Chemosphere 87 (2012) 918–924

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Chemosphere

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Influence of surface functionalization and particle size on the aggregation kineticsof engineered nanoparticles

Junfeng Liu a, Samuel Legros a, Guibin Ma b, Jonathan G.C. Veinot b, Frank von der Kammer a,⇑,Thilo Hofmann a,⇑a Department of Environmental Geosciences, University of Vienna, Althanstrasse 14 UZAII, A-1090 Vienna, Austriab Department of Chemistry, University of Alberta, Edmonton, Alberta, Canada T6G 2G2

a r t i c l e i n f o

Article history:Received 8 August 2011Received in revised form 19 January 2012Accepted 23 January 2012Available online 19 February 2012

Keywords:GoldDLSColloidal stabilityNatural organic matter

0045-6535/$ - see front matter � 2012 Published bydoi:10.1016/j.chemosphere.2012.01.045

⇑ Corresponding authors. Tel.: +43 1 4277 53380; fE-mail addresses: frank.von.der.kammer@univie.ac

hofmann@univie.ac.at (T. Hofmann).

a b s t r a c t

In an effort to minimize the impact on the environment or improve the properties of choice, most engi-neered nanoparticles used for commercial applications are surface functionalized. The release of thesefunctionalized engineered nanoparticles (FENPs) into the environment can be either deliberate or acci-dental. Scientific research to date has tended to focus on evaluating the toxicity of FENPs, with less atten-tion being given to exposure assessments or to the study of their general behavior in naturalenvironments. We have therefore investigated the effects of environmental parameters such as pH, NaClconcentration, and natural organic matter concentration on the aggregation kinetics of FENPs with timeresolved dynamic light scattering, using functionalized gold nanoparticles (FAuNPs) as a representative ofthese particles. We also investigated the effects of average particle size, the type of surface capping agent,and particle concentration on FAuNP aggregation kinetics. Our results show that the physico-chemicalproperties of the capping agent have a greater influence on the aggregation behavior of FAuNPs thaneither their core composition or their particle size.

� 2012 Published by Elsevier Ltd.

1. Introduction

Functionalized engineered nanoparticles (FENPs) are derivedfrom engineered nanoparticles (ENPs) through the addition of acapping agent to their surfaces. ENP surfaces offer a platform formolecules to bond with ENPs (e.g., through electrostatic or covalentbonding), resulting in changes to the physical and chemical proper-ties of the particles. Such surface modification offers a convenientapproach to tailoring ENP properties and making them more suit-able for their intended application. Examples include the use of cat-ionic surfactants to assist the dispersion of hydrophilic nanoclay ina polymer matrix, or the coating of TiO2 nanoparticles in sunscreenswith aluminum oxide to suppress photocatalytic activity (Matsum-oto et al., 2000; Tong and Deng, 2006). FENPs have been widely usedin biomedical (El-Sayed et al., 2005; Wangoo et al., 2008), catalytic(Zhao et al., 2006; Cuquerella et al., 2010), optical (Chau et al., 2006;Sharma and Gupta, 2006), cosmetic (Wu and Guy, 2009; Kokuraet al., 2010), and electronic fields (Ozawa et al., 2009; Ashwellet al., 2010). In this regard, it is very likely that these materials willbe released into the environment, either during their production oras a result of use. The chemistry of the functionalization or capping

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used on these particles is expected to dominate their physico-chemical behavior, rather than the properties of the particle cores(Dougherty et al., 2008).

The behavior of FENPs within the natural environment remainspoorly understood. Studies have been carried out on the toxicity ofFENPs (Pan et al., 2007; Chen et al., 2009) but very little (if any)attention has been paid to exposure assessments or the measure-ment of actual FENP concentrations in natural environments. Aprecise understanding of the mechanisms determining colloidalstability and the related aggregation processes for FENPs in aquaticenvironments is also required to support exposure modeling.

Although stability and aggregation studies have been carried outon ENPs such as TiO2 and CeO2 (Buettner et al., 2010; von derKammer et al., 2010; Ottofuelling et al., 2011) the results obtainedare not directly applicable to FENPs, even if they are of the samematerial, because of the different physico-chemical properties im-posed by the introduction of the capping agent. Indeed, the colloidalstability of FENPs is not only a function of environmental parame-ters (e.g., pH, ionic strength, electrolyte type), but also the characterof the capping agent, the nature of the bonding between the cap-ping agent and the surface of the particle, and in part to the natureof the core material. For example, different behavior has been ob-served between functionalized silver nanoparticles (FAgNPs) (El Ba-dawy et al., 2010) and functionalized gold nanoparticles (FAuNPs)(Diegoli et al., 2008) under comparable environmental conditions;

J. Liu et al. / Chemosphere 87 (2012) 918–924 919

the colloidal stability of citrate-coated FAgNPs is affected bychanges in the pH and by changes in calcium concentrations; thisis not the case for analogs FAgNPs coated with polyvinylpyrrolidone(El Badawy et al., 2010). Similarly, gold nanorods functionalizedwith mercaptoundecanoic acid show a higher negative surfacecharge than their uncoated counterparts (Dougherty et al., 2008).In addition, Basu et al. (2007) indicated capping agents of FENPsmay also influence their interactions with microorganisms.

The mechanisms of FENP aggregation and the stability of FENPsare controlled by electrostatic interactions, steric stabilization, andcomplex interactions with the capping agents – especially whencapping agents are large organic macromolecules, but the detailedmechanisms involved are not yet fully understood. The objective ofthis study was to examine the influence of capping agents andaverage particle size on the aggregation behavior of FENPs. We em-ployed functionalized gold nanoparticles (FAuNPs) as a representa-tive of FENPs, using different sizes (30 nm and 100 nm diameter)and capping agents (citrate, and 11-mercaptoundecanoic acid).We investigated the aggregation kinetics as a function of particleconcentration, pH, NaCl concentration, and natural organic matter(NOM) concentration, using time-resolved dynamic light scatteringanalysis to establish the initial aggregation rate constants. Theseaggregation rate constants, as a function of environmental param-eters, can be used to support exposure modeling used to predictFENP concentrations in different natural environments.

2. Materials and methods

2.1. Preparation and characterization of FAuNPs

2.1.1. Preparation of FAuNP stock suspensionsThree different FAuNPs of two different sizes and with two dif-

ferent capping agents were investigated in this study. Citrate-coated FAuNPs of two different sizes were purchased from BritishBiocell International (BBI), these being 30 nm (C30) and 100 nm(C100), and FAuNPs coated with 11-mercaptoundecanoic acid(M30) were synthesized by the Chemistry Department of the Uni-versity of Alberta in Edmonton, AB., Canada. The preparation of theM30 FAuNPs involved three stages as follows. (1) Synthesis: Goldnanoparticles were prepared in an aqueous solution by heating asolution of H2AuCl4�2H2O (0.25 mM) and citric acid (4.25 mM) toapproximately 90 �C for 1 h to obtain the desired size of gold nano-particles; (2) Functionalization: The stock of gold nanoparticles wasadded directly to an ethanol solution of 11-mercaptoundecanoicacid (0.25 mM) and the mixture stirred under subdued lightingfor 1 week. During this period, the apparent color of the solutionchanged from ‘‘blood red’’ to ‘‘purple red’’; and (3) Purification:Dialysis time was based on our past experience with other systems(personal communication Jonathan Veinot). For monitoring thepresence of 11-mercaptoundecanoic acid using thin layer chroma-tography (TLC), the concentration is too low for detection.

2.1.2. Characterization of FAuNP stock suspensionsThe size and zeta potential of each FAuNP suspension was measured

bydynamiclightscatteringusingaMalvernZetasizerNano-ZS(Table1)

Table 1Details for applied FAuNPs in the study.

Sample Capping agent Particlediameter(nm)

Zetapotential(mV)

Concentration(mg L�1)

C30 Citrate 31 ± 0.32 �42.0 ± 2.0 40.4 ± 0.35C100 Citrate 98 ± 2.02 �49.8 ± 0.21 37.9 ± 0.26M30 11-Mercaptoundecanoic acid 28 ± 0.35 �45.3 ± 3.6 19.04 ± 0.10

– see detailed description below. The concentrations of stock suspen-sions were investigated by inductively coupled plasma optical emis-sion spectroscopy (ICP-OES, PerkinElmer Optima 5300 DV) followingdigestion with concentrated aqua regia solution at 80 �C.

2.2. Solution chemistry

Millipore water with a maximum resistivity of 18 MX cm�1 wasused for all experiments, prepared by using a Millipore AdvantageA10 system (Millipore, Billerica, US) equipped with a Bio-PakTM ul-tra filter (5000 g mol�1 molecular weight cut-off). Stock NaCl solu-tions used for adjusting the electrolyte background in sampleswere prepared by dissolving reagent-grade NaCl in water. The pHwas adjusted using 0.1 M HCl and 0.1 M NaOH (Titrisol, Merck,Austria). Suwannee River Natural Organic Matter (SRNOM; Inter-national Humic Substances Society) was used as a standard sampleof natural organic matter (NOM) that has been well studied inaquatic environments. A 1 g L�1 SRNOM stock solution was pre-pared and then diluted to 0.1 g L�1 and 0.01 g L�1 for use in samplepreparation. The DOC of the SRNOM stock solution, 0.4 ±0.015 g L�1, was also determined in the study (Table S1).

2.3. Sample preparation

Polycarbonate disposable cuvettes (1 � 1 cm; Macherey & Na-gel, Germany) were used for sample preparation and time-resolveddynamic light scattering measurement. All experiments followedthe sequence: (1) addition of Millipore water, (2) addition of NaCl,(3) addition of HCl or NaOH, when required, (4) addition ofSRNOM, when required, (5) 10 min on the auto-shaker, (6) additionof FAuNPs, (7) time-resolved dynamic light scattering measure-ment, and (8) pH measurement.

The first set of experiments investigated the influence of initialconcentration of FAuNPs on their aggregation kinetics. The massconcentration of FAuNPs varied from 2.5 to 20 mg L�1, which isequivalent to between 9.2 � 109 and 7.3 � 1010 particles per mLfor the 30 nm spherical particles and between 2.5 � 108 and2 � 109 particles per mL for the 100 nm particles. The number con-centrations were obtained assuming a density of 19.3 g cm�3 forgold. The NaCl concentration was set to 0.5 M and the pH was be-tween 6.2 and 6.8.

The second set of experiments investigated the influence ofelectrolyte concentration on the aggregation kinetics of FAuNPs.The FAuNP concentration was set to 5 mg L�1, the NaCl concentra-tion varied between 0.01 M and 0.5 M, and the pH was again be-tween 6.2 and 6.8.

The third set of experiments investigated the influence of sus-pension pH on the aggregation kinetics of FAuNPs. The NaCl con-centration was set to 0.001 M and the FAuNP concentration to5 mg L�1, while the pH of the suspension ranged from 2.00 to12.31.

The final set of experiments investigated the influence ofSRNOM on the aggregation kinetics of FAuNPs. The NaCl concentra-tion was set to 0.1 M for the C30 and C100 particles, and to 0.2 Mfor the M30 particles. The FAuNP concentration was set to5 mg L�1, the SRNOM concentration varied between 0.5 mg L�1

and 100 mg L�1, and the pH ranged from 6.5 to 7.2.

2.4. Dynamic light scattering

All time-resolved aggregation kinetics studies were carried outin the standard 1 � 1 cm disposable cuvettes. Particle size wasdetermined by dynamic light scattering at 20 �C using a ZetasizerNano-ZS equipped with a 4 mW He–Ne laser (633 nm). The scat-tered light was observed at a fixed backscattering angle of 173�.Each aggregation kinetics experiment consisted of 60 individual

Aggr

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a

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Fig. 1. Influence of FAuNP concentration on aggregation kinetics. (a) Linearrelationship between mass concentration of different FAuNPs and initial slope(k11); and (b) linear relationship between number concentration of differentFAuNPs and initial slope (k11). The error bars represent the standard deviation oftriplicate measurements.

920 J. Liu et al. / Chemosphere 87 (2012) 918–924

measurements. The hydrodynamic diameter of the particles wascalculated from the particle diffusion coefficient (D) with theStokes–Einstein equation, using the cumulant method for fittingthe autocorrelation function (Kretzschmar et al., 1998). For thefast-aggregating C30 and M30 particles, every measurement con-sisted of five replicates, each with a 2 s collection time. The appliedparticle number concentrations for the C100 particles could belower because of the higher scattering intensity of each individualparticle, and six replicates measurements were made, each with a10 s collection time. All experiments were performed in triplicate,with the optimum measurement position and attenuator positiondetermined from preliminary tests and then fixed for each set ofthree experiments.

2.5. Determination of aggregation kinetics

The initial increase in hydrodynamic radius is proportional toboth the aggregation rate constant (k11) and initial particle numberconcentration (C) – see Eq. (1) below (Kretzschmar et al., 1998). Ifthe particle concentration is constant, the aggregation rate can bedetermined directly from the initial slope of the regression curvesobtained from plots of particle size against aggregation time.

drh

dt

� �t!0

a k11C ð1Þ

The attachment efficiency (a) was calculated from Eq. (2) (below) inorder to elucidate the influence of NaCl concentration. The attach-ment efficiency is determined by normalizing the rate of slowaggregation (k11, which is in the reaction-controlled aggregation re-gime) with respect to the rate of fast aggregation (kfast, which is inthe diffusion-limited aggregation regime).

a ¼ k11

kfast¼

drhdt

� �t!0

h idrhdt

� �t!0

h ifastð2Þ

In the reaction-controlled aggregation regime the surface chemistryof the particles is the dominant factor affecting particle attachment.The rate of attachment increases with increasing electrolyte con-centration until the electrical double layer is fully compressed andconditions are most favorable aggregation. This electrolyte concen-tration is termed the critical coagulation concentration (CCC). Atelectrolyte concentrations above the CCC the system is fully desta-bilized and aggregation is solely dependent on the number of parti-cle collisions. The aggregation rate is hence determined directly bythe diffusional behavior of the particles, which is what is known as adiffusion-limited aggregation regime (Chen and Elimelech, 2006).

The initial slopes of the aggregation plot were calculated fromthe first 5 points for C30 and M30 particles, and the first 15 pointsfor C100 particles. In most cases the hydrodynamic radii of the lastpoints used for the rate calculations were within the factor of1.38rh1 that is typically used to determine the doublet formationrate (Holthoff et al., 1996). The results presented herein can, in the-ory, also be seen as doublet formation rates. In some cases the veryfirst measurements might have been missed due to initialization ofthe Zetasizer at the beginning of each measurement. However, alinear relationship still exists between the data points used andregression curves.

3. Results and discussion

3.1. Influence of FAuNP concentration on aggregation kinetics

As expected, a positive linear relationship was observed be-tween the aggregation rate constant (k11) and the particle massconcentration (Fig. 1a). The magnitude of k11 and its increase with

mass concentration were both greater for C30 and M30 than forC100. After converting the FAuNP mass concentrations to particlenumber concentrations, C30, C100 and M30 show the same linearrelationship (Fig. 1b). Transforming mass concentrations into num-ber concentrations bears the high risk of introducing a mathemat-ical bias, especially when using the average diameter frommultimodal, broad or skewed distributions. In this case the parti-cles are almost monodisperse and narrowly distributed, in particu-lar since the BBI particles used in the study are the basis for thecertified NIST gold nanoparticle standard. Therefore we expect thattransforming mass concentration in number concentration has lit-tle influence being underpinned by the very good linear regression(R2 value of 0.9565). In addition, plotting the 99% confidence inter-val on linear fitting all aggregation rate constants fall in the sameregression line (Fig. S2).

Although still commonly used as a descriptor for ENP disper-sions, the mass concentration of nanoparticles is not always help-ful when investigating particle number related reactions, sinceaggregation reactions are based on particle–particle collisions that

NaCl concentration (M)0.001 0.01 0.1 1

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Fig. 2. Relationship between NaCl concentration and attachment efficiency (a) ofFAuNPs. The error bars represent the standard deviation of triplicatemeasurements.

J. Liu et al. / Chemosphere 87 (2012) 918–924 921

are determined by the number of particles per volume rather thanby their mass concentrations. As is clear from Fig. 1b, particle num-ber concentrations make the description of aggregation rates as afunction of particle concentration independent of particle size. Thisindicates the C30, C100 and M30 FAuNPs tested herein are in thediffusion-limited aggregation regime. Kretzschmar et al. (1998)found a similar linear relationship for natural nanoparticles. Theslightly lower increase rate of k11 with number concentration forM30 than for C30 may indicate a slight difference in the stabiliza-tion of these particles due to differences in their coatings.

3.2. Influence of NaCl concentration on aggregation rate

The attachment efficiency (a) for the FAuNPs was found to varyas a function of the NaCl concentration (Fig. 2). With increasingNaCl concentration the attractive van der Waals forces becomeincreasingly more dominant until finally all particle collisions re-sult in attachment at fully favorable conditions (fast aggregationin diffusion limited aggregation).

All FAuNPs in Fig. 2 shows CCC values within the range of NaClconcentrations used. The FAuNPs with the same capping agent butdifferent particle sizes (C30 and C100) share the same CCC of0.07 M NaCl which is much higher than that for TiO2 (anatase,7.24 � 10�3 M) reported by Hsu and Chang (2000); it is similar tothat for fullerenes (0.12 � 10�3 M) (Chen and Elimelech, 2006),but lower than that for natural nanoparticles (>0.3 � 10�1 M)(Grolimund et al., 1998). The higher CCC values compared to thatof TiO2 can be attributed to additional electrostatic repulsion intro-duced by the citrate stabilizing the gold nanoparticles. In accor-dance with our own results, El Badawy et al. (2010) observed thehydrodynamic diameter of citrate-coated FAgNPs increasing from10 nm to approximately 400 nm when the NaNO3 concentrationwas increased from 0.01 M to 0.1 M at pH 6. Despite different corecompositions, both citrate-coated FAuNPs and citrate-coated FAg-NPs showed aggregation in the same Na+ concentration range(0.01–0.1 M), indicating that the surface functionalization controlsthe aggregation behavior. The CCC for M30 particles (0.2 M) ismuch higher than that for C30 and C100 particles. This result couldbe explained by a difference in surface coverage between citrateand 11-mercaptoundecanoic acid. Nevertheless, the zeta potentialvalues measured on the stock suspension (Table 1) are very similarfor all applied FAuNPs in this study. Therefore, even if there mightbe different amount of capping agent on the different particle sur-face, their electrostatic behavior is rather similar. In the presence ofsimilar zeta potentials for both types of particles the higher CCC forM30 could be explained by an additional component of stericrepulsion that would be induced by the long-chain of 11-mercap-toundecanoic acid. Indeed, steric repulsion can increase the CCC bysome hundred mM (Pincus, 1991), and may even prevent aggrega-tion completely.

Overall, despite having a similar core composition and size, dif-ferent aggregation behavior occurs as a result of the different cap-ping agents.

3.3. Influence of pH on aggregation kinetics

The pH related aggregation rate constant (k11) for C30, C100 andM30 particles was observed at a constant background electrolyteconcentration (NaCl at 1 mM; Fig. 3). Below pH 3, C30 and C100particles start to aggregate but no aggregation was observed whenthe suspension pH was above 3. Aggregation at low pH arises fromthe neutralization of the surface charge by protonation of the car-boxylic acid groups of citrate on the surfaces of C30 and C100 par-ticles. The pKa of the carboxylic groups on the citrate surfaces were3.13, 4.76, and 6.4 (Ghose et al., 2002) which have been measuredin water. Some variation deriving from the interaction of citrate

with the gold nanoparticle surface could occur. Nevertheless, eventhough the exact bonding between citrate ions and the gold surfaceis still uncertain, FTIR measurement (Fig. S5) demonstrated that itis not a covalent bonding to the surface of the gold particles. Thisresult is confirmed by SERS measurement in Zhu et al. (2003).Therefore, pKa values of the citrate measured in water are likelyto be very close to the pKa values of the citrate on the gold surface.At pH 7, the citrate-coated FAuNPs were electrostatically stabilizedby the negative charge of the deprotonated carboxylic acid groups(Fig. S1, supplementary information). At a pH below the lowest pKa

of citrate, the negative surface charge of the citrate was fully neu-tralized by protonation. Citrate-coated FAuNPs then enter into a

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Fig. 3. The initial slopes (aggregation rate constant, k11) of different FAuNPs used inthe study, as a function of pH, in 1 mM NaCl. The error bars represent the standarddeviation of triplicate measurements.

922 J. Liu et al. / Chemosphere 87 (2012) 918–924

fast aggregation regime. Consistent with our study, El Badawy et al.(2010) also showed that with a decrease in pH from 10 to 2 at0.01 M NaNO3, the particle size increased from 10 nm (at a pH be-tween 10 and 6) to about 1000 nm (at a pH of around 3), suggest-ing that the pKa of the capping agent is a critical factor for thestabilization of FENPs.

For M30 particles, aggregation started at pH values between4.30 and 5.42, in agreement with results published by Smalleyet al. (1999). In their study, the pKa of the 11-mercaptoundecanoicacid coated FAuNPs fell from 5.7 ± 0.2 to 4.4 ± 0.2 when the electro-lyte concentration changed from 0.1 to 1 M NaClO4 (Smalley et al.,1999). A study by Dougherty et al. (2008) reported the zeta poten-

tial of an 11-mercaptoundecanoic acid coated gold nanorod to bein the range of approximately �60 mV to 0 mV for a pH of that ran-ged from about 7 to slightly lower than 2, which is also consistentwith our results.

3.4. Influence of SRNOM on aggregation kinetics

The influence of SRNOM on the aggregation behavior of FAuNPscoated with citrate and 11-mercaptoundecanoic acid was investi-gated under ionic strength conditions that favored a fast aggrega-tion (Fig. 4). The presence of 100 mg L�1 of SRNOM reduced theaggregation rate from 0.39 to 0.041 for C30 particles and from0.018 to 0.010 for C100 particles, but adding SRNOM did not appar-ently change the fast aggregation rate constant for M30 particles.

We assume that the citrate on C30 and C100 particle surfaceswere substituted by SRNOM but that SRNOM did not replace the11-mercaptoundecanoic acid on M30 particle surfaces. This isdue to the bonding between citrate and gold surface, commonlyrecognized as a weak bonding (physical adsorption by electrostaticforces) (Zhu et al., 2003). This weak bonding would permit the cit-rate to be displaced by SRNOM. Diegoli et al. (2008) showed thathumic acid was able to substitute citrate capping on gold nanopar-ticles and retard aggregation. On the contrary, it is well acceptedthat 11-mercaptoundecanoic acid is bound to gold nanoparticlesvia a covalent thiol bound (Jordan et al., 1994; Weisbecker et al.,1996; Stettner et al., 2009) which is a much stronger bonding togold nanoparticles than citrate. XPS measurements have been per-formed (see Fig. S6) and were consistent with this hypothesis. Be-sides, the coverage and/or the conformation of the 11-mercaptoundecanoic acid on the gold surface may also not permitSRNOM functional groups to reach the surface. Zhang et al. (2000)investigated the displacement adsorption of 4-mercaptopyridineon a citrate-coated gold surface using AFM-based force measure-ments and concluded that the bonding between gold and thiol(Au–S) is strong, and Vitale et al. (2008) pointed out that the Au–S is a covalent bond. Both of these last two results can be used assupporting evidence for our hypothesis on the effects that SRNOMhas on M30 particles.

Stankus et al. (2011) studied gold nanoparticles coated with cit-rate and with 2,2,2-[mercaptoethoxy(ethoxy)]ethanol (MEEE).MEEE has a similar structure to the 11-mercaptoundecanoic acidused in our tests and the same covalent thiol bonding to the goldsurface (Fig. S1). In the presence of 0.01 and 0.1 M monovalent ions(KCl), they observed that NOM (humic acid) had a stabilizing effecton gold nanoparticles coated with citrate, consistent with the pres-ent findings. On the contrary, they observed a stabilizing effect ofNOM (humic acid) for gold nanoparticles coated with MEEE inmonovalent electrolyte regardless of the amount of NOM added,while in this study despite 11-mercaptoundecanoic acid bearingan ionic group (carboxylate) that should provide greater electro-static repulsion, no stabilization of the particles was detectable fol-lowing the addition of NOM in the presence of a monovalentcation. This difference is most likely due to a different sample prep-aration sequence used in our study compare to that used by Stan-kus et al. (see Supporting Information). We added FAuNPs into thebackground solution already containing SRNOM and electrolyte,whereas Stankus et al. introduced the electrolyte into a cuvettecontaining NOM (humic acid) and FAuNP suspension as the finalstep prior to the measurement. Using the same sample preparationsequence as Stankus et al. the aggregation rate of M30 particles in afast aggregation regime was reduced as the SRNOM concentrationincreased (Fig. S3). We assume that in this case the SRNOM ad-sorbed to the surface of M30 particles after the admixture of FAu-NPs. The immediate coating by NOM is likely to result in FAuNPstabilization. In the original mixing sequence, the elevated ionicstrength caused the NOM to form clusters (Gregory, 2006). This

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Fig. 4. The effect of the SRNOM on different FAuNPs undergoing fast aggregation byaddition of NaCl (0.1 M NaCl for C30 and C100, 0.2 M NaCl for M30). The error barsrepresent the standard deviation of triplicate measurements.

J. Liu et al. / Chemosphere 87 (2012) 918–924 923

elevated ionic strength might also result in a prior destabilizationof the particles after FAuNPs was introduced. Hence NOM have lit-tle chance to stabilize the particles against aggregation.

The observed behavior of different FENPs with NOM has con-firmed the important influence of the type of bonding betweenthe capping agent and the FENPs and that the addition of NOMdoes not always stabilize the particles against aggregation.

4. Conclusions

The presented study reveals the importance of the surface func-tionalization for the aggregation behavior of functionalized gold

nanoparticles. The results show that both of the physical andchemical properties of the capping agents significantly influencethe FENPs aggregation behavior. The interaction of NOM at ele-vated monovalent cation concentration bears implications for thebehavior of these particles in natural waters. Understanding theinfluence of pH, ionic strength, and NOM is essential for predictingthe stability and fate of FENPs and exposure modeling.

It was possible to show unambiguously that with well-definedsurface functionalization the pH dependent surface charge, whichdetermines the electrostatic repulsion, can be accessed quite easilyvia the pKa of the carboxyl groups. The protonation/deprotonationshould therefore be accessible by chemical speciation modeling.This will require, however, information about the surface densityof the functional groups and a correction for the effect of surface-interaction on the pKa values of individual groups to produce accu-rate results: a clear task for future investigations. Even though bothparameters are not easily assessed, these types of particles are stillless challenging than metal oxide particles with a wide variation ofsurface hydroxyl group’s reactivity. Fresh water typically contains0.1–2 mM NaCl and 0.05–30 mg L�1 NOM, at a pH between 4 and 8(Hiraide et al., 1987; Appelo and Postma, 2005). The citrate coatedparticles would be stable in most fresh waters and hence be rela-tively mobile. In contrast, the particles coated with 11-mercap-toundecanoic acid are likely to aggregate in waters with a lowpH. When the particles are released into waters with NOM-richand high NaCl concentration (e.g. in waste water treatment thatcorrespond to the sample sequence used in this study), the aggre-gation of particles coated with 11-mercaptoundecanoic acid wouldnot be retarded regardless of the NOM concentration. However, fora release to waters with NOM-rich but low NaCl concentration (e.g.in some river water that correspond to the sample sequence usedin Stankus et al.), both particle types tested might be overcoatedor the coating might be replaced by NOM. This implies that evenat a dramatic increased NaCl concentration aggregation is unlikelyto take place and mobility will be increased. Future work needs toinvestigate the effects of divalent cations on aggregation kinetics ofdifferent FENPs for further understanding the behavior of FENPs indifferent aquatic environments.

Acknowledgements

The authors would like to thank the European Chemical Indus-try Council (Cefic) for their financial support within the projectentitled Detection, Fate and Uptake of Engineered Nanoparticles inAquatic Systems.

The authors are also grateful to the China Scholarship Counciland the University of Vienna for the scholarship provided to Junf-eng Liu.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.chemosphere.2012.01.045.

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