. Recently, an emerging porous material – metal-

organic framework (MOF) – has attracted substantial attention in the scientific

community (Zhou et al., 2012). This class of materials has been widely assessed for

use in a variety of adsorption applications. With the recent advent of hydro-stable

MOFs (e.g. Zr-/Hf-based MOFs and azolate-based MOFs), it was even proposed as

an alternative adsorbent material in wastewater remediation.

Chapter 6

148

Thus far, research on the use of functional MOFs in oxyanion pollutants

removal from wastewater is still in its infancy (Howarth et al., 2015c). Although

some preliminary studies have been reported with satisfactory results, there is still

significant room for improvement in performance. More importantly, the MOF

adsorbents used in these studies did not exhibit sufficient regeneration capabilities.

Benefits of utilizing functional MOFs for only one-time use can hardly break even

the intrinsic cost. The synthesis of MOFs is relatively costly in comparison with

conventional carbon and bio-sorbents. Thus, it is imperative for MOFs to be used

in multicycle applications, meaning it must retain its adsorption capacity over time

in order to break even the initial intrinsic cost. This limitation would dictate the

economic viability of utilizing water stable MOFs in water treatment industries.

The reusability of MOFs is intrinsically poor due to its confined and rigid

structural framework. More flexible and dynamic structures are needed to facilitate

the uptake as well as the release of specific analyte compounds. Both Fang et al.

and Bennett et al. (2016) have commented that proper defect engineering towards

the functional MOFs may open up novel opportunities in adsorption and catalysis.

Through deliberate introduction of linker vacancies, several structural changes are

consequently triggered: (1) meso-pores would be generated leading to reduced

network rigidity, (2) more open mass-transport pathways would be formed, (3)

more active sites may be realized for targeted guest-host interactions.

Building upon this idea, we hypothesized that defected MOFs may exhibit

an enhanced performance in water pollutants uptake and excellent regenerability.

The large-scale defected MOFs are classified as amorphous MOFs, i.e. highly

disordered framework structures whilst retaining the basic building blocks and

Chapter 6

149

connectivity but lacking long-range periodic order (Orellana-Tavra et al., 2015).

Herein, we used a Zr-based MOF, UiO-66-NO2, as the parent material for oxyanion

pollutants removal. The basic structure of this MOF, [Zr6O4(OH)4(BDC-NO2)6]

(BDC = 1,4-benzenedicarboxylate), is based on the zirconium oxo-clusters and 2-

nitro-BDC ligands (Kandiah et al., 2010). It possesses a high hydro-thermal

stability and fairly low toxicity. In this study, the Zr-MOF UiO-66-NO2 was

prepared via a solvo-thermal recipe and subsequently amorphized. The resulting

amorphous UiO-66-NO2 (am-UiO-66-NO2) material was properly characterized

and carefully analyzed. The am-UiO-66-NO2 adsorption capabilities of oxyanion

(i.e. arsenate, chromate and selenite) uptake together with its reusability were

investigated in batch experiments. Moreover, an X-ray photoelectron spectroscopy

(XPS) study was then carried out for an enhanced understanding of the material as

well as the adsorption processes.


6.2.1 Materials



99.5%), 2-nitroterephthalic acid (NO2-BDC, 99%), 1,4-benzenedicarboxylic acid

(BDC, 98%), sodium arsenate dibasic heptahydrate (Na2HAsO4∙7H2O, 98%),

sodium chromate (Na2CrO4, 98%), and sodium selenate (Na2SeO4, 98%) were

purchased from Sigma-Aldrich. In particular, ZrCl4 was stored in a desiccator to

protect it from the influence of humidity. Moreover, ethanol (EtOH, 99.9%),

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150

dimethylformamide (DMF, 99.9%), nitric acid (HNO3, 68%), and sodium

hydroxide (NaOH, 99%) were purchased from VWR. The stock solutions (all in

100 ppm) with respect to arsenate, chromate and selenate were obtained by

dissolving Na2HAsO4∙7H2O, Na2CrO4 and Na2SeO4, respectively in 1 L deionized

(DI) water (Analytic lab, ACEX, Imperial College London). The solutions of

required concentrations used in this study were prepared by diluting the respective

stock solution with DI water. pH adjustment was conducted using a series of nitric

acid or sodium hydroxide with concentrations ranging from 1 M to 0.001 M. The

pH of solutions was measured by an ORION 525A pH meter.

6.2.2 UiO-66-NO2 synthesis

Crystalline UiO-66-NO2 was prepared through a typical solvothermal synthesis

(Kandiah et al., 2010). ZrCl4 (1.50 g), NO2-BDC (1.56 g) and trivial amount of DI

water (0.01 g) were mixed with 180 g of DMF in a 200 mL glass bottle. The solution

was then sonicated for 15 minutes at room temperature to ensure a complete

dissolution of all the chemicals. After that, the solution was transferred to Teflon-

lined stainless-steel autoclaves and heated at 100 oC for 24 h in a convective oven

(UF30, Memmert). Once the solvothermal treatment was done, the autoclaves were

cooled down to room temperature. The final solution was centrifuged with 15000

rpm (Thermo Scientific Legend X1R) for 15 minutes to collect the as-synthesized

powders, which were then washed three to four times by 100 mL ethanol solution

each cycle to remove unreacted precursors. This activation process was completed

by repeated solvent-exchange with ethanol for a week. The UiO-66-NO2 powders

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151

were then obtained and dried under vacuum condition (Fistreem Vacuum Oven) at

60 oC for 24 h.

6.2.3 UiO-66-NO2 amorphization

The amorphization of UiO-66-NO2 was performed through introducing more ligand

defects of incorporating M-OH sites. The as-synthesized UiO-66-NO2 was

immersed in an aqueous alkali sodium hydroxide solution (NaOH, pH 12) for 2 h

under room temperature. The amorphous UiO-66-NO2 was then collected through

centrifugation (15000 rpm, 15 min), and washed with DI water three to four times.

Finally, the obtained product was dried under vacuum condition (60 oC, 24 h) for

further use.

6.2.4 Characterizations

The surface morphology of both UiO-66-NO2 and am-UiO-66-NO2 was studied by

using a field emission scanning electron microscope (FESEM, LEO Gemini 1525)

coupled with Energy-dispersive X-ray (EDX). The post-adsorption adsorbents were

collected using centrifugation and washed with DI water several times before drying

under vacuum conditions. The samples were immobilized on a carbon tape and then

coated with 10 nm gold for improved conductivity before analysis.

Both UiO-66-NO2 and am-UiO-66-NO2 adsorbents were analyzed by the

PXRD, FTIR, BET and XPS studies. The detailed methodology information can be

referred to Section 3.2 in Chapter 3 and Section 4.2.2 in Chapter 4. Prior to the

analyses, samples were dried under vacuum condition overnight.

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152

6.2.5 Adsorption batch experiments

The adsorption capabilities of UiO-66-NO2 and am-UiO-66-NO2 were evaluated

with respect to the arsenate, chromate and selenate solutions, respectively. The tests

were investigated at room temperature (25 ± 1 oC). Solutions (each 50 mL) with

different concentration (1-50 mg/L) were prepared in glass vials by diluting the

respective stock solutions with the DI water. The adsorbent dosage was 0.5 g/L.

The pH values of solutions were adjusted to 2 and maintained by 0.1 M nitric acid

or sodium hydroxide solutions during the process. The solutions were shaken on a

rotary shaker at 220 rpm for 96 h, which was considered as more than adequate for

establishing equilibrium according to the preliminary tests and the relevant

literature. At the end of tests, the solutions were filtered through 0.22 µm filters,

and the filtrates were analyzed for residual ionic concentration by an inductively

coupled plasma emission spectrometer (ICP-OES, Optima 2000 DV, PerkinElmer).

The repeated use of am-UiO-66-NO2 was investigated with eight cycles of

adsorption and desorption tests all under room conditions. In each adsorption cycle,

0.5 g/L adsorbent was added in 50 mL solutions with a concentration of 50 mg/L at

pH 2 for 96 h. After the adsorption cycle, the spent adsorbent was collected using

centrifugation and washed with DI water, and then immersed in an alkali NaOH

solution (pH 10) for 2 h on a rotary shaker at 220 rpm for complete desorption.

Afterwards, the adsorbent was collected using centrifugation and washed by DI

water again before drying under vacuum condition for the next adsorption cycle.

The adsorption capacity of each cycle was measured to evaluate the regeneration

performance.

Chapter 6

153


6.3.1 Characterizations of materials

The morphology of as-synthesized UiO-66-NO2 was examined by FESEM. As

shown in Figure 6-1(a), the UiO-66-NO2 particles are observed to be around 500

nm in diameter. The crystalline materials were well intergrown and clear, sharp

edges can be observed. Its bulk crystallinity was evaluated by PXRD as shown in

Figure 6-1(b). It can be found that all 2θ peaks were consistent with the previously

reported literature data, which proves the topology and framework structure of UiO-

66-NO2. The characterization data indicates that the UiO-66 framework has

therefore been successfully prepared (Cavka et al., 2008; Kandiah et al., 2010;

Valenzano et al., 2011). Further to that, the presence of specific chemical groups

was further evidenced by characterizing the as-synthesized UiO-66-NO2 under

FTIR study. The FTIR spectra are depicted in Figure 6-1(c). As expected, the

characteristic FTIR spectrum matches very well with the data in literature (Kandiah

et al., 2010; Valenzano et al., 2011). Representative vibrations such as peaks at 730

cm-1 and 680 cm-1 corresponding to Zr-(μ3)O groups can be observed in the FTIR

spectrum. In particular, the presence of peaks at 1555 cm-1 and at 1355 cm-1

(partially covered by a strong band attributed to a carboxylate mode and thus

appears as a shoulder) are ascribed to the absorption owing to the asymmetric

(ν(NO)asym) and symmetric (ν(NO)sym) stretching modes (Kandiah et al., 2010).

They therefore confirm the presence of nitro groups at the linkers. The

characterization data indicate that UiO-66-NO2 has been successfully prepared.

Chapter 6

154

Figure 6-1. Characteristics of UiO-66-NO2 and am-UiO-66-NO2: (a) and (d)

FESEM image of UiO-66-NO2 and am-UiO-66-NO2; (b) PXRD patterns of UiO-

66-NO2 and am-UiO-66-NO2; (c) FTIR spectra of UiO-66-NO2 and am-UiO-66-

NO2.

By introducing more defects into UiO-66-NO2, an amorphous UiO-66-NO2

with highly disordered framework structure can be obtained, whilst retaining the

basic metal-ligand connectivity. Its morphology can be found in Figure 6-1(d). In

Chapter 6

155

comparison with its crystalline counterpart, am-UiO-66-NO2 appear to be more

spherical and blunter edges. Because of the disordered and aperiodic structure of

am-UiO-66-NO2, its PXRD pattern lacks definite peaks whilst being dominated by

broad humps, as shown in Figure 6-1(b) (Orellana-Tavra et al., 2015). Despite the

irregularities, its basic building blocks as well as chemical compositions are still

retained, suggested by the FTIR spectrum (Figure 6-1(c)). Am-UiO-66-NO2

exhibited a highly similar FTIR pattern when compared with the crystal UiO-66-

NO2; and most of the characteristic bands are still present.

Besides the abovementioned characteristics, the changes in the porous

structure between UiO-66-NO2 and am-UiO-66-NO2 can be better understood

through the BET analyses. The N2 adsorption–desorption isotherms of both

materials were plotted in Figure 6-2(a). Based on the isotherms, the as-synthesized

UiO-66-NO2 was found to possess a BET surface area of 660 m2/g as well as a total

pore volume of 0.35 cm3/g, of which a 0.22 cm3/g micro-pore volume and 0.10

cm3/g larger-pore volume can be detected. Unlike the UiO-66-NO2 sample, am-

UiO-66-NO2 exhibited a distinctive nitrogen adsorption behavior. The BET surface

area of am-UiO-66-NO2 decreased to 530 m2/g, meanwhile a higher total pore

volume (0.65 cm3/g) was detected. This higher pore volume consisted of no micro-

pore volume but was due to the considerable larger-pore volume. In addition,

another difference was observed in the pore width distribution (Figure 6-2(b)): most

of the pores in UiO-66-NO2 framework spans around 6 angstroms; on the contrary,

these pores disappear to a great extent in am-UiO-66-NO2 whilst much larger pores

appear spanning around 9.5 angstroms. Therefore, it seems that the amorphization

process dismantled the confined micro-pores, and opened the rigid and highly

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156

connected framework to a more dynamic structure. This could be due to the

hydroxyl groups replacing the carboxylate linkers and creating the vacancies in the

interior structure (Cliffe et al., 2014; Øien et al., 2014). The higher degree of

disconnection between the metal-oxide units would lead to the larger pores, e.g. the

void as shown in Figure 6-2.

Figure 6-2. (a) Nitrogen adsorption-desorption behaviors of UiO-66-NO2 and am-

UiO-66-NO2. (b) Pore width distribution of UiO-66-NO2 and am-UiO-66-NO2.

6.3.2 Adsorption performance for oxyanions

Adsorption capacities

The removal of three representative oxyanions (arsenate AsO43-, chromate CrO4

2-

and selenate SeO32-) that are particularly hazardous and carcinogenic were

investigated in batch experiments. Based on the preliminary tests, the adsorption

studies were carried out at pH 2, which was considered as the optimal aqueous

condition for the interaction between zirconium-based adsorbents and oxyanions.

The adsorption isotherms with respect to both UiO-66-NO2 and am-UiO-66-NO2

were summarized in Figure 6-3. It was found that the UiO-66-NO2 adsorbent

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157

demonstrated fair adsorption capacities towards these three oxyanion pollutants: 65

mg-As/g, 20 mg-Cr/g, 20 mg-Se/g, respectively. Nevertheless, these capacities

were much enhanced in the cases that the am-UiO-66-NO2 adsorbent was applied.

As shown in Figure 6-3, the adsorption capacities of am-UiO-66-NO2 were

respectively 85 mg-As/g, 45 mg-Cr/g and 40 mg-Se/g. The increment could be due

to the increasing number of terminal hydroxyl groups (M-OH) in am-UiO-66-NO2,

as several researchers including Audu et al. and Howarth et al. have confirmed the

Zr-OH groups are responsible for the facile binding of oxyanions to the Zr6 node in

Zr-MOFs. In addition to the single component adsorption test, a multiple

component uptake test with the co-existence of three oxyanion species had been

conducted. The experiment results suggested that the adsorption affinity of am-

UiO-66-NO2 follows the order: As > Se ≈ Cr, whilst the other anions such as

chloride, nitrate and sulfate did not inhibit the adsorption performance. Besides,

there was no substantial signal detected with regards to Zr(IV) ions in all the post-

adsorption water samples. This finding suggests that the am-UiO-66-NO2 adsorbent

is intact during all the adsorption processes.

Benchmarking the adsorption capacities of am-UiO-66-NO2 provided by the

Langmuir modeling with the other representative adsorbents in oxyanion uptake,

we can find that the am-UiO-66-NO2 adsorbent outperforms many other adsorbents

(Kumar et al., 2014). Its adsorption capacities for arsenate, chromate and selenate

are higher than that of the commercial adsorbents, and comparable to those

delicately synthetic adsorbents in laboratory settings (Howarth et al., 2015b).

Chapter 6

158

Figure 6-3. Adsorption isotherms as well as reusability in multiple cycles with

respect to As (a & b), Cr (c & d) and Se (e & f).

Furthermore, the post-adsorption am-UiO-66-NO2 were examined by EDX

analysis. The material samples after adsorption tests were collected and then

washed by DI water several times to make sure a clean outer surface of spent

adsorbents without any oxyanion species deposition. After that, the spent samples

underwent an elemental analysis, as shown in Figure 6-4. The detected element

signals verified that the samples were the Zr-based amorphous MOF, and the

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159

samples were indeed loaded with specific oxyanions. It was found that the presence

of specific oxyanions within the adsorbents matched very well with the zirconium

signals. This suggested the oxyanion adsorptions of am-UiO-66-NO2 are related to

the Zr-containing metal units, which is in line with the finding previously reported.

Moreover, if we studied the FTIR spectra of am-UiO-66-NO2 after the binding of

oxyanions, we can see respective complexes formed within the adsorbent structures.

For instance, in comparison to the FTIR spectra (Figure 6-4(d)) between the original

am-UiO-66-NO2 sample and the am-UiO-66-NO2 sample after adsorbing arsenate

species, a significant new band centered at 815 cm-1 appeared for the post-

adsorption sample. This 815 cm-1 peak corresponding to the Zr-O-As complex

proves the binding of arsenic within the am-UiO-66-NO2 adsorbents (Wang et al.,

2015). The finding is in line with the previously reported data with respect to the

interaction between zirconium-based MOFs and oxyanion species (see Chapter 3).

However, those zirconium-based MOFs exhibited very limited reusability across

multi-cycle use in adsorption/desorption of oxyanion species. Therefore, although

the enhanced capability of am-UiO-66-NO2 in oxyanion uptake has been confirmed,

further investigations are still needed.

Chapter 6

160

Figure 6-4. Elemental mapping analysis with respect to post-adsorption am-UiO-

66-NO2: (a) arsenate uptake, (b) chromate uptake, and (c) selenate uptake. (d)

Post-arsenic-adsorption analysis using FTIR: red line – spent adsorbent sample,

black line – pristine material sample.

Chapter 6

161

Adsorbent reusability

Reusability of material is considered important in water treatment. As mentioned,

one critical limitation of applying functional MOF adsorbents for heavy metal

decontamination is the relatively costly synthesis. Without sufficient reusability, the

MOF adsorbents are to be discarded after one-time application. This results in high

costs and difficulty in its applications to an industrial scale, since it can hardly break

even its intrinsic costs. It has been hypothesized that amorphous MOFs may find

applications in areas that involve the collapse of porous structures around guest

species, e.g. reversible gas storage and drug release (Bennett and Cheetham, 2014).

Therefore, we conducted several multi-cycle performance tests to evaluate the

regenerability and reusability of am-UiO-66-NO2 for oxyanion uptakes.

Specifically, more than 8 cycles of adsorption-desorption/regeneration

experiments were repeated in the respective cases of arsenate, chromate and

selenate. The resulting adsorption capacities of each cycle for the regenerated am-

UiO-66-NO2 adsorbent were recorded in Figure 6-3. A consistently effective uptake

for the three oxyanions was found throughout the 8 cycles. It is worthy to note that

the adsorption capacity after 8 cycles can retain almost 80%, and particularly, more

than 90% of initial adsorption capacity was retained in arsenate removal. The

adsorption capacities of am-UiO-66-NO2 at the end of the eighth cycle are still

higher than the initial adsorption capacities of pristine UiO-66-NO2. Moreover,

after each uptake cycle and during the following regeneration step, we constantly

observed a nearly full desorption of the guest oxyanions from am-UiO-66-NO2. The

finding suggested an effective desorption of oxyanions, which was not observed for

the perfectly connected MOF adsorbents like UiO-66 and UiO-66-NO2.

Chapter 6

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The outstanding reusability of am-UiO-66-NO2 could be due to the unique

dynamic structure. Owing to the amorphization process, most of the confined

micro-porous space was dismantled, leaving behind more channels and larger voids

within the amorphous MOF structure. Unlike the rigid and highly connected MOFs,

this unique structure is more open and flexible, which would enable guest

compounds to exhibit easier diffusion (in and out) and interactions with active sites

(Bennett et al., 2016). This would explain why the oxyanions in this study could be

efficiently captured as well as effectively released via a facile treatment. During the

regeneration process, we treated the spent adsorbent with alkali aqueous solutions

(pH 10). Consequently, the bounded oxyanion complexes were weakened by the

water environment and the exceeding free hydroxyl groups outdid the oxyanion

complexes to form the terminal M-OH sites (Audu et al., 2016). In the meantime,

the released oxyanions easily diffused out from the am-UiO-66-NO2’s interior

structure and dissolved back into the aqueous solutions. These active and dynamic

interactions between the Zr6 node and hydroxyl groups were rooted in the

amorphization process. The reinstallation of terminal M-OH sites renders the

materials ready for the next round of oxyanion uptake under the acidic, oxyanion

concentrated conditions.

XPS analysis

In order to have a further detailed understanding towards the am-UiO-66-NO2

material as well as its adsorption processes, we carried out an XPS study, which is

a useful technique to analyze the various chemical states of particular elements.

Firstly, the UiO-66-NO2 samples before and after amorphization were examined

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163

with respect to their characteristic Zr 3d region. As shown in Figure 6-5, the Zr 3d

spin-orbit of the materials display an asymmetric double peak shape with 3d

splitting of 2.43 eV owing to 3d3/2 and 3d5/2, respectively (Jerome et al., 1986).

These Zr 3d spectra can be decomposed into three component peaks with the

binding energies of 176.22, 176.82 and 177.44 eV. Referencing to the literature

database, these peaks can be ascribed to the zirconium in Zr-carboxylate (176.22

eV), Zr-hydroxyl (176.82 eV), Zr-oxide (177.44 eV), respectively (Jerome et al.,

1979; Thermo Scientific XPS database). With a careful inspection towards the

relative contents of individual sub-peaks in both sets (Table 6-2), it should be noted

that the relative content of Zr-acetate group in crystalline UiO-66-NO2 decreased

considerably after the amorphization, a.k.a. the introduction of ligand defects,

meanwhile, the relative content of Zr-OH group in am-UiO-66-NO2 increased

comparing to its crystalline counterpart. This evidence suggests the occurrence of

an amorphization process, of which hydroxyl groups may replace certain

carboxylate linkers, create the vacancies in the interior structure of UiO-66-NO2.

Figure 6-5. High resolution scan XPS spectra of Zr 3d orbitals with respect to: (a)

UiO-66-NO2 sample, and (b) am-UiO-66-NO2 sample.

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Table 6-2. Binding energy and relative contents of Zr 3d orbitals with respect to

UiO-66-NO2 and am-UiO-66-NO2 sample.

Element

orbital

Sample

Proposed

component

Binding

energy (eV)

Relative

content (%)

Zr 3d

UiO-66-

NO2

Zr-O-C 176.22 74.7

Zr-OH 176.82 19.9

Zr-O-Zr 177.44 5.47

am-UiO-66-

NO2

Zr-O-C 176.22 53.7

Zr-OH 176.82 35.4

Zr-O-Zr 177.44 10.9

Secondly, the am-UiO-66-NO2 samples after the uptake of arsenic,

chromium and selenium were investigated under XPS respectively, and the scan

results are shown in Figure 6-6. Specifically, with respect to each post-uptake

samples, the As 3d peak, Cr 2p peak, and Se 3d peaks can be identified respectively

in their characteristic binding energy ranges (Desimoni et al., 1988; Soma et al.,

1994; Wagner et al., 1979a). Therefore, once again, the capture of these targeting

compounds within am-UiO-66-NO2 could be confirmed. In addition to this, the Zr

spectra in regards to the three post-uptake am-UiO-66-NO2 samples were collected

and compared with that of the pristine sample. Unlike the original am-UiO-66-NO2

of which the Zr spectrum can be divided into three sub-peaks, a new and additional

sub-peak can be identified for the post-uptake samples. Taking the arsenic uptake

case for illustration, the Zr 3d double peaks were decomposed into four components

(Figure 6-6): three of which are similar with the ones identified in the pristine

sample and respectively correspond to Zr-carboxylate (176.22 eV), Zr-hydroxyl

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165

(176.82 eV) and Zr-oxide (177.44 eV), whilst a distinctive one at the binding energy

of 176.44 eV can be ascribed to Zr in the form of Zr-O-As (Thermo Scientific XPS

database, Jerome et al., 1979). Likewise, a peak at 176.91 eV is associated with Zr-

O-Cr and another one at 177.9 eV is due to Zr-O-Se. It was suggested that the uptake

of oxyanions by am-UiO-66-NO2 is through the Zr-hydroxyl groups on the

zirconium-based cluster units to form respective Zr-O-M (M: oxyanions)

complexes. This agrees with what Howarth et al. (2015a) and the first study in

Chapter 3 had observed in the cases of oxyanion uptake using zirconium-based

MOFs, of which Zr-hydroxyl groups act as the active adsorption sites.

Figure 6-6. High resolution scan XPS spectra on post-adsorption am-UiO-66-NO2

adsorbent in the case of: (a & b) arsenate uptake, (c & d) chromate uptake, and (e

& f) selenate uptake.

Chapter 6

166

Finally, it was found that the characteristic nitrogen 1s peak corresponding

to the -NO2 group centered around 404.50 eV can be found in all the samples

(Figure 6-7) (Hwang et al., 1989). This concludes that the structural integrity of the

am-UiO-66-NO2 adsorbent was unimpaired, since the basic connectivity provided

by the BDC-NO2 groups was still retained in the amorphous material, even after the

uptake of oxyanions.

Figure 6-7. High resolution scan XPS spectra of nitrogen 1s orbital with respect to

am-UiO-66-NO2 material, and post-adsorption adsorbent in the case of arsenate

uptake, chromate uptake and selenate uptake.

6.4 Conclusions

The water stable Zr-MOF, UiO-66-NO2, was prepared and then amorphized to

obtain a material with a more open and dynamic structure. The resulting am-UiO-

66-NO2 was thoroughly examined under FESEM, FTIR, XRD and BET analyses to

Chapter 6

167

understand its morphology, chemical composition, crystallinity, and interior porous

structure, respectively. Further to that, its capability in oxyanion pollutants (i.e.

arsenate, chromate and selenate) removal was evaluated by static batch experiments.

The am-UiO-66-NO2 adsorbent was found to demonstrate highly enhanced

adsorption capacities. Moreover, the spent am-UiO-66-NO2 adsorbent can be

effectively regenerated and reused across multi-cycles. It was found that more than

80% of its adsorption capacities were retained after 8 cycles of applications. Finally,

the material and its adsorption behaviors for oxyanions were further analyzed by

the XPS study, which confirmed the material characteristics of am-UiO-66-NO2, its

uptake of oxyanions, together with the corresponding complexation mechanisms.

Chapter 7

168

CHAPTER 7 ZIRCONIUM-BASED

NANOCLUSTERS AS MOLECULAR ROBOTS FOR

ANIONS UPTAKE

Chapter 7 looks further into the applicability of metal-organic materials. This

chapter develops the metal-organic nanoclusters as smart molecular robots to

capture harmful anionic species from water media.

ABSTRACT

Water contamination owing to heavy metal ions is a persisting and ubiquitous

global threat. The current remediation technologies are low in efficiency, expensive

in materials and often associated with complicated processes. Therefore, there is a

significant need for novel approaches and materials that can enhance

decontamination effectiveness and, if possible, achieve molecular-level accuracy.

Here, we report a characteristic metal-organic cluster working as molecular robots

for contaminated water remediation. This zirconium-based cluster exhibits a

stimuli-responsive behavior to facilitate the water treatment process: it can dissolve

in acidic aqueous solutions for molecular-level decontamination, and quickly

aggregate for post-remedy collection at a neutral pH. They can precisely capture the

representative anionic pollutants, whilst featuring great capacities, super-fast

kinetics, as well as multi-cycle applications. Notably, with this approach, the

removal of pollutants can be completed within seconds, which is two to four orders

of magnitude faster than the removal rates of typical sorbents. In addition, we also

Chapter 7

169

confirm the responsible active sites by experimental evidence together with X-ray

Absorption Spectroscopy (XAS) studies. This work could lead to the development

of molecular robotic concepts for water decontamination and consequently a much-

improved industrial process.

7.1 Introduction

As discussed in previous chapters, the availability and access of clean water in many

regions still remain serious concerns (Shannon et al., 2008), owing to the increasing

level of environmental pollutions. Amongst typical pollutants, ionic contaminants

are known to be recalcitrant, non-biodegradable, and extremely toxic even at low

concentrations (Fu and Wang, 2011). Therefore, it has been classified as a leading

global risk towards both natural environment and human health by WHO (WHO,

2011). Thus far, cost effective sorbents or ion-exchange resins based upon solid

materials like activated carbon or metal oxides are most preferred. However, these

raw materials are often low in active site loadings and slow in sorption kinetics. In

order to achieve a greater sorptive capacity, specific functionalization or

modification must be carried out for the preparation of heterogeneous nano-

particles (Brandl et al., 2015) This would result in intensive energy consumptions

and therefore costly synthesis procedures. Besides, there is another key issue that

limits the performance of these conventional porous materials, i.e. the difficult

access of targeting compounds into the interior spaces where the vast majority of

potential active sites are located (Alsbaiee et al., 2016). This can be quite

Chapter 7

170

challenging, and consequently the majority of the sorptive capacity is restricted to

the sites present on the sorbent materials’ exterior.

Recently, scientists have been working on hierarchically structured

functional materials or well-defined crystalline porous materials, such as zeolite or

metal-organic frameworks, to install a network of diffusing channels combined with

a regular arrangement of active sites. Their applicability in contaminated water

remediation has been extensively explored (Mondloch et al., 2015). Despite

demonstrating brilliant performances in preliminary studies, they seldom exhibit

sufficiently fast kinetics for contaminant capture and adequate reusability across

multiple cycles, due to their confined and restricted scaffold structures. Following

these ideas but adopting a novel strategy, we turn our attention towards metal-

organic clusters. Note that, unlike the topologically connected porous frameworks,

a metal-organic cluster, itself, is a discrete molecular unit. Clusters exhibit a range

of fascinating properties such as the abundance of exposed active sites and readily

reversible reactivity owing to the open structures, which are not normally observed

in the corresponding bulk materials (Tyo and Vajda, 2015). In this study, we

demonstrate that metal-organic clusters are capable of working as smart molecular

robots for highly efficient water decontamination.

7.2 Methods and materials

Unless otherwise stated, all the chemicals were of analytical grade, and they were

used as received without further purification. The reagents including zirconium(IV)

propoxide solution (70 wt.% in 1-propanol), methacrylic acid (99%), sodium

Chapter 7

171

arsenate dibasic heptahydrate (98%), sodium chromate (98%), sodium fluoride

(97%), sodium phosphate dibasic (98%) were purchased from Sigma-Aldrich.

Furthermore, nitric acid (68%), sodium hydroxide (98%), ethanol (96%), acetone

(99%), and the respective elemental ion standard solutions (99.9%) were purchased

from VWR.

Synthesis of Zr-clusters.

Zr-clusters (oxozirconium methacrylate clusters) were prepared through the

reaction between 1 mL of 70 wt.% zirconium(IV) propoxide solution in 1-propanol

and 1 mL of methacrylic acid in a Schlenk tube under argon atmosphere. The

clusters crystallized quantitatively from the solution and were then collected after 1

day (Schubert, 1997).

Experimental details

The water decontamination capability of Zr-clusters was evaluated by the sorption

of typical anionic pollutants in water (arsenate, chromate, fluoride and phosphate).

The sorption tests were investigated by batch experiments on a magnetic stirrer (220

rpm) at room temperature (25 ± 1 oC). pH control was through a series of highly

purified nitric acid and sodium hydroxide solutions with different concentrations;

and pH measurements were conducted by an ORION 525A pH meter. The spent

Zr-clusters were collected using filter papers (cellulose acetate membrane,

membrane diameter 28 mm, pore size 0.2 μm, from Sigma). The ionic

concentrations were measured by an inductively coupled plasma emission

spectrometer (ICP-OES, Optima 2000 DV, PerkinElmer). Ultraviolet

Chapter 7

172

measurements with respect to the residual phosphate concentrations in the case of

phosphate uptake were conducted using a UV-VIS scanning spectrophotometer

(UV-1800 Shimadzu).

Stock solutions preparation

The stock solutions (all in 100 ppm) with respect to the four anionic pollutants were

prepared by dissolving Na2HAsO4∙7H2O, Na2CrO4, NaF, Na2HPO4, respectively in

1 L deionized (DI) water (Analytic lab, ACEX, Imperial College London). The

required solutions of required concentrations used in the following tests were

prepared by diluting the respective stock solutions with DI water. In addition,

different concentrations (1 M, 0.1 M, 0.01 M and 0.01M) of nitric acid solutions

and sodium hydroxide solutions were prepared beforehand for the following

adjustments of solution pHs.

Sorption tests

In the isotherm tests, 0.01 g Zr-clusters were dispersed in 10 mL DI water at pH

2~2.5, and then added to a series of 40 mL respective solutions with different initial

concentrations from 1 to 100 ppm. After 48 hours of contact time, which was

believed to be sufficient for the processes to reach equilibrium, the solutions were

adjusted to a neutral pH (~6.5) and then filtered using a 0.22 µm filter and the

residual concentration of the filtrate was measured by ICP-OES. Similar test

procedures were employed in the sorption rate tests, except that the solution samples

were collected at different time. Besides measuring the ionic concentration of

Chapter 7

173

collected samples using ICP-OES, a UV-Vis measurement was conducted with

respect to the sample aliquots collected from the phosphate uptake case.

After each sorption tests, the spent and aggregated Zr-clusters forming large

flocculants were separated from the solutions and then washed two to three times

using DI water. The collected Zr-clusters were regenerated by quick washing with

weak alkaline aqueous solution and then another two or three times of DI water

washing. After drying under vacuum condition, the regenerated Zr-clusters were

put into new cycles of sorption tests, which were repeated with similar operational

procedures.

Material imaging and characterizations.

The FESEM images as well as EDX analyses were obtained by using a Zeiss SEM

(LEO Gemini 1525) coupled with EDX. The HRTEM and AFM imaging were

carried out using a high resolution TEM (JEOL JEM-2000FX) and a Bruker AFM

(Innova), respectively. For the AFM measurement, the sample was scanned under

ScanAsyst model using a E scanner, with a ScanAsyst Fluid+ (Olympus) probe.

The AFM images were only flattened by the AFM analysis program without any

other treatment.

The thermal stability of Zr-cluster was evaluated using a Netzsch TG209 F1

Libra thermogravimetric analyzer from ambient temperature (20 oC) to 990 oC with

a ramp heating rate of 5 oC /min under nitrogen gas flow (0.1 L/min). Furthermore,

the ATR-FTIR spectra of Zr-clusters were obtained using a PerkinElmer

spectrometer (Spectrum 100) equipped with diamond ATR crystal. The XRD

analysis was performed with a powder X-ray diffractometer (Panalytical Xpert)

Chapter 7

174

operated with Ni-filtered Cu Kα radiation at a voltage of 40 kV and a current of 40

mA. The surface charges of Zr-clusters at different pH were measured by a zeta

potential analyzer (ZetaPALS, Brookhaven Instruments).

X-ray absorption spectroscopy.

The O K-edge absorption spectra in the energy range 520-580 eV were obtained

using the linearly polarized X-ray absorption spectroscopy with a total electron

yield (TEY) detection method, from the Surface, Interface and Nanostructure

Science (SINS) beamline at the Singapore Synchrotron Light Source (SSLS),

National University of Singapore (NUS). The spectra are divided by the photo yield

of a clean gold foil and normalized to the integrated intensity between 565 eV and

580 eV for O1s spectra after subtracting an energy-independent background.

7.3 Results

7.3.1 Material Characterizations

The specific metal-organic clusters we studied here is an oxozirconium

methacrylate cluster, Zr6(OH)4O4(OMc)12 (Zr-cluster). This Zr-cluster (Figure 7-1a)

can be obtained quantitatively through a facile recipe of treating the zirconium

source with an excess of methacrylic acid (Schubert, 1997). It contains an

octahedron-shaped hexanuclear zirconium(IV) core, in which each metal atom is

connected to oxide and hydroxide groups in a µ3-bridging manner; and the

methacrylate ligands are chelating to stabilize the cluster. The information

regarding its crystallographic structure is shown in Figure 7-1(a). In addition, it is

Chapter 7

175

calculated that one single Zr-cluster has a molecular size of 13 Å based on the

theoretical analysis of its molecular structure. Empirically, when dispersing Zr-

clusters under the high-resolution transmission electron microscope (HRTEM) as

well as the atomic-force microscope (AFM), we can observe the well separated

particles in the images as shown in Figure 7-1(b) and Figure 7-2 & 3. Both suggest

that the size of these particles spanned around a few nanometers (1-10 nm, larger

ones are due to the particle agglomeration during the sample drying process), in line

with the theoretical molecular size. The energy-dispersive X-ray (EDX) analysis

evidenced the existence of zirconium (Figure 7-1(b) and Figure 7-2), confirming

that these tiny particles are indeed the well-dispersed Zr-clusters.

Chapter 7

176

Figure 7-1. Structural concepts of Zr-cluster and schematic representations of

molecular robots for water decontamination. (a) Photograph of as-synthesized Zr-

clusters and structural representation of zirconium clusters with octahedral metal

center (octahedron-shape highlighted in blue); color code: Zr (blue), C (grey), O

(red), H atoms are omitted for clarity. (b) HRTEM image of Zr-cluster with EDX

analysis shown in inset (bottom). Inset (top): AFM image of well-dispersed

clusters. (c) ATR-FTIR spectrum of Zr-cluster indicating critical molecular

groups. (d) Zeta-potentials of Zr-cluster in water at pH 2 and pH 6.5. Inset:

Photograph of dissolved clusters under acidic aqueous condition and aggregated

flocculants formed in neutral environment. e, Schematics of molecular robotic

concept, illustrating the process of Zr-cluster as stimuli-responsive molecular

robots for water decontamination.

Chapter 7

177

Figure 7-2. HRTEM image of well-dispersed Zr-cluster. (The nano-sized particles

were highlighted in yellow circle for clarity and the EDX analysis in the inset

proves that these particles contain zirconium.)

Figure 7-3. AFM image of Zr-cluster particles. (The bright and large dots are the

agglomerated ones, which were formed during the drying process and larger than

the ideally separated particles. Some ideally separated particles can as well be

found, which are shown in the inset.)

Chapter 7

178

Further to the imaging, the as-synthesized particles were characterized by

powder X-ray diffraction (PXRD) (see Figure 7-4), as well as attenuated total

reflection-Fourier transform infrared spectroscopy (ATR-FTIR). It can be found in

the characteristic infrared spectra (Figure 7-1(c) and Figure 7-5) that the related

methacrylate sub-groups together with the distinctive Zr-O, Zr-O-Zr, and -OH

groups (at peak 660, 790, and 3350 respectively) are all present. The fairly strong

Zr-O bonds substantiate Zr-cluster’s hydrolytic stability (Faccioli et al., 2015), and

its thermal stability was confirmed using a TGA analysis (see Figure 7-6).

Combining with the fact that zirconium nanoparticles are associated with low

toxicity to living organisms and thus will not exacerbate the prevailing public health

concern on nanoparticles, a sound basis of introducing Zr-clusters for water

treatment is established (Yao et al., 2011).

Figure 7-4. PXRD full spectrum of as-synthesized Zr-cluster.

Chapter 7

179

Figure 7-5. ATR-FTIR full spectrum of as-synthesized Zr-cluster.

Figure 7-6. TGA analysis of as-synthesized Zr-cluster. (Zr-cluster was found to be

stable up to 105 oC, and therefore its functionality would not be influenced during

decontamination operations carried out at room temperature. The degradation

beyond 105 oC might be owing to the decomposition of organic ligands and then

zirconium oxide core structure.)

Furthermore, in aqueous systems, it was found that the dissolution of Zr-

clusters can be achieved at acidic pH (<3). Its zeta-potentials at two distinct pH, i.e.

pH 2 and 6.5, were recorded and shown in Figure 7-1(d). Zr-clusters repelled one

Chapter 7

180

another due to the considerably positive zeta-potential at the acidic pH, whilst

quickly aggregating at the neutral pH. Hence, on the basis of these characteristic

behaviors of Zr-cluster, we hypothesized to introduce it as a group of smart

molecular robots (capable of performing a series of complex operations in a fast

and accurate manner; and can be guided by an external control) for contaminated

water remediation (Figure 7-1(e)). In this remediation process, Zr-clusters carrying

defined active sites function individually to capture the pollutants in wastewater at

acidic pH; and when the mission is complete, which is signaled by adjusting to a

neutral pH, they would respond quickly by self-aggregation for precipitation;

moreover, the aggregated Zr-clusters can release the pollutants and re-dissolve for

a new round of decontamination practice.

7.3.2 Sorption performance

To verify this molecular robot concept, we studied the capabilities of Zr-cluster for

removing a spectrum of typical anionic pollutants, including arsenate, chromate,

fluoride and phosphate. Notably, these anionic pollutants are globally alarming: not

only do they raise severe toxicological concerns for water qualities, but they also

create a series of environmental issues in various water bodies (Blowes, 2002;

Conley, 2009; Nordstrom, 2002). For instance, both arsenate and chromate are

dangerous human carcinogens; although fluoride is known for its use in dental

products, accumulated fluoridation in water could lead to bone diseases and

neurological damages; similarly, phosphorous may work as a source of nutrient in

aquatic ecosystems, but it could easily accumulate and concentrate resulting in

tremendously harmful eutrophication. Considering the facts that ionic pollutants are

Chapter 7

181

normally non-biodegradable and associated with rapid mobility, Zr-cluster was

expected to achieve a substantial and quick removal of the pollutants.

The thermodynamic capacities of Zr-cluster were evaluated by analyzing

the equilibrium isotherms with respect to each anionic compound, as shown in

Figure 7-7 and 7-8. The isotherms appear to be better fitted by the Langmuir model

(Figure 7-8), suggesting the presence of a monolayer of similar active sites covering

the homogeneous surface. Zr-cluster demonstrates excellent uptake capacities

towards all these anionic compounds: up to ca. 175 mg-arsenic/g, 60 mg-

chromium/g, 45 mg-fluoride/g, 70 mg-phosphorus/g, respectively. It is worth

noting that the capacities are much higher than that of the commercially available

sorbents (e.g. 10 – 40 mg/g, see Table 7-1). Moreover, when computing the molar

ratio between Zr-cluster and captured compounds, we can find a consistent ratio of

1 to 4 in the cases of arsenic, fluoride and phosphorus, whereas a ratio of 1 to 2 was

found for chromium. The difference may be due to the water chemistry (details refer

to Chapter 2). Under equilibrium experimental condition (pH = 6 ~ 6.5, pC > 2),

the predominant species for arsenic, fluoride and phosphate are all monovalent

compounds (H2AsO4-, F-, H2PO3

-, respectively), whilst the chromium one is a

divalent species (CrO42-). Therefore, it is inferred that one Zr-cluster may possess

four active sites for the monovalent pollutants, and the active sites would work in

pairs to capture divalent chromate species.

Chapter 7

182

Figure 7-7. Uptake equilibrium isotherms with respect to respective anionic

pollutants by Zr-cluster.

Figure 7-8. Sorption equilibrium isotherm being analyzed by Langmuir and

Freundlich models with respect to (a) arsenate, (b) chromate, (c) fluoride and (d)

phosphate uptake.

Chapter 7

183

Table 7-1. Representative sorbents comparison

Sorbent Applications Sorption

Capacity Sorption Rate Reference

Amended SilicateTM

adsorbents (ADA

Technologies)

Arsenic uptake 40 mg/g at pH 7

30 min to

achieve 90%

equilibrium

(Frazer,

2005)

Activated carbon Arsenic uptake 30.5 mg/g at pH 7 Unknown

(Mohan and

Pittman,

2007)

Hydrous cerium

oxide–graphene

composite

Arsenic uptake 62.3 mg/g at pH 7

20 min to

achieve 90%

equilibrium

(Yu et al.,

2015a)

Lanthanum-

modified carbon

Fluoride

uptake 94 mg/g at pH 7

60 min to

achieve 90%

equilibrium

(Yu et al.,

2015b)

Chelating resins

containing

calixpyrroles

Fluoride

uptake 19 mg/g

200 min to

achieve 90%

equilibrium

(Kałędkowski

and

Trochimczuk,

2006)

Mesoporous

alumina (MA450)

Fluoride

uptake 8.3 mg/g

20 min to

achieve 90%

equilibrium

(Jagtap et al.,

2011)

Bacillus – bacterial

biomass

Chromate

uptake 39.9 mg/g

Unknown (24 h

used for

equilibrium

studies)

(Ahluwalia

and Goyal,

2007)

TiO2-graphene

hydrogel

Chromate

uptake

13.1 mg/g at pH

5.5

60 min to

achieve 90%

equilibrium

(Li et al.,

2016b)

δ-MnO2 Chromate

uptake

1.6 mg/g at pH

7.5

Unknown (48 h

used for

equilibrium

studies)

(Wang et al.,

2013)

Nanostructured Fe–

Al–Mn trimetal

oxide

Phosphate

uptake

48.3 mg/g at pH

6.8

200 min to

achieve 90%

equilibrium

(Lv et al.,

2013)

Iron-hydroxide

eggshell

Phosphate

uptake 14.5 mg/g at pH 7

180 min to

achieve 90%

equilibrium

(Mezenner

and

Bensmaili,

2009)

Al-impregnated

mesoporous silica

(Al10SBA-15)

Phosphate

uptake

26.7 mg/g at pH

6.7-7.2

50 min to

achieve 90%

equilibrium

(Shin et al.,

2004)

Zr-clusters As, Cr, F, P

uptake

175 (As), 45 (F),

60 (Cr), 70 (P)

mg/g at pH 6.5

2 sec to achieve

equilibrium This work

Chapter 7

184

In addition to exhibiting great uptake capacities, another appealing feature

of Zr-cluster for water decontamination is its superior uptake rate, as the cluster can

function in a molecular mode for pollutant capture. Referring to the aforementioned

zeta-potential behaviors, Zr-clusters in acidic aqueous media (pH = 2 ~ 2.5) are

completely dissolved and therefore each individual cluster carrying the active sites

can be fully exposed to the target pollutants. The rapid removal processes are

recorded in Figure 7-9, from which we can see that the captures of pollutants are all

completed within seconds (empirically less than 2 seconds). It should be noted that

this rate is the experimentally measured rate, where the manual handling operations

cannot be avoided for the measurements. The theoretical kinetics is deemed to be

much faster, running in a nanoseconds order of magnitude (Lynch et al., 2011;

Pappas et al., 2009). The rapid sorption process is further proved by the UV-Vis

analysis with respect to the example of phosphate removal. As shown in Figure 7-

9(b), after the addition of Zr-clusters into the contaminated water for 2 seconds, the

characteristic shoulder at 350 nm in the UV-Vis spectra was reduced to almost a

flat line. Benchmarking this remarkably fast removal rate versus the other well-

known sorbents (see Table 7-1), Zr-cluster working as molecular decontamination

robots represents a state-of-the-art approach: it is more than two orders of

magnitude faster than the sorption rates of some nano-sorbents, and three to four

orders of magnitude faster than that of conventional porous materials (Kumar et al.,

2014). This is greatly preferred in industrial applications as the rapid interaction

rate at the solid-solution interface would lead to a much-reduced retention time, and

consequently less construction footprint as well as less operating cost.

Chapter 7

185

Figure 7-9. (a) Removal rates with respect to respective anionic pollutants by Zr-

cluster. (b) UV-Vis spectra with respect to phosphate removal process by Zr-cluster.

Apart from the thermodynamic and kinetic behaviors, tests have also been

conducted to evaluate the specific affinity, selectivity and the reusability of Zr-

clusters. It was found that when arsenate, chromate, fluoride and phosphate (1 ppm

each) co-existed in a water solution, a dosage of 0.1 g/L of Zr-clusters could

effectively reduce the arsenate, fluoride and phosphate species to a desirable level

(less than 10 ppb), whereas a concentration of 0.3 ppm residual chromate can still

be detected (70% removal), as shown in Figure 7-10. The moderate affinity towards

chromate may be due to its divalent characteristics that required more active sites

of Zr-clusters. Besides, the removal efficacy of Zr-clusters towards these four

contaminants was evaluated with the coexistence of excess amounts of common

anions (Cl-, NO3-, SO4

2-) and common cations (Na+, K+, Ca2+). It was found that the

coexistence of these common ions has no effect on the pollutants uptake, as shown

in Figure 7-10. Further to that, the spent Zr-clusters can be facilely regenerated

through a quick wash in a weak alkaline aqueous solution. It was found that more

than 85 percent of the capacities were retained after three cycles (Figure 7-11). The

Chapter 7

186

finding suggests that Zr-clusters can be efficiently recycled and reused for multiple

cycles without appreciable loss of activity, which is a crucial requirement for

industrial applications.

Figure 7-10. Uptake efficiency of anionic pollutants – arsenate, chromate, fluoride

and phosphate, with the existence of common ions. (Ini. – Initial concentration;

Eq. – Equilibrium concentration)

Figure 7-11. Uptake capacities after three consecutive regeneration cycles with

respect to respective anionic pollutants by Zr-cluster.

Chapter 7

187

Moreover, we also investigated the possibility of zirconium release after the

sorption cycles, and found that less than 10 ppb of zirconium was present in the

clean water recovery, as shown in Figure 7-12. This implies: (1) low possibility of

Zr-cluster decomposition throughout the applications, (2) negligible safety concern

in regards to the remediated water recovery, (3) great aggregation efficiency of Zr-

cluster (in comparison with the initial dosage in Figure 7-12), i.e. the majority of

Zr-clusters aggregated at neutral pH for collection, which leaves behind practically

no nano-sized Zr-clusters in the post-remedy recovered water.

Figure 7-12. Zirconium elemental residual in post-remedy water recoveries, in

comparison with initial dosage of Zr clusters.

7.3.3 Mechanism analyses

The spent and aggregated Zr-clusters forming large flocculants were collected by

filtration and then analyzed by the field emission scanning electron microscopy

(FESEM) equipped with EDX, as shown in Figure 7-13(a). Again, taking the

phosphate case as the example, the elemental mapping demonstrates the precise

binding between phosphorus and zirconium elements. Further to that, the

Chapter 7

188

quantitative analysis (Figure 7-13(b)) indicates the atomic ratio between these two

elements is 6 : 4 (Zr : P). As every Zr-cluster contains six zirconium atoms, each

cluster must have caught four equivalent phosphate species. This evidence is in line

with the thermodynamic capacity data, and therefore further proves that four active

sites are provided by each Zr-cluster.

Figure 7-13. Mechanisms of anionic pollutants removal by Zr-cluster. (a) FESEM-

EDX elemental mapping of aggregated Zr-cluster flocculants that were collected

after phosphate removal. (b) EDX quantitative data together with zirconium and

phosphorus elemental ratio. (c) O K-edge XAS spectra of Zr-clusters before and

after capturing different target compounds.

We postulated that the four Zr-OH groups existing in Zr-cluster are the

active sites responsible for binding with the anionic pollutants, to form the Zr-O-M

(M: targeting compounds) complexes. To better understand the mechanisms behind,

we carried out the O K-edge X-ray absorption spectroscopy (XAS) with respect to

Chapter 7

189

the Zr-clusters before and after applications. The O K-edge XAS could assist our

analysis by revealing the transitions of O1s core level to unoccupied O2p states, of

which, the O2p states would hybridize with other atomic states (Yin et al., 2015;

Yin et al., 2016). The absorption spectra are shown in Figure 7-13(c), and they

present similar peak patterns in all cases. This indicates the fact that the octahedral

core-structure of Zr-clusters does not change after acquiring different anionic

pollutants. Therefore, Zr-clusters can be efficiently recycled and reused for repeated

cycles without modification to the main structure. In addition, the spectrum of the

as-synthesized (raw) Zr-cluster agrees well with the literature data in regards to the

Zr-O group forming octahedral structure (Soriano et al., 1993). This spectrum can

be divided into two regions: (1) The pre-edge region is attributed to the O2p-Zr4d

hybridization (527-537eV). This region exhibits two distinct peaks, A and B (Figure

7-13(c)); they are ascribed to O2p states that respectively hybridized with Zr4d eg

and t2g states, which are split by the crystal field effects of octahedral structure.

The energy separation between these peaks is defined as crystal field splitting, Δd

(Figgis, 1966), It can be found from the spectra that there is a clear decrease in Δd

when the pollutants are captured. This is due to the decrease in overlap between the

O2p states and the Zr4d bands when the former interacts with the captured

compounds, resulting in a smaller splitting of the Zr4d bands. (2) The second region

appears at higher energies and displays a more complex structure that can be

attributed to the mixture of O2p states with the Zr5sp states (Soriano et al., 1993).

Further to the O-Zr interactions, we can observe a small pre-peak at ~529eV in the

O K-edge absorption spectrum with Cr (see arrow in Figure 7-13(c)). Referencing

to the XAS studies reported previously, this pre-peak can be ascribed to the

Chapter 7

190

hybridization of O2p states with Cr d-bands (Yao et al., 2014). This is the evidence

that the oxygen in Zr-clusters hybridizes with the targeted compounds in the water,

forming Zr-O-Cr complexes. The peak signals for O-As, O-F, and O-P bonds

overlap with the existing peaks in the O K-edge absorption spectra.

7.4 Discussion and conclusion

Summarizing these results, we have demonstrated that Zr-clusters can work as

smart molecular robots and deliver a highly efficient water remediation process:

they can dissolve in acidic aqueous solutions and function swiftly for the capture of

pollutants, and then quickly aggregate at a neutral pH for precipitation and easy

collection, and facile regeneration is achieved through washing at weak basic

conditions. Furthermore, unlike the solid nature of conventional anionic sorbents,

Zr-clusters can be well dissolved and stored in the liquid-state as an acidic aqueous

solution for future applications. Therefore, they require no specific shaping or

packing into a sorption bed, and more importantly, the units in liquid-state are easier

to retrofit into existing plants or household purification systems, which significantly

reduces the footprint and operating costs (Giri et al., 2015). Besides, these

nanocluster materials are by all means simple in synthesis and process. The cost

analysis of Zr-cluster (vide infra) indicates that the raw materials are cheaper (ca. 2

times) in comparison to the commercial products on current markets, the cost of

which can be even further reduced (ca. 5 times cheaper) assuming a wholesale price

for the chemicals. All of these estimates exhibit the promise of this molecular

concept for industrial applications in the near future.

Chapter 7

191

Cost analysis of Zr-cluster based on arsenic removal

Table 7-2. Commercially available arsenic removal products and costs.

Crystal Quest: Arsenic Removal Water Filters Gaps Water Treatment: Arsenic Reduction Simplex system

Volume 85 Liter Volume 30 Liter

Price 3900 USD Price 868 USD

Cost * 2730 USD Cost * 607.6 USD

Capacity 1.5 million gallons from 50 to 10 ppb

Capacity 1500 cubic meter from 50 to 10 ppb

Total amount of arsenic removed

226.8 g Total amount of arsenic removed

60 g

Normalized cost 12 USD per unit gram of arsenic removed

Normalized cost 10.1 USD per unit gram of arsenic removed

* Assume a 30% profit margin and therefore the cost is 70% of the price.

Data achieved from:

http://www.gapswater.co.uk/acatalog/copy_of_Arsenic_Reduction_System.html

https://crystalquest.com/collections/commercial-industrial-arsenic-removal-water-filters-2

Table 7-3. Production cost of Zr-cluster.

Reagent price #

Zirconium(IV) propoxide solution

(70 wt.% in 1-propanol)

63.9 USD for 100 milliliters

Normalized price 0.639 USD for 1 mL

Methacrylic acid 44.9 USD for 500 grams

Normalized price 0.090 USD for 1 g

Zr-cluster synthesis yield 0.91 gram produced based on 1 mL Zirconium(IV) propoxide solution and 1 g methacrylic acid

Zr-cluster synthesis cost 0.801 USD per gram

Chapter 7

192

Miscellaneous cost ^ 0.343 USD per gram

Total cost 1.144 USD per gram

Zr-cluster for arsenic removal

Capacity 175 mg/g

Amount of Zr-clusters required for unit gram of arsenic removed

5.714 gram


# Price based on the online quotation of Sigma-Aldrich. This price can be further brought down if purchasing by wholesale prices. See next page.

^ Assume the synthesis cost accounts for the 70% percent of the total cost, while the miscellaneous cost takes up the rest 30%.

Note: The actual price may be further decreased if the reuse of materials for synthesis is considered.

Table 7-4. Production cost of Zr-cluster estimated based on wholesale prices.

Reagent wholesale price *

Zirconium(IV) propoxide solution

(70 wt.% in 1-propanol)

25.6 USD for 100 milliliters

Normalized price 0.256 USD for 1 mL

Methacrylic acid 18.0 USD for 500 grams

Normalized price 0.036 USD for 1 g

Zr-cluster synthesis yield 0.91 gram produced based on 1 mL Zirconium(IV) propoxide solution and 1 g methacrylic acid

Zr-cluster synthesis cost 0.321 USD per gram

Miscellaneous cost ^ 0.137 USD per gram

Total cost 0.458 USD per gram

Zr-cluster for arsenic removal

Chapter 7

193

Capacity 175 mg/g

Amount of Zr-clusters required for unit gram of arsenic removed

5.714 gram


* Wholesale price is assumed to be 40% of the currently available chemical prices shown on the website of Sigma-Aldrich.

^ Assume the synthesis cost accounts for the 70% percent of the total cost, while the miscellaneous cost takes up the rest 30%.

Note: The actual price may be further decreased if the reuse of materials for synthesis is considered.

After all, although the adverse health effects of anionic pollutants have been

known for a long time, our exposure to these pollutants perseveres, and is even

exacerbated in certain less-developed countries. Advancing from the current

anionic sorbents, Zr-clusters acting as molecular decontamination robots provide

superior performance, an efficient regeneration procedure and economic

competitiveness. In conclusion, we believe that this metal-organic cluster materials-

based technology could be of significance in addressing the global problems of

water scarcity and environmental pollution.

Chapter 8

194

CHAPTER 8 CONCLUSIONS AND

RECOMMENDATIONS

Chapter 8 concludes the achievements made in this thesis compared with the

initial aims and provides suggestions for improvements and future work.

8.1 General conclusions

This thesis focused on developing functional metal-organic materials for great

efficacies in anions removal. To achieve this, the thesis was assembled into three

major parts: to use hydro-stable Zr-MOF for effective removal of anionic pollutants

(arsenic and silica), to improve the applicability of MOF adsorbents (resolve binder

and regenerative problem), to develop a novel molecular robotic concept using

metal-organic nanoclusters for anions decontamination. Respective conclusions of

each study have been made and can be found in the conclusion section of Chapter

3-7. To avoid too much repetition and redundancy, the details of each study would

not be repeated in this chapter, rather will a general discussion together with proper

evaluations be made herein.

It has been well accepted that MOF materials are structurally diverse, and

using rational design, the chemical and physical properties of MOFs can be well

tuned and materials with very high surface areas, high porosity, and high stability

can be obtained. Functional MOFs have been viewed as a promising platform for

adsorption applications that can potentially alleviate the problems encountered by

conventional porous adsorbents. Nevertheless, the research of using functional

Chapter 8

195

MOFs for water treatment is still in its infancy. Therefore, the studies in this thesis

sought to explore the full potential of this new generation of porous materials in

wastewater remediation, especially in anions removal, taking functional MOF

materials to new frontiers by expanding their applications as well as applicability.

The development of functional adsorbents for anionic species can be seen in Figure

8-1, whilst a comprehensive comparison amongst the metal-organic materials that

were developed in this thesis can be found in Table 8-1.

Figure 8-1. Development of anions sorbents: from conventional metal oxides to

structured porous materials and now nano-clusters.

Table 8-1. Comparison and evaluation amongst metal-organic materials studied in

current thesis

UiO-66

UiO-66/α-

alumina

composite

am-UiO-

66-NO2 Zr-cluster

Reference chapter 3 & 4 5 6 7

BET surface area Great Good Good Fair

Chapter 8

196

Stability Good Good Great Fair

Applications studied Arsenate,

Silicate Arsenate

Arsenate,

Chromate,

Selenate

Arsenate,

Chromate,

Fluoride,

Phosphate

Performance

Capacity Great Good Fair Good

Kinetics Good Good Good Excellent

Reusability None None Excellent Great

Economic effectiveness Decent Fair Decent Good

Key advantage Adsorption

capacity

Continuous

treatment Reusability

Rapid

kinetics

Limitation to be resolved Reusability Fabrication

Cost

Adsorption

capacity

Extreme

condition

stability

Note Excellent > Great > Good > Decent > Fair

Achievements made in these studies with respect to the research objectives

that were addressed in Chapter 1 Introduction include:

1. All the Zr-MOFs (UiO-66 in different forms, UiO-66-NO2 and am-UiO-66-

NO2) have been synthesized and functionalized. Proper characterizations

have been carried out to understand their characteristics, including their

morphologies, particle sizes, crystallinities, element composition,

functional groups, etc.

2. UiO-66 was found to be capable of removing arsenate species with an

outstandingly great adsorption capacity and a wide working pH range.

3. UiO-66 was found to be capable of removing silicate effectively, which may

be used as a pretreatment to osmosis membrane technologies.

4. Monolayer Langmuir model were found to describe the adsorption

isotherms of Zr-MOFs.

Chapter 8

197

5. The adsorption mechanisms were carefully analyzed, and the active site was

confirmed as the Zr-OH groups responsible for complexing with the

oxyanion species.

6. A specifically designed ceramic hollow fiber was fabricated to combine

with the Zr-MOF adsorbents for delivering improved adsorption-filtration

processes, in comparison with the conventional packing column beds. The

formed composite resolved the binder problem that is normally required for

functional adsorbents in particle forms.

7. Defect engineering on hydro-stable MOF (UiO-66-NO2) to obtain

amorphous MOF (am-UiO-66-NO2), which provides enhanced adsorptive

performances and excellent regenerative capabilities for anions removal.

8. Metal-organic cluster (oxozirconium methacrylate) was developed as smart

molecular robots for anionic pollutants removal from wastewater.

Considered holistically, MOF adsorbents have been proved to provide a

superior performance in the removal of various anionic species. The adsorption

behaviors and mechanisms were systematically investigated for better

understanding. Compared to other previously reported adsorptive materials, MOF

adsorbents are advantageous. However, to go further in wastewater remediation

using MOFs as novel functional porous solids, several questions remain on the road

to commercialization. Given the relatively high synthesis cost, practical

applications using this class of materials shall be used in the developed markets

aiming at the great value-added industrial sectors. They can provide first-class

processes to remove the undesirable compounds and remediate those concentrated

Chapter 8

198

industrial wastewaters. It is believed that there is a promising future for MOF

applications as functional adsorbents in water treatment. Continuing efforts in both

academic and industrial sectors are needed in order to achieve a scale-up and cost-

effective synthesis and operation process.

8.2 Recommendations

This thesis intends to study metal-organic materials for anionic species uptake in a

systematic manner. However, most of the investigations are centered on the

empirical studies. More in-depth theoretical simulation studies can be carried out

for further understanding of the materials and their behaviors. Overall, although

certain achievements have been made, there are still quite a few limitations that can

be considered in future studies and further engineering.

Firstly, more advanced characterizations on the material structures and

sorption mechanisms shall be carried out to provide more precise evidence for

conclusions. For instance, in the case of functional clusters, single crystals can be

grown post-anion-uptake followed by diffraction measurement. Techniques like

pair distribution function (PDF) measurement and extended X-ray absorption fine

structure (EXAFS) analysis can be considered to reveal the uptake mechanism more

visually and comprehensively. However, all of these further analyses require a great

depth knowledge in physics and nanomaterials, as well as necessary access to the

instruments. They can be considered in future studies.

Secondly, in the case of clusters capturing anionic species, the actual

sorption rate is too rapid to be measured by hand. This can be visualized using a

Chapter 8

199

transient infrared spectroscope, which is able to provide the time resolved IR spectra

of clusters interacting with anionic species. By doing so, accurate equilibrium time

can be confirmed.

Thirdly, most of the adsorption studies are on the proof-of-concept stage. In

order to fully understand the adsorption behaviors, more parameter studies shall be

carried out, e.g. ionic strength effect, agitation level effect, etc. Moreover, most of

the adsorption tests are with respect to single component. Future studies shall

concentrate on analyze the multi-functionality of MOF adsorbents, and test their

performance using practical wastewater streams. The impurities in actual water

samples such as colloid particles, natural organic matter, and co-existing ions might

influence the adsorption performance.

Fourthly, all the adsorption tests conducted are in batch mode and in lab-

scale. Future studies in pilot scale shall be considered to evaluate the materials’

performance in larger scale and longer-term use. The operation parameters such as

the retention time, influent water quality and temperature should be further

investigated in the operation process. This is especially important in the case of

MOF/α-alumina composite, for which further engineering is needed. Such

characteristics as reusability, membrane strength and anti-fouling properties shall

be carefully studied in the next phase.

List of Publications

200


Paper published

1) C. Wang, X. Liu, J. P. Chen and K. Li, Applications of water stable metal-

organic framework. Chemical Society Review, 2016, 45, 5107-5134. IF: 38.

(Chapter 2)

2) C. Wang, M. Lee, X. Liu, B. Wang, J. P. Chen and K. Li, Metal-organic

framework/α-alumina composite with novel geometry for enhanced adsorptive

separation. Chemical Communications, 2016, 52, 8869-8872. IF: 6.8. (Chapter

5)

3) C. Wang, X. Liu, J. P. Chen and K. Li, Superior removal of arsenic from water

with zirconium metal-organic framework UiO-66. Scientific Reports, 2015, 5,

16613. IF: 5.6. (Chapter 3)

4) X. Liu, C. Wang, B. Wang and K. Li, Novel organic-dehydration membranes

prepared from zirconium metal-organic frameworks. Advanced Functional

Materials, 2017, 27, 1604311. IF: 11.4.

5) Y. Yu, C. Wang, X. Guo and J. P. Chen, Modification of carbon derived from

Sargassum sp. by lanthanum for enhanced adsorption of fluoride. Journal of

Colloid and Interface Science, 2015, 441, 113-120. IF: 3.6.

6) D. Zhao, Y. Yu, C. Wang and J. P. Chen, Zirconium/PVA modified flat-sheet

PVDF membrane as a cost-effective adsorptive and filtration material: a case

study on decontamination of organic arsenic in aqueous solutions. Journal of

Colloid and Interface Science, 2016, 477, 191-200. IF: 3.6.


201

7) C. Wang, X. Liu, X. Yin, M. Lee, A. Wee, J. P. Chen and K. Li, Zirconium-

based nanoclusters as molecular robots for water decontamination. In

submission. (Chapter 7)

Conference presentations

1) 9th JSPS HOPE Meeting with Nobel Laureates. Japan, February 2017.

2) ACS Publications Symposium: Innovation in Molecular Science. China,

November 2016.

3) 13th IWA Specialized Conference on Small Water and Wastewater Systems

(SWWS) and 5th IWA Specialized Conference on Resources-Oriented

Sanitation (ROS). Greece, September 2016.

4) 6th International Congress on Ceramics. Germany, August 2016.

5) AIChE annual meeting. United States, November 2015.

6) AIChE annual meeting. United States, November 2014.

Appendix

202

Appendix

Molecular structural information and ligand abbreviations of MOFs

MOF Molecular formula Ligand information

bio-MOF-1 Zn8(ad)4(BPDC)6O⋅2Me2N

H2

ad = adeninate; BPDC =

biphenyl dicarboxylic acid.

CALF-25 BaH2L Barium tetraethyl-1,3,6,8-

pyrenetetraphosphonate

CAU-1 [Al4(OH)2(OCH3)4(H2N-

bdc)3]⋅x H2O

bdc = 1,4-

benzenedicarboxylate

(terephthalate)

CAU-10 [Al(OH)(m-BDC-X)1−y(m-

BDC-SO3H)y] (X=H, NO2,

OH)

H2BDC=1,3-

benzenedicarboxylic acid

Cu2L Cu2L L=3,3’,5,5’-tetraethyl-4,4’-

bipyrazolate

FIR-54 [Zn(Tipa)]·2NO3·DMF·4H2

O

Tipa = tris(4-(1H-imidazol-1-

yl)phenyl)amine); DMF =

dimethylformamide.

FMOF-1 Ag4Tz6 Tz = 3,5-bis(trifluoromethyl)-

1,2,4-triazolate

HKUST-1 Cu3(BTC)2(H2O)3 BTC=1,3,5-

benzenetricarboxylate

M3(BTP)2 (M =

Ni, Cu, Zn, Co)

Ni3(BTP)2·3CH3OH·10H2O H3BTP = 1,3,5-tris(1H-

pyrazol-4-yl)benzene

MAF-6 Zn(eim)2 eim = 2-

ethylimidazolate

MAF-7 Zn(mtz)2 mtz = 3-methyl-1,2,4-

triazolate

MAF-49 Zn(batz) H2batz = Bis(5-amino-1H-

1,2,4-triazol-3-yl)methane

MAF-X8 Zn(mpba) H2mpba = 4-(3,5-

dimethylpyrazol-4-yl)benzoic

acid)

MAF-X25ox [MnIIMnIII(OH)Cl2(bbta)] H2bbta = 1H,5H-benzo(1,2-

d:4,5-d’)bistriazole

Mg-CUK-1 [Mg3(2,4-pdc)2(OH)2] pdc = pyridinedicarboxylate

MIL-53(Cr) Cr(OH)(BDC) BDC = (O2C)-C6H4-(CO2)

MIL-68 Fe(OH)(bdc) bdc = 1,4-


(terephthalate)

MIL-96 Al12O(OH)18(H2O)3(Al2(OH

)4)(BTC)6⋅24H2O

BTC=1,3,5-


MIL-100 Fe3O(C6H3(CO2)3)2 –

MIL-101 Cr3F(H2O)2O(BDC)3 BDC = (O2C)-C6H4-(CO2)

Appendix

203

MIL-121 (Al(OH)[H2btec]·(guest)

(guest = H2O, H4btec)

H4btec = 1,2,4,5-

benzenetetracarboxylic acid,

pyromellitic acid

MIL-124 Ga2(OH)4(C9O6H4) -

MIL-160 AlO6C6H3 FDCA = 2,5-furandicarboxylic

acid

MIL-163 Zr(H2-TzGal) H6-TzGal = 5,5′-(1,2,4,5-

tetrazine-3,6-diyl)bis(benzene-

1,2,3-triol)

mmen-

Mg2(dobpdc)

mmen-Mg2(dobpdc) mmen = N,N’-

dimethylethylenediamine;

dobpdc = 4,4’-

dioxidobiphenyl-3,3’-

dicarboxylate

MOF-5 Zn4O(BDC)3 BDC = (O2C)-C6H4-(CO2)

MOF-74 [Mg2-(dobdc)(H2O)2]·6H2O dobdc = 2,5-dioxido-1,4-


MOF-801 Zr6O4(OH)4(fumarate)6 –

MOF-808 Zr6O4(OH)4-

(BTC)2(HCOO)5(H2O)2

BTC = 1,3,5-


MOF-841 Zr6O4(OH)4(MTB)2(HCOO)

4(H2O)4

H4MTB = 4,4′,4″,4‴-

Methanetetrayltetrabenzoic

acid

Na-HPAA Na2(OOCCH(OH)PO3H)(H2

O)4

HPAA =

hydroxyphosphonoacetate

NENU-1 [Cu2(BTC)4/3(H2O)2]6[H2Si

W12O40]⋅(C4H12N)2

BTC = 1,3,5-


NENU-500 [TBA]3[PMoV8MoVI

4O36(O

H)4Zn4][BTB]4/3

BTB = benzene tribenzoate;

TBA = tetrabutylammonium

ion

NH2-MIL-125 Ti8O8(OH)4(C6H3C2O4NH2)

6

–

[Ni(BPEB)] Ni(BPEB) H2BPEB = 1,4-bis(1H-

pyrazol-4-ylethynyl)benzene

NU-1000 Zr6(OH)8(OH)8(TBAPy)2 TBAPy = 1,3,6,8-tetrakis(p-

benzoic acid)pyrene

NU-1100 Zr6(OH)4(OH)4(L)4 L4H = 4-[2-[3,6,8-tris[2-(4-

carboxyphenyl)-ethynyl]-

pyren-1-yl]ethynyl]-benzoic

acid

NU-1105 C312H210O32Zr6 (Zr6-oxo clusters) (ligand =

Py-FP)

PCMOF10 Mg2(H2O)4(H2L)·H2O H6L = 2,5-dicarboxy-1,4-

benzene-diphosphonic acid

PCN-222 C48H32ClFeN4O16Zr3 Fe-TCPP (TCPP=tetrakis(4-

carboxyphenyl)porphyrin)

PCN-228 Zr6(OH)4O4(TCP-

1)3·10DMF·2H2O

TCP = tetrakis(4-

carboxyphenyl)porphyrin;

Appendix

204

DMF = dimethylformamide.


2)3·45DMF·25H2O

TCP = tetrakis(4-




3)3·30DMF·10H2O

TCP = tetrakis(4-



PCN-521 [Zr6(OH)8(OH)8)]L2 L = 4′,4′′,4′′′,4′′′′-

methanetetrayltetrabiphenyl-4-

carboxylate, MTBC

PCN-523 [Hf6(OH)8(OH)8)]L2 L = MTBC

PCN-601 [Ni8(OH)4(H2O)2Pz12]TPP Pz = pyrazolate; H4TPP =

5,10,15,20-tetra(1H-pyrazol-4-

yl)porphyrin.

PCN-777 Zr6(O)4(OH)10(H2O)6(TATB

)2

TATB = 4,4’,4’’-s-triazine-

2,4,6-triyl-tribenzoate

PCP-33 (Cu4Cl)(BTBA)8·(CH3)2NH

2)·(H2O)12

H3BTBA = 3,5-bis(2H-

tetrazol-5-yl)-benzoic acid

Tb-DSOA ([Tb4(OH)4(DSOA)2(H2O)8]

·(H2O)8)n

DSOA = 2,2′-disulfonate-4,4′-

oxydibenzoic acid

UiO-66 Zr6O4(OH)4(BDC)6 BDC = (O2C)-C6H4-(CO2)

UiO-67 Zr6O4(OH)4(bpdc)6 bpdc = biphenyldicarboxylate,

O2C(C6H4)2CO2

UiO-68 Zr6O4(OH)4(C20H10O4)6 –

ZIF-7 Zn(bim)2 Hbim = benzimidazole

ZIF-8 Zn(mim)2 Hmim = 2-methylimidazole

ZIF-67 Co(mim)2 Hmim = 2-methylimidazole

ZIF-90 Zn(C4H3N2O)2 2-carboxaldehyde imidazolate

Zn-pbdc Zn-pbdc pbdc = poly(1,4-

benzenedicarboxylate)

Note: AEMOF – alkaline earth metal-organic framework; BFMOF – backfolded

metal-organic framework; CALF – Calgary Framework; CAU – Christian

Albrechts University; CPP – coordination polymer particle; FIR/FJI – Fujian

Institute of Research; HKUST – Hong Kong University of Science and

Technology; IRMOF – isoreticular metal-organic framework; JLU – Jilin

University; MAF – metal azolate framework; CUK – Cambridge University-

KRICT; MIL – Matérial Institut Lavoisier; NENU – Northeast Normal

University; NU – Northwestern University; PCP – Porous Coordination

Polymer; PCMOF – proton-conducting metal-organic framework; PCN – porous

coordination network; UiO – University of Oslo; ZIF – Zeolitic Imidazolate

Framework.

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