Sorption of Silver Nanoparticles to Environmental and Model Surfaces

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Sorption of Silver Nanoparticles to Environmental and Model Surfaces Priya Mary Abraham, Sandra Barnikol, Thomas Baumann, Melanie Kuehn, Natalia P. Ivleva, and Gabriele E. Schaumann Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es303941e • Publication Date (Web): 26 Apr 2013 Downloaded from http://pubs.acs.org on April 28, 2013

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Environmental Science & Technology

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Sorption of Silver Nanoparticles to Environmental

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and Model Surfaces

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Priya M. Abraham,1 Sandra Barnikol,1 Thomas Baumann,2 Melanie Kuehn,2 Natalia P. Ivleva,2

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and Gabriele E. Schaumann*1 1

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University of Koblenz-Landau, Institute of Environmental Sciences, Dept. Environmental and Soil Chemistry, Landau, Germany

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2

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*Corresponding author: [email protected]

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ABSTRACT

Technische Universität München, Institute of Hydrochemistry, Munich, Germany

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The fate of engineered nanoparticles in environmental systems is controlled by changes in

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colloidal stability and their interaction with different environmental surfaces. Little is known

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about nanoparticle-surface interactions on the basis of sorption isotherms under quasi-equilibrium

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conditions, although sorption isotherms are a valuable means of studying sorbate-sorbent

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interactions. We tested the extent to which the sorption of engineered silver nanoparticles (nAg)

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from stable and unstable suspensions to model (sorbents with specific chemical functional

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groups) and environmental (plant leaves and sand) surfaces can be described by classical sorption

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isotherms. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) qualitative

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and quantitative analyses were also used to assess the morphology and nanomechanical

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parameters of the covered surfaces. The sorption of nAg from stable suspensions was non-linear

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and best described by the Langmuir isotherm. Langmuir coefficients varied with sorbent surface

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chemistry. For nAg sorption from an unstable suspension, the sorption isotherms did not follow

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any classical sorption models, suggesting interplay between aggregation and sorption. The

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validity of the Langmuir isotherm suggests monolayer sorption, which can be explained by the

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blocking effect due to electrostatic repulsion of individual nanoparticles. In unstable suspensions,

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aggregates are instead formed in suspension, formed on the surface and then sorbed, or formed in

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both ways.

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INTRODUCTION

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Engineered inorganic nanoparticles (EINP) are vital candidates for diverse novel and potential

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applications through their unique antimicrobial, electronic, optical and structural strength

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enhancement properties.1 EINPs are intentionally produced particles with at least one

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dimensional limit of 1 to 100 nm and which display special properties that differ from bulk

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material with the same chemical composition.2,3 Silver nanoparticles (nAg) display antimicrobial

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properties,4 leading to their use in fabrics, paints, personal care products, water filters, and other

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products.5-7 Estimated global production of nAg is 500 tons per year and environmental

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concentration of nAg in soil and in water were predicted as 0.02 µg/kg and 0.03 µg/L,

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respectively.8 Hence there is a chance of nAg entering wastewater streams and other aquatic

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environmental systems.9 There are also studies highlighting the mobility of nAg via food

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chains.10,11 Thus, a significant amount of the nAg entering the environment is also expected to

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reach organisms. Despite potential adverse effects there is still a lack of knowledge and it

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remains imperative to improve our current understanding of their environmental risk, transport

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and fate.12

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In aquatic environments and aquatic-terrestrial transition zones, the fate of EINPs is mainly


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determined by the nature of particle itself, hydrodynamic conditions, and the interaction of these

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particles with environmental surfaces such as leaves, organisms, and natural colloids.13-15 EINPs

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can be immobilized via attachment to sessile environmental surfaces or sedimentation following

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homo- and heteroaggregation.16,17 They can also undergo chemical transformations such as

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oxidation, reduction, partial dissolution, hydrolysis, and biological degradation.13

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To date, interactions between EINPs and surfaces have been investigated mainly in the context of

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nanoparticle transport in porous media using column experiments.18-21 Another approach involves

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investigating nanoparticle deposition kinetics using a quartz crystal microbalance.22-24 Column

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scale experiments give indirect access to information such as attachment efficiency, deposition

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kinetics, aggregation kinetics, and the retention of nanoparticles.13 In these studies, silica gel

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(bare and coated with humic acid), glass beads (hydrophobic and hydrophilic), sand, and soil

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were used as sorbents.13 It is known from experiments using non-invasive imaging techniques,

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that any heterogeneity of the sample translates into a change of the apparent sorption of filtration

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parameters.25 Thus, the parameters derived from those experiments are likely ambigious.

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Surface chemistry also plays a significant role in nanoparticle attachment.26 However, very few

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systematic studies9,27,28 focus on the dependence of EINPs on the chemistry of the collector

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surface. Further studies focus on the sorption of molecules29 and metal ions30 to nanoparticles,

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describing the sorption using a Langmuir isotherm. Kinetic studies are available on the dynamic

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aspects of nanoparticle deposition based, for example, on the random sequential adsorption

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(RSA) model.31 However, studies on the adsorption of nanoparticles to surfaces under quasi-

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equilibrium conditions are less frequently referenced in literature.32 In a study investigating the

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Langmuir sorption of CdSe/ZnS quantum dots to model substrate, Park et al. expressed the need



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of future studies to assess the universality of this phenomenon.26

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Interaction forces governing nanoparticle deposition and aggregation have been described by the

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DLVO (Derjaguin, Landau,Verwey, and Overbeek) theory of colloidal stability.13,33 In the current

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DLVO and extended DLVO conception, only van der Waals interactions are considered and a

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further extension of interaction theory includes the Lifshitz theory to account for Lewis acid-base

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interactions.34,35 Based on these models we can assume that under comparable electrostatic

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situations and in stable suspensions, nanoparticle-surface interactions are controlled mainly by

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their ability to interact via each intermolecular interaction type. A new model for colloid transport

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eliminates the empirical concept of the attachment efficiency by splitting the colloid population

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into with different physico-chemical characteristics and therefore different sticking efficiency. 36

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This model, while ad hoc applicable to heterogeneous environmental particles, could benefit from

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a mechanistic description of the interaction between colloids and surfaces as presented in this

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study.

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The analog in the interaction between organic chemicals and surfaces are polyparameter linear

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free energy relationship (pp-LFER) or linear solvation energy relationship (LSER) models,37

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which describe the partitioning of neutral chemicals between two phases by considering the

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energy contributions of the most important intermolecular interactions.38,39 Although

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nanoparticle-surface interactions are also subject to additional influences like electrostatic

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repulsion, electrostatic attraction, or steric repulsion – which are not yet directly integrated into

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the LFER model40 – we expect that attractive interactions between nanoparticles and surfaces

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beyond electrostatic interactions will follow comparable patterns to those expected for

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intermolecular interactions.


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The objective of this study was to assess whether the interaction of nanoparticles with surfaces

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can be described by classical sorption models and to what extent it depends on and varies with

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suspension stability. For this we investigated the attachment of nAg from stable and unstable

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suspensions to model surfaces undergoing well-defined chemical interactions39, and

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environmental surfaces (glass beads, silica gel, quartz sand, leaf discs) from stable suspensions.

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The presence of nanoparticles on the sorbent surface was detected directly using adhesion-force

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measurements from AFM analyses. This technique is proposed as a tool to quantify the effective

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surface accessible to nanoparticles.

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MATERIALS & METHODS

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Preparation of the nAg suspension. The nAg powder was purchased from io-li-tec (Ionic

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Liquid Technologies, Germany). They were produced using plasma-chemical vapor deposition

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(CVD). According to the manufacturer, their primary particle size was 35 nm. An aqueous

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nanoparticle suspension was prepared by following a standard protocol for preparing nanoparticle

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suspensions from dry powder using an ultrasonic processor without a stabilizing agent.41

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Characterization of nAg. To confirm the existence of surface plasmon resonance, we recorded

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the UV/Vis spectrum of the nAg suspension using a SPECORD 50 device (Analytic Jena,

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Germany). To obtain nAg size information, dynamic light scattering (DLS, Beckman Coulter-

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Delsa Nano C, USA), AFM (Veeco Nanoscope V) and Transmission electron microscope (TEM,

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LEO 922 OMEGA) were employed. Samples for size and morphology analyses by AFM, were

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prepared by dipping a leaf disc of Ficus benjamina (see below) into a nanoparticle suspension

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and drying it overnight in a laminar flow cabinet (Spectec, Germany). Tapping-mode AFM

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images were taken using phosphorus-doped silicon probes with a force constant of 5 N/m and



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125-169 kHz tapping frequency. TEM samples were prepared on a carbon coated copper grid by

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spraying the suspension using ultrasonic atomizer. To determine the fraction of dissolved Ag ions

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in a suspension, it was filtered using centrifugal ultrafiltration tubes with a 10 nm cut-off, as the

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particle size distribution did not show any particles smaller than 10 nm. Ag in filtered and

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unfiltered suspensions was determined using inductively coupled plasma-quadrupol mass

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spectroscopy (ICP-MS, Thermo Fisher Scientific, Germany) after digesting the nAg with 5%

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HNO3 for 24 hours, agitated at room temperature.41 Our preliminary experiments showed that

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yields from this standard method differ by less than 0.5% from those of digestion methods with

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higher HNO3 concentrations and with microwave extraction. To get information about the surface

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chemistry of nanoparticles, energy-dispersive X-ray (EDX, Bruker AXS Microanalysis,

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Germany) and surface-enhanced Raman spectroscopy (Horiba LabRAM HR Raman microscope,

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Japan) were used. For EDX measurements, samples were prepared by air drying 10 µL of nAg

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suspension on aluminum discs. For Raman spectroscopy, samples were prepared by air drying

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10 µL of nAg suspension on a silicon wafer. We used a He-Ne excitation laser (λo = 632.8 nm,

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power = 35 mW) to acquire Raman spectra. Wavelength calibration was accomplished using the

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first-order phonon band of pure silicon at 520 cm-1 and by zero-order correction of the grating

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used through a 50x magnification objective. Raman spectra of nanoparticles were recorded within

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an exposure time of 1 second, through a 100x magnification objective.

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Model surfaces for sorption studies. Following an idea of Tuelp and co-workers39, who used

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column packing materials for HPLC systems to determine the LSER parameters for complex

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pesticides and pharmaceuticals, we worked with the following materials from YMC Europe

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GmbH: YMC*Gel Pro C18 RS (octadecane (C18) functional group), YMC*Gel Phenyl (phenyl

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(Ph) functional group), YMC*Gel Cyano (cyano (CN) functional group), and YMC*Gel Diol


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(diol (OH) functional group). In addition to these HPLC packing materials, we used silica gel

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(Carl Roth GmbH) and glass beads as model surfaces, and as simple representants of

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environmental surfaces with surface chemistry similar to that of the model materials, we used

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sand and leaf discs (Ficus benjamina, family: Moraceae). Five leaf discs with a diameter of 4 mm

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were used for the experiment. The surface areas of all surfaces were measured using BET

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(Autosorb 1-MP (Quantachrom), USA) by nitrogen physisorption. The surface charge was

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measured using a particle charge detector (PCD 02 Mütek, Germany). Sorbents were dispersed in

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water and titrated using an anionic polyelectrolyte (polydiallyl-dimethylammonium chloride,

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0.1 mmol L-1), in an automatic titrator and the isoelectric point was detected via a PCD. The

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surface charge (Qc) was evaluated from the amount of polyelectrolyte used until zero charge as

Qc =

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V c w

(1)

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where V is the volume of polyelectrolyte added (L), c is the charge of polyelectrolyte (molcL-1),

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and w is the sample amount (Kg). Table S1 (SI) shows the characteristic parameters of the

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sorbents.

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Sorption experiments were carried out by adding specific amounts of sorbents to nAg

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suspensions and agitating them at a speed of 15 rpm for 14 hours in an overhead shaker at 19°C.

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This duration was identified as sufficient for equilibrium conditions in preliminary experiments.

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Eight different initial concentrations of nAg, ranging from 0 to 40 µg/L, were prepared for the

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sorption experiments. Higher nAg concentrations were avoided to prevent homoaggregation of

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the particles.42 After agitation, the surfaces were separated by centrifugation using a speed of

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1985 g (3500 rpm) for 20 min, which is low enough to avoid sedimentation of nanoparticles in

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the size range relevant for this study.43 Concentrations of Ag in suspensions before and after



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sorption were measured using ICP-MS. In order to test, to which extent sorption of dissolved

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silver ions may contribute to the overall sorption, additional sorption experiments were done with

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a Ag+ solution, obtained by centrifugal filtration of a nAg suspension with a filter cut-off of

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10 nm as we aimed to evaluate the behavior of the Ag+ ions in exactly the same environment as

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the nAg particles and there was no indication of particles smaller than 10 nm in any of our

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measurements (see below). Glass beads and silica gel surfaces before and after sorption were

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analyzed using the peak force quantitative nanomechanical mapping (PFQNM) AFM-based

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method with antimony-doped silicon probes. AFM analysis was carried out using the PFQNM

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method to measure the adhesion force between the tip and the sample and to see if there is a

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difference in forces before and after sorption. After the sorption experiments, glass-bead and

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silica-gel sorbents were dried overnight in a laminar flow cabinet. Samples for AFM

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measurements were then prepared by fixing the sorbents on a glass slide using double-sided

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adhesive tape. The probe was calibrated prior to measurement; the tip radius was 5.18 nm and the

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spring constant was 17.68 N/m. To compare the adhesion force between the tip and the surface,

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adhesion forces corresponding to 262144 data points were taken from each image. After the

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sorption experients, the leaf discs were analyzed using SEM (FEI Quanta, USA) in low vacuum

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mode with back-scattered detector.

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RESULTS AND DISCUSSION

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Characterization of nAg. The suspension was characterized for size and morphology by TEM

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and AFM (Figure 1). The AFM image indicates the presence of nanoparticles with sizes ranging

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from 40 nm to 170 nm. The phase image confirms the presence of nanoparticles, characterizing

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nAg with a higher phase value (20°) than leaf surface (0°), thus indicating that Ag nanoparticles


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are harder than leaf surface.

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Figure 1 shows two representative TEM images of the nAg particles. In total, 6 TEM images with

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32 particles were analysed with the following result: Particle sizes range from 13 nm to 160 nm

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and consist of 50 % aggregates (> 50 nm), 38% spherical primary particles (size ~ 40 ± 10 nm) as

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well as small spherical particles in the size of 13-20 nm (12%). This corresponds to estimated

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mass percentages of 9.9 %, 89.9 % and 0.2 % of primary particles, aggregates and small particles,

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respecitvely.

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UV/Vis absorption spectroscopy measurement displays a surface plasmon peak at a wavelength

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of 413 nm (SI Figure S1). For metal nanoparticles, the absorption maxima is controlled by the

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size, shape, and environment of particles and hence UV/Vis spectroscopy can be used as a

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complementary tool for structural and size characterization of nanoparticles in suspension.44,45

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Previous studies report that a wavelength maximum (λmax) around 420 nm corresponds to a

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particle size range of 35-60 nm.46,47 The measured peak maximum at 413 nm inidicates that the

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nanoparticles in this study are on the smaller end of the reported sizes, which corresponds to the

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specification of the manufacturer, and our AFM and TEM measurements (Figure 1). The peak is

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rather broad (full width at half maximum, FWHM = 156.75 nm) indicating polydispersity and

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homoaggregation.48,49 There is a small shoulder peak at around 680 nm which can be attributed to

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nonspherical particles, indicating that some nanoparticles in the suspension are ellipsoid.50 DLS

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studies indicated an average hydrodynamic diameter of 105.6 ± 5.2 nm (SI Figure S2), which

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also supports the presence of homoaggregates in the suspension. To test suspension stability for

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the planned sorption experiment duration, we conducted a time-dependent DLS measurement for

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20 hours. During this time, the average diameter varied between 100 nm and 120 nm, with a non-

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significant but slightly decreasing trend (SI figure S3). The suspension was thus regarded as 9 ACS Paragon Plus Environment


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stable for the sorption experiment durations (14 hours). The zeta potential of the suspension was -

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44.31 mV and the pH was 6.4. In the stock nAg suspension, 7.6% of the Ag passed through a

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filter with a cut-off of 10 nm (3000 Da) via centrifugal filtration and thus was regarded as

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dissolved Ag+ as there was no indication of particles smaller than 10 nm in any of our

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measurements. Dissolution studies of bare nAg with a primary particle size of 82 nm showed a

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3% release of silver ions in natural surface water,51 which is lower than the presented result.

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However, the silver-ion release rate depends on primary particle size (smaller size favors faster

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release), concentration, and environmental factors.52 Size information from UV/Vis, DLS, and

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AFM thus correspond within the error ranges.

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In order to analyze potential surface coatings of the silver nanoparticles SEM-EDX

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measurements were performed on nanoparticle aggregates (Figure S4) In addition to silver, the

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EDX analysis revealed a significant carbon signal (Figure S4B). Since the substrate also

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contributes to the EDX signal, further characterisation was performed with Raman

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microspectrometry. Raman spectra obtained from nanoparticles prepared on silicon wafers

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showed two small peaks at around 1350 cm-1 and 1580 cm-1 (SI Figure S5A) in addition to the

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characteristic peaks for bare silicon wafers (Figure S5B). These bands corresponds to D and G

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oscillations characteristic of carbon53 and are known to represent carbonaceous materials like

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graphite, soot, and carbon nanotubes.54,55 Hence, the results indicate the presence of carbon on

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the nanoparticle surface, which may be a by-product of CVD synthesis.56 No other capping

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agents were detected on silver nanoparticle surface.

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Figure 1

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Batch sorption study. Figure 2A shows an example of a sorption isotherm of nAg, in this case

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for diol-functionalized surface. The shape of the sorption isotherms is qualitatively representative

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for all surfaces except leaf. Sorption isotherms for the nAg sorption to all other surfaces are

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shown in the supporting information (SI Figure S6). To rule out the effect and contribution of

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silver ions in the suspension on sorption behavior, we repeated the sorption experiment with an

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Ag+ solution filtered from nAg suspension. Figure 2B shows an example of the difference in the

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sorption behavior of a nAg suspension and an Ag+ solution, in this case for sorption onto diol-

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functionalized surface. For all other sorbents, see the supporting information (SI Figure S7). The

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results clearly show that the sorption of Ag+ is negligible compared with a nAg suspension.

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Figure 2

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To operationally describe sorption data and with the objective of deriving quantitative sorption

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parameters and testing their suitability, we tested to what extent classical sorption models can

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describe the attachment of nAg to the respective surfaces. We therefore tested linear sorption as

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well as Freundlich and Langmuir sorption isotherms:

Q=

K L Q max c 1+ KL c

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Langmuir equation:

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Freundlich equation:

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Q is the relative coverage, KL is the Langmuir coefficient, KF is the Freundlich coefficient, c is

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the concentration of sorbate in aqueous phase, Qmax is the maximum amount adsorbed onto the

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sorbent, which for Langmuir adsorption would correspond to a monolayer, and n is the

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Freundlich exponent, which approaches 1 for linear sorption.

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Figure 3 shows the sorption isotherm of nAg to the leaf discs. Here sorption is approximately

Q = KF c

(2)

n


(3)

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linear. This can be explained by the hydrophobic wax film on leaf surface57 which comprises

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aliphatic carbon chains. A comparable model is an octadecane-functionalized surface for which

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the Freundlich exponent displays a linear behavior. For leaf discs, linear sorption gives the slope

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as 3.26 L/g which is comparable to the slope for the near-linear sorption isotherm for nAg

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sorption to octadecane-functionalized sorbents (3.51 L/g). SEM image of leaf disc after nAg

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sorption show aggregates in some specific regions (SI Figure S8) that may be due to drying

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effect,58 which would again underline the relatively low interactions between nanoparticles and

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surfaces, enabling their movement with the drying water front. Another explanation may be self

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assembly of nanoparticles driven by structural or constitutional features on certain areas of the

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leaf,59 or the formation of other colloids, e.g. silver chloride, on leaf surfaces since there can be

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chloride ions on the surface.60

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Figure 3

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Comparison of sorption models. The model assumptions in both isotherms differ significantly,

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reflecting different sorption mechanisms. The Freundlich isotherm was deduced under the

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assumption that sorption enthalpy is distributed heterogeneously on sorbent surfaces and

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increases with surface coverage. The Freundlich exponent can be described as an index of

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diversity of free energies associated with the sorption of nanoparticles to heterogeneous sorption

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sites on sorbents.61 The Freundlich isotherm formally allows infinite coverage and thus unlimited

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sorption capacity.62 In contrast, Langmuir adsorption is based on the assumption that adsorption

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takes place on fixed homogeneous adsorption sites of equal energy, forming a monolayer surface

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coverage.63 Both isotherms indicate that sorption becomes less favorable as sorbate

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concentrations increase, either due to the completion of a monolayer (Langmuir) or the


1 2

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occupation of sites with increasingly lower sorption enthalpy.61

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Both sorption models describe experimental sorption with comparable fitting quality as

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demonstrated in Table S3 (SI) by the regression coefficient (R2) and degree of freedom (Chi2).

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Statistically, it is unclear which sorption model is more reasonable. Also, systematic deviations

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between the data and modeled isotherms were comparable for both models. Thus, as with many

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sorption isotherms of organic chemicals to NOM,63,64 the fitting quality does not allow the

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attribution of a Langmuir or Freundlich mechanism. Available sorption studies in the literature

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describe the sorption of silver nanoparticles to barium sulfate microparticle surface by Freundlich

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adsorption model32 and the sorption of CdSe/ZnS quantum dots to model substrates by Langmuir

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sorption model.26

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The Freundlich coefficients (KF) range from 8.4 (µg(1-n)Ln)/g to 19.5 (µg(1-n)Ln)/g (Table S3), and

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the Freundlich exponents n indicate a wide range of sorption curvature, ranging from near-linear

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sorption (n = 0.96 ± 0.15) to strongly non-linear sorption up to n = 0.53 ± 0.04 (Table S3). KF and

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n vary in the order (Figures 4A and 4B):

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K F:

Diol > Glass > Silica gel > Cyano > Sand > Phenyl > Octadecane

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n:

Octadecane > Phenyl > Cyano > Silica gel > Sand > Glass > Diol

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From a chemical point of view, linearity would be expected for the lowest specific interactions

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between nanoparticles and the surface, and non-linearity is expected to increase with increasing

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binding strength and specificity65,66 or surface heterogeneity.61 Assuming the least specific

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interactions for the alkyl and the phenyl surfaces and strongest ones for the most polar surfaces, it

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is in line with these prerequisites. Variation of KF also follows this assumption by showing higher

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values for more polar diol-functionalized surfaces and lower values for the nonpolar octadecane-


1 3


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and phenyl-functionalized surfaces. However the sorption data are related to the mass of the

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sorbent and all sorbents are expected to have a specific, but unknown, sorption capacity.

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Therefore, KF as determined in this study cannot be used to obtain parameters describing

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nanoparticle-surface interactions unless the sorption capacity is known.

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Assuming Langmuir-type sorption resulted in Langmuir coefficients ranging from close to zero

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(KL = 0.02 ± 0.06) L/g for the octadecane-functionalized surface up to (KL = 0.6 ± 0.1) L/g for the

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diol-functionalized surface. The parameters for maximum loading, Qmax range from

292

54.8 ± 4.0 µg/g to 526.4 ± 1757.5 µg/g. Qmax, however, shows large errors for sorption to

293

octadecane- and phenyl-functionalized surfaces. This uncertainty is due to the still weak

294

curvature of the sorption isotherms (Figure 5A). As shown in Figure 4C and 4D, KL and Qmax

295

vary in the order:

296

KL:

Diol > Glass > Sand > Silica gel > Cyano > Phenyl > Octadecane

297

Qmax:

Octadecane > Phenyl > Cyano > Silica gel > Glass > Sand > Diol

298

Figure 4

299

Assuming a Langmuir type interaction, Qmax indicates the effective surface coverable by the

300

nanoparticles, which is usually unknown and hard to describe. As expected, Qmax did not correlate

301

with the BET surface area (SI Figure S9A). The functionalized surfaces in particular display only

302

slight differences in BET surface area (SI Table S1) coinciding with significant changes in Qmax

303

values (SI Table S3). This supports the assumption that BET surface area is not suitable as a

304

descriptor of sorption capacity. It may be because a significant part of the BET surface area is

305

located in pores not accessible by nanoparticles, or caused by nanoscale surface roughness. The

306

additional lack of correlation between Qmax and sorbent surface roughness measured using AFM


1 4

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307

(SI Figure S9A) suggests that nanoscale surface roughness does not increase the effective space

308

available for nanoparticle attachment which makes sense if the length scale of the surface

309

roughness is smaller than the length scale of the particles. There was no correlation between

310

sorbent surface charge and Qmax (data not shown), at least for the sorbents where we were able to

311

measure the surface charge. This indicates that electrostatic forces did not play a major role in the

312

sorption of nAg to the surfaces used in this study. An attempt to connect Qmax to the apparent

313

geometrical surface area by considering the sorbents as spheres with smooth surfaces also failed.

314

For example, Cyano-, phenyl-, and octadecane-functionalised surfaces (particle size 3 µm), have

315

the same geometrical surface area (0.8 m2 g-1) but their Qmax varies by a factor of up to 5 (Table

316

S3). Considering a debye radius of 1 µm around the 100 nm large particles, would lead to an

317

occupied surface area of 1.5-7.5 cm2 g-1, which would indicate an effective coverage of 2-11 % of

318

the geometric surface area. This suggests that only part of the sorbent surface is involved in the

319

nAg-surface interaction observed in our study. This result nicely fits into the concept of

320

attachment in non-uniform media under unfavorable conditions.67,68 Thus, an independent

321

approach to estimate the effectively coverable surface of the sorbents still needs to be developed

322

and also needs to consider morphological heterogeneity of the sorbent surface.

323

Maximum particle coverage can also be estimated by extrapolating the particle deposition

324

kinetics to infinite time.69-71 Most of these studies use optical microscope and height information

325

from AFM to study particle coverage on flat sorbent surfaces. This approach does not seem

326

useful for real environmental systems because the surfaces display significant surface roughness

327

on the order of a few nanometers. Below, we will discuss the suitability of using adhesion-force

328

information from AFM to determine the effective surface area. Only with this information can the

329

assumption of Langmuir sorption mechanisms ultimately be validated. Nevertheless, the


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330

Langmuir model allows the interaction parameter KL and the capacity parameter Qmax to be

331

separated. Therefore, we will keep to the Langmuir model when discussing specific interaction

332

parameters, keeping in mind that the mechanism needs further validation.

333

Variation in the KL value for different sorbents can be explained by their ability to undergo

334

particular intermolecular interactions. Nonpolar sorbents (i.e. octadecane- and phenyl-

335

functionalized sorbents) displayed the lowest KL value and sorbents with polar groups undergoing

336

H-donor/acceptor interactions displayed the highest KL value. This is in line with expectations

337

regarding intermolecular interaction51 under the assumption that nAg particles can undergo some

338

H-donor/acceptor interactions. This may be due to the presence of carbonaceous or organic

339

material in the nanoparticle surfaces as suggested from our Raman and EDX measurements.

340

Furthermore, it has been reported, using SERS (surface-enhanced Raman scattering) and by a

341

DFT (density functional theory) study of water on metal cathode of silver nanoparticles, that

342

water molecules exist on the metal cathode with HO-H---Ag hydrogen bonding interactions.72

343

This confirms that even bare nAg particles can undergo some H-acceptor interactions.

344

Figure 5 shows sorption data normalized to Qmax together with a fitted Langmuir isotherm. It is

345

clear that with more polar diol-functionalized surfaces, more silver is adsorbed (79%) and with

346

less polar sorbents, e.g. octadecane-functionalized (8%) and phenyl-functionalized (20%)

347

surfaces, it is comparably less.

348

Figure 5

349

Thus, although fitting quality is comparable for the Langmuir and Freundlich models, the

350

application of the Langmuir model allows the direct separation of the effect of limited surface

351

coverage and the effect of nanoparticle-surface interactions, each into a single sorption


1 6

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352

parameter. As long as sorption is ongoing from a stable suspension, the assumption of a

353

monolayer sorption is also reasonable as nanoparticle-nanoparticle interactions are effectively

354

repulsive, inducing a blocking effect. This situation changes completely when investigating

355

attachment to the same surface from less stable suspensions as demonstrated by a specific study

356

in which the sorption of silver nanoparticles from unstable suspensions was investigated

357

(hydrodynamic diameter growth rate: 14.3 nm/h, SI Figure S10). Here, sorption isotherms for all

358

the sorbents were random points and did not follow any models (SI figure S11) indicating that

359

nanoparticle-nanoparticle interactions outweigh nanoparticle-surface interactions.

360

Determination of the surface coverage in AFM images of µm-scale sections of sorbents.

361

Glass-bead and silica-gel surfaces before and after sorption with nanoparticles were analyzed

362

using AFM. The chemically functionalized sorbent surfaces were not investigated due to the

363

smaller grain size and difficulty in fixing them to a flat surface. Height images do not provide any

364

information about the sorbed nanoparticles due to high surface roughness and sharp edges on the

365

sorbents (SI Figure S12). However, the adhesion-force images obtained using PFQNM show

366

clear differences between covered and uncovered surfaces (SI Figure S13 and S14). Adhesion-

367

force values give information about the surface properties of the sample, including both chemical

368

and material properties in nanometer scale.73 As such, adhesion-force images can be used to

369

explain changes in the material properties of a sample in nanometer resolution. The frequency

370

distribution graph of adhesion force for uncovered glass beads and silica gel (black bars in Figure

371

6A and 6B) indicates adhesion forces ranging between 30 and 70 nN for glass-bead surfaces and

372

between -10 and 30 nN for silica surfaces. Due to nAg attachment, an increase in the number of

373

data points with adhesion forces between 30 to 90 nN was observed for both surfaces. This range

374

of adhesion forces was attributed to the presence of nAg on the surface. We suggest determining


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Page 18 of 32

375

surface coverage by quantifying the increase in the percentage of data points in this force region.

376

As the total area in the AFM image always has same total number of data points, the increase in

377

this force region should correspond to nAg coverage. We found that the frequency of data points

378

in this force region increased with measured coverage (data not shown), but as expected, a

379

significantly higher number of images has to be taken and analyzed in order to directly quantify

380

Q via AFM with reasonable certainty. Humidity also has a large effect on adhesion-force

381

measurements,74 hence PFQNM measurements have to be done in a humidity-controlled setup to

382

obtain more quantitative results. Other challenges are the effects of sharp edges on adhesion

383

force. Furthermore, reliability of such data always depends on the heterogeneity of surfaces and

384

their force background pattern. For more heterogeneous surfaces, it may be advisable to combine

385

adhesion-force measurements with other mechanical or material properties.

386

Figure 6

387

In summary, the results show that nanoparticle attachment to sorbents depends on sorbent-sorbate

388

intermolecular interactions that can be analyzed by investigating nanoparticle sorption to a set of

389

model surfaces undergoing well-known interactions under quasi-equilibrium conditions if the

390

suspension is stable. In this case, Langmuir sorption isotherms allow the determination of both a

391

nanoparticle-surface interaction parameter and a maximum surface coverage. The observation

392

that nanoparticle attachment is limited to a maximum coverage could be explained by the

393

blocking effect due to electrostatic repulsion or, as suggested by the low percentage of covered

394

geometric surface, by preferential attachment of the particles to physically or chemically more

395

favorable sites

396

The extension of this sorption study to environmental surfaces showed that nAg sorption to

397

leaves is comparable to sorption to the octadecane surface, and sorption to sand is comparable to


1 8

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398

sorption to glass and silica gel. This can be explained through chemical intermolecular

399

interactions. The observation that environmental surfaces behaved in similar ways to sorbents

400

undergoing comparable intermolecular interactions demonstrates the transferability of our

401

approach to more complex surfaces. The set of Langmuir coefficients further suggests that nAg

402

may undergo H-bond acceptor interactions. This could be due to the binding of some organic

403

compounds to part of the nAg surface.

404

The results of our study thus help to understand particle-surface interactions on the basis of

405

sorption isotherms under quasi-equilibrium conditions and for stable suspensions. This approach

406

will help in assessing the fate of stable nanoparticle suspensions in the environment. To gain a

407

more general understanding about the fate of EINPs in environmental systems, a larger set of

408

stable and unstable suspensions and nanoparticles with different coatings must be investigated.

409

ACKNOWLEDGMENTS

410

This study was supported by the German Ministry for Education, Science and Culture of

411

Rheinland-Pfalz (MBWWK) as part of the Forschungsinitiative RLP, and the German Research

412

Foundation (DFG; Research unit INTERNANO: FOR 1536, project SCHA849/16-1). We thank

413

Dr. S. K. Woche (Institute of Soil Science, Leibnitz Universität, Hannover, Germany) for her

414

help with measurements using PCD. We thank Mr. Mohammad Fotouhi Ardakani (Karlsruher

415

Institut für Technologie, KIT, Karlsruhe, Germany) for the TEM measurements.

416

ASSOCIATED CONTENT

417

Supporting information. Table S1,S2 and Figure S1-S14

418


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Figure captions

Figure 1. TEM image (above) of silver nanoparticles and AFM height, amplitude and phase images (below) of silver nanoparticles on terrestrial leaf surface. The scan area is 1.9 X 1.9 µm Figure 2. Representative sorption isotherm for sorption of silver nanoparticles to diol functionalized sorbent surface (A) and comparison for the sorption of silver ions and silver nanoparticles to diol functionalized sorbent surface (B). Figure 3. Sorption isotherm for the sorption of nAg on to leaf discs of the plant Ficus Benjamina. Figure 4. Freundlich exponents (A), Freundlich coefficients (B), Langmuir coefficient (C) and Langmuir adsorption maxima (D) for the sorption of silver nanoparticles onto the sorbents. Figure 5. Langmuir sorption isotherms of silver nanoparticles on different sorbents. Figure 6. Frequency distribution of adhesion force between the AFM tip and glass bead surface (A) and silica gel surface (B), before and after sorption. 262144 data points in an image were taken to plot the frequency distribution.


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Figure 1. TEM image (above) of silver nanoparticles and AFM height, amplitude and phase images (below) of silver nanoparticles on terrestrial leaf surface. 95x82mm (300 x 300 DPI)


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Figure 2 Representative sorption isotherm for sorption of silver nanoparticles to diol functionalized sorbent surface (A) and comparison for the sorption of silver ions and silver nanoparticles to diol functionalized sorbent surface (B). 264x130mm (150 x 150 DPI)



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Figure 3. Sorption isotherm for the sorption of nAg on to leaf discs of the plant Ficus Benjamina. 84x67mm (300 x 300 DPI)


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Figure 4. Freundlich exponents (A), Freundlich coefficients (B), Langmuir coefficient (C) and Langmuir adsorption maxima for the sorption of silver nanoparticles on to the sorbents. 250x159mm (150 x 150 DPI)



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Figure 5 Langmuir sorption isotherms of silver nanoparticles on different sorbents. 254x174mm (150 x 150 DPI)


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Figure 6. Frequency distribution of adhesion force between the AFM tip and glass bead surface (A) and silica gel surface (B), before and after sorption. 262144 data points in an image were taken to plot the frequency distribution. 240x101mm (150 x 150 DPI)



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TOC Art 173x114mm (150 x 150 DPI)


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Sorption of Silver Nanoparticles to Environmental and Model Surfaces

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