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Deciphering the elementary steps of transport-reaction processes at individual Ag nanoparticles by 3D superlocalization microscopy Anisha N. Patel, Ariadna Martinez-Marrades, Vitor Brasiliense, Dmitry Koshelev, Mondher Besbes, Robert Kuszelewicz, Catherine Combellas, Gilles Tessier, and Frédéric Kanoufi Nano Lett., Just Accepted Manuscript • DOI: 10.1021/acs.nanolett.5b02921 • Publication Date (Web): 01 Sep 2015 Downloaded from http://pubs.acs.org on September 6, 2015

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Deciphering the elementary steps of transportreaction processes at individual Ag nanoparticles by 3D superlocalization microscopy Anisha N. Patel,1 Ariadna Martinez-Marrades,2 Vitor Brasiliense,1 Dmitry Koshelev,2 Mondher Besbes,3 Robert Kuszelewicz,2 Catherine Combellas,1 Gilles Tessier,2,* Frederic Kanoufi1,* 1

Sorbonne Paris Cité, Paris Diderot University, Interfaces, Traitements, Organisation et

Dynamique des Systèmes Laboratory, CNRS-UMR 7086, 15 rue J. A. Baif, 75013 Paris, France 2

Sorbonne Paris Cité, Paris Descartes University, Neurophotonics Laboratory, CNRS UMR

8250, 45 rue des Saints-Pères, 75006 Paris, France 3

Laboratoire Charles Fabry – IOGS, CNRS UMR 8501, 2 rue Austin Fresnel, 91127 Palaiseau

Cedex, France

ABSTRACT

Transport-reaction processes at individual Ag nanoparticles (NPs) are studied using electrochemistry coupled with in situ 3D light scattering microscopy. Electrochemistry is used to trigger a (i) diffusiophoretic transport mode capable of accelerating and preconcentrating NPs towards an electrode, (ii) subsequent diffusion-controlled oxidation of NPs. Individual NP

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dissolution rate, analyzed using optical modeling, suggests the intervention of insoluble products. New insights into diverse NPs behaviors highlight the strength of coupled opticalelectrochemical 3D microscopies for single-NP studies.

KEYWORDS: Single nanoparticles; Diffusiophoresis; Electrodissolution; OptoElectrochemistry; 3D Superlocalization Optical Microscopy.

Due to their high surface-to-volume ratio, the physical and reactive behaviors of nanoobjects are strongly driven by interfacial processes. Even in highly monodisperse populations, monitoring individual nanoparticles (NPs) is essential to understand ensemble properties, since even barely detectable size variations can alter the individual or collaborative properties of the nanoobject.1,2 Electrochemistry at microelectrodes (having at least one dimension of tens of micrometers or less3) or nanoelectrodes (one dimension of tens of nanometers or less3) has the sensitivity required to study the exchange of charge carriers between individual nanoobjects and their local environment. It allows for extremely sensitive studies that can provide a rich analysis of charge transfer at the level of various individual nanoobjects, from NPs of different composition and/or sizes,4-10 to emulsion nanodroplets,11 or in a similar fashion during molecular release (exocytosis) of electroactive species from single cellular nanovesicles.12 The most popular strategy for elucidating individual nanoobject electrochemistry (nano-impact electrochemistry) lies in the monitoring of their reactive landing on a small-sized collector microelectrode. This can be either standardly fabricated3-6 or obtained through the confinement of the electrolyte solution meniscus in an ultramicro-electrochemical cell, such as that employed in the scanning electrochemical cell


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microscopy (SECCM) configuration.8-10 The latter SECCM approach is particularly appealing as the low background electrical signal and high surface-to-volume ratio provides sub-millisecond time-resolution electrochemical inspection, which has very recently indicated that the nanoobject position in the solution (after or before its impact with the electrode) could be indirectly probed.10 However, purely electrochemical methods cannot easily discriminate between individual and ensemble behavior or probe unambiguously the overall reactive trajectory of the nanoobjects; hence, comprehensive visualization is generally required and obtained via coupling nanoelectrochemistry studies to an in situ orthogonal microscopic technique, such as AFM,7,13 transmission electron microscopy,14 or, at lower expense and high throughput, optical microscopies.15-17 Fluorescence,18 dark field (DFM)17,19 and surface plasmon resonance (SPR)15 microscopies have recently been employed to correlate the optical signature of individual nanoobjects to their electrochemical actuation. However, these methods are spatially selective and only 2D as the depth of field is limited to a few microns, and in the case of SPR to tens of nm, whilst real chemical or electrochemical reactions are intrinsically 3D problems where the behavior of the nanoobjects in solution (agglomeration, phoretic transport) has an essential influence on their properties. The 3D electrochemical pathway of redox active species, which also applies to any interfacial phenomenon such as biomolecular detection,20 can be described by 3-elementary steps: i) transport of the species to the electrode surface, ii) adsorption or interaction with the electrode surface, followed by iii) electrochemically driven physical-chemical transformation. The aim of this work is to track the chemical reactive pathway of individual entities in an electrochemical context and analyze each of the above elementary steps. It is provided by superresolution optical microscopy based on localization methods. This concept appeared in the wake


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of single molecule detections,21 and was further developed for fluorescent species by Eric Betzig, one of the 2014 Chemistry Nobel Prize Laureates.22 It was recently extended to light scattering monitoring for various objects, including untagged metallic NPs. In addition to their high scattering cross-section, metallic NPs exhibit coherent scattering, that allows for their interferometric detection and 3D superlocalization, as we have already shown using digital 3

holographic microscopy,23 with accuracies down to 3 x 3 x 10 nm . In particular, 3D localization with full volume inspection allows for the decoupling of surface to volume effects, which is essential in deciphering transport-reaction processes, as very recently suggested for NPs under electrochemical actuation in confined environment. 10,24 Herein, we take advantage of the great sensitivity and resolution of holographic microscopy and 2D dark field microscopy (DFM) to examine, by coupling it to electrochemistry, the transport-reaction contribution to the elementary steps of an electrochemical transformation at the level of individual NPs. This is carried out with 3D nanometer-range accuracy, employing the case example of the oxidation of colloidal Ag NPs, owing to its particular interest in a wide range of applications exploiting their catalytic or antimicrobial activities.25,26 The transport of single Ag NPs of 30 and 50 nm in radius is tracked in 3D as they arrive at the electrode surface, where their oxidation is driven. In addition to providing an estimate of NP size, this tracking reveals a preferential transport mode through diffusiophoresis, where NPs are driven to preconcentrate near the electrode surface. The subsequent dissolution of each NP at the electrode is monitored optically by the change in its individual scattered light intensity, Isc, which is sizedependent. Interestingly, the Ag NPs may not dissolve instantaneously upon arrival at the electrode surface. The dissolution kinetics of individual Ag NP during the electrochemical dissolution process is estimated by optical modeling of Isc and found to be approximately 1 to 2


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orders of magnitude slower than that estimated using electrochemical impact experiments and SPR studies.6,16 The difference is attributed to the intervention of poorly soluble chemical intermediates formed during the oxidation process. Observation of Nanoparticle Events. An illustration highlighting the principle of coupling electrochemistry with holographic imaging is shown in Figure 1, where a laser is used to illuminate the full volume of the sample, retrieving 3D images thanks to an interferometric detection. 2D image analysis can be carried out either by 2D reconstruction of the 3D holographic images, or by using simple 2D DFM with a white light source. With both imaging techniques, the NPs appear as bright features, due to their ability to scatter light illuminating the cell. Although these scattering NPs are imaged as diffraction-limited features (ca. 290 nm) much larger than their actual size, superlocalization is used to identify the center of mass of these diffraction patterns. Superlocalization enables the tracking and monitoring of objects with nanometer resolution. A more detailed description for the two experimental modes (3D holographic microscopy and 2D DFM) is provided in the Supporting Information (SI), S 1. In order to monitor the transport-reaction processes, an electrolyte solution containing 30 nm radius Ag NPs in 0.1 M KNO3 was introduced inside a microfluidic electrochemical cell,19 which was illuminated and imaged above the objective lens of an inverted microscope. The upper surface of the cell comprises of a ca. 7 mm2 Au working electrode, 50 nm thick. A voltammogram was then recorded, Figure 1, whilst optically monitoring the electrode surface. The optical monitoring is provided as movies in the SI (Movies S 1 and S 2 for the DFM and holographic monitoring, respectively). 2D holographic reconstructions (Figure 1) of selected frames from Movie S 3, showing 5 frames over 12.5 seconds, summarizes the different scenarios observed during the electrochemical activation. As the electrode potential, E, is swept from 0 to


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1 V vs Ag/AgCl, the arrival of 6 Ag NPs is observed, 2 of which subsequently disappear. Unlike the case of single electrochemical nano-impact experiments,4-6,8-10,24 the electrode used herein is too large to work as a collector of NP electrochemical events as it produces currents 4 orders of magnitude larger (or more) than that expected for single electrochemical NP impacts (in the pA range). However, the electrode is used to trigger NPs events that are monitored optically such as: NP transport in solution, their adsorption or desorption on the electrode, and as far as the electrodissolution process is concerned, only the NP dissolution step is monitored. By following the change in Isc of individual particles, we are able to extract optical intensity profiles from individual NPs. Similar observations were obtained from a DFM experiment (Movie S 1), and examples of such Isc profiles, as shown in Figure 2a, confirm the different scenarios observed in Figure 1: (i) arrival and sticking of a NP (red), (ii) adsorption and subsequent disappearance of a NP (blue), and (iii) disappearance of a preadsorbed NP (green). These insightful observations reveal behaviors that cannot be detected by single electrochemical nano-impacts experiments. Indeed, it is seen here that the dissolution of Ag NPs may not occur instantaneously upon landing of the NPs on the electrode surface, which cannot be resolved without the use of optical monitoring. Moreover, the different NP events monitored optically can be correlated to the electrode activity. In this respect, the corresponding cyclic voltammogram, CV, representing the activity of the whole macroscopic electrode is overlaid with the optical activity of individual NPs, from which NP events are easily correlated to the applied electrode potential (E). Figures 2b and S 3 summarize such events. The first observation concerns the optical disappearance of Ag NPs from the electrode surface, most likely associated to their individual electrochemical dissolution, or eventually desorption. From Figures 1, 2a and S3, the onset E for Ag NP optical disappearance is Edis > 0.65 V. As expected for an electrochemical process, the


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occurrence of the NP disappearance increases with the electrode potential and, when E > 0.9 V, the optical intensity for more than 70 % of absorbed NPs decays to the background signal within the same potential region, indicative of their dissolution or desorption. Moreover, Figures 2b and S3 show an increase in the number of adsorption events of NPs at the electrode surface commensurate with increasing E (or current). Noteworthy, Figure 2b shows that the landing of NPs on the electrode starts at Eland = 0.6 V, about 0.05 V earlier than the onset potential, Edis, for their disappearance. This suggests that a potential-dependent process is driving the Ag NPs towards the electrode before the NPs electrochemical transformation takes place. A qualitative visualization of such potential-driven mode of transport is analyzed by 2D DFM in Figure 2c. Here we present the distribution for the characteristic time of flight of individual NPs moving in the optical depth of field (d ~1-2 µm) in the electrode vicinity before they leave the electrode region or adsorb onto it. It is evident, for when E < 0.6 V the time of flight of the NPs is ca. 0.7 ± 0.2 s, whereas when the current is flowing at the electrode for E > 0.6 V, the NPs are barely observed for more than 0.4 s and have an average time of flight of 0.22 ± 0.12 s. The shortening of the characteristic time of flight suggests that two different transport mode are involved in the two potential regions. In addition, NPs are twice as more frequently detected when E > 0.6 V (N=14) than when E < 0.6 V (N=6) suggesting that if diffusion is the preferred mode of transport of NPs when E < 0.6 V, when current is flowing at the electrode, an external force is acting on the NPs and propelling them towards the electrode. A quantitative analysis of the different modes of transport encountered herein requires 3D visualization. Holographic imaging allows 3D localization to be carried out with full-volume inspection. It can therefore reveal the mode of transport of the NPs and also differentiate between surface and volume processes. For instance, it was demonstrated from the SECCM monitoring of


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Ag NP electrochemical synthesis that Ag NPs may instantaneously detach from HOPG electrode surfaces. This was concluded based on the much higher number of single electrochemical events compared to the number of ex-situ imaged surface bounded NPs.9 The optical imaging methods proposed here provide an unambiguous in-situ means to confirm these observations, indeed both movie S 1 and the time of flight estimates provided in Figure 2c show that NPs detach readily from the electrode surface without reacting with it. Moreover, 3D imaging can also unambiguously distinguish desorption (which can be tracked in 3D) from electrochemical dissolution, both events which simply lead to optical disappearance in classical 2D DFM imaging. Desorption vs Dissolution. During a dissolution process, the NP decreases in size concomitantly with Isc, with the absence of any detectable particulates released into the solution. Here detectable particulates would correspond, based on the optical method sensitivity to Ag NPs > 5 nm, it is then possible that incomplete NP dissolution followed by NP desorption would not be optically detected. In a desorption process, the particle would clearly detach from the surface and migrate away. 3D localization was achieved to visualize each individual NP and examine its surrounding volume during its Isc decay. Examples of volume reconstructions, corresponding to the frames in Figure 1, are provided in the SI, S 2. The volume reconstructions show a NP arriving at the electrode surface near a preadsorbed NP during the course of the CV cycle, and eventually fading in intensity without releasing any particulates into its surrounding area, thus confirming a dissolution process. The dynamics of this process is analyzed in detail, below, based on the modeled evolution of Isc and of NP size evolution upon dissolution. Transport Analysis. 3D localization is also used to track the trajectory of NPs before their arrival in the vicinity of the electrode surface. Mean-squared displacement (MSD) analysis of


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each NP trajectory was done to obtain their individual mobility, which allows estimation of their apparent hydrodynamic radius (SI, S 4). Such analysis allows an indirect estimation of transport phenomena. In the absence of external force applied to the NPs, a Brownian motion is observed, allowing an estimate of the NP diffusion coefficient, DNP, and hydrodynamic radius, rNP to be made. The significance of particle sizes and electrochemical dissolution dynamics is discussed later on in the text. When the NPs are subjected to an external force, a drift is observed and, as long as the drift is smaller or comparable to the diffusive contribution, a pseudo-Brownian trajectory is obtained from which an apparent diffusion coefficient, DNP,app, or equivalently an apparent NP size, rNP,app, is extracted. This apparent diffusion coefficient (or size) may be smaller (resp. larger size) or larger (resp. smaller size) than the expected value, reflecting the braking or propelling effect of the drift on the NP. In the absence of potential or current control, Figure 3a (blue) shows an example of such an MSD for an individual NP, for which DNP was found to be 6.8 µm2 s-1 and from the StokesEinstein relationship rNP = 32 ± 8 nm (corresponding 3D trajectory in the SI, Figure S4a). Figure 3b summarizes the size distribution of 6 NPs tracked in the absence of potential control (blue). The average radius found for the 3D holographic tracking was within 31 ± 5 nm at 90% confidence. However, the number of particles, which can be tracked in 3D, is limited by the particles concentration (to avoid overlap) and the investigated volume (from which Brownian particles eventually exit). In order to increase the statistical significance of this result, we used 2D conventional dynamic light scattering analysis (DLS) and 2D NP tracking analysis (NanoSight® LM10 microscope) over several hundreds of particles. The Nanosight system illuminates a portion of the sample with a 80 µm diameter oblique laser beam (distance from the


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electrode unknown). It is then able to track NPs over a depth ranging between 10 µm (the depth of field of the objective) for the most stringent tracking thresholds and up to 80 µm (extension of the illuminated region).27 In our case, this depth was estimated to be 50 µm, and the total investigated volume was around 100x80x50 µm3 (a 15 times larger volume than that investigated in 3D, allowing for a larger number of events to be tracked). Each sub-wavelength particle within this investigated volume is imaged as an Airy disc, and 2D tracking algorithms are used to determine their center of mass. In the absence of polarization, this yields a NPs size of 32 ± 0.2 nm (SI, Figure S 5). During electrode polarization, the 3D trajectories of 4 NPs were also tracked in the close vicinity of the electrode, as they traveled towards it and were adsorbed (SI, Figure S 4b). MSD analysis of these trajectories, Figure 3a (red) and b (red), reveals these NPs to have an apparent radius of ca. 17, 19, 21 and 21 nm respectively (average of 20 ± 5 nm at 90% confidence, see estimate in the SI). In addition, 3 other particles, which landed close to the image border (NPs 1, 4 and 5 in Figure 1) only remained shortly within the investigated volume, but travelled over ~ 1 - 2 µm distance between subsequent images (0.025 s), which is consistent with NPs with DNP,app ~ 10 µm2 s-1 or an apparent NP size, rNP,app ~ 20 nm. The 3D visualization of N=7 NPs moving faster, or apparently smaller, under potential control, E > 0.6 V, corroborates the same propelling effect qualitatively explored (for N=14 NPs) in 2D DFM. In order to increase the statistical significance of our 3D description, similar electrochemical experiments with Ag NPs were carried out in a larger microfluidic cell using NanoSight® 2D ensemble tracking analysis. A significant effect on the apparent hydrodynamic diffusion coefficient (therefore equivalently on the apparent size) was observed, as shown in Figure 3b (green). While E < 0.3 V, monodisperse Ag NPs are observed (see SI, Figure S 6), with a


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distribution identical to that obtained in the absence of polarization (rNP ~ 32 ± 0.2 nm). When the electrode potential was swept between ca. 0.3 to 0.9 V, an electrical current was measured at the electrode (see SI, Figure S 6) while NP trajectories were accumulated to provide a sufficiently large number of NPs trajectories (Figure S6 and Figure 3b). Mainly, two separate apparent size distributions were then observed, with a mean of 17.5 and 32.5 nm, with a much higher number of events (N > 200) provided by the long acquisition time and the large investigated volume. Indeed, while the 3D volume used for holographic tracking was deliberately chosen within 15 µm from the electrode surface, the 2D Nanosight system tracks particles in a 15 times larger volume (3 times deeper along z). Moreover, to avoid camera saturation and maximize tracking accuracy, the direct observation of the illuminated electrodeelectrolyte interface must be avoided: the observation was set on a region of the illuminated solution at farther distances (ca. z > 50 µm) from the electrode. During a cyclic voltammetric experiment performed at v = 0.01 V s-1, electrogenerated molecular species can be transported from the electrode upon a diffusion distance d ~ (DRT/Fv)1/2 ~ 50 µm (for D = 10-5 cm2 s-1). The region investigated by Nanosight® then extends both within and outside the electrochemical diffusion layer, suggesting that the presence of two populations of NPs in the Nanosight® measurements result from the difference in the investigated region. It should be noted that this discrimination upon the investigated region is consistent with the discrimination of NPs populations based on electrode potential (or time) observed in Figure 2c. The two NPs populations probed by the Nanosight® microscope at farther distances from the electrode and the exclusive presence of particles with a smaller apparent hydrodynamic radius in the vicinity of the electrode during flowing current probed by 2D DFM and 3D holography allow us to ascribe their higher mobility to the vicinity of the surface. We attribute this difference to the effect of a drift


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of the NPs during potential control, propelling them towards the electrode surface. It also explains, as expanded on below, the increase in the number of NPs arriving at the Au surface with E > 0.6 V, as highlighted in Figure 2b and c. Origin of NP drift under electrode potential. The 3D MSD analysis of the apparent rNP,app = 20 nm NPs was carried out taking into account the above hypothesis of NP drift and a fixed apparent NP size of rNP = 30 nm, which produced an apparent NP velocity (vNP) of ca. 8 µm s-1. The effect of the electrode potential on NP attraction and directed movement was recently proposed in studies from the groups of Bard,24 Crooks,28 or Unwin.10 The former two attributed their observation to the electrophoretically-driven motion of NPs, whereas the latter proposed the catalytic generation of O2 bubbles localized at one end of a ruthenium oxide NP propels them towards the electrode, as observed with self-propelled Janus “swimmers”. Due to the high electrolyte concentration and low current density applied in this study, the electrophoretic contribution is likely negligible here. Indeed, the latter can be estimated from the current flowing through the electrodes (i < 1 µA in Fig 1 and 2), the electrolyte conductivity (σ = 1 S m-1) and the electrode surface area (A ~ 7 mm2). The electric field, Ef, imposed within the electrolytic solution during the electrochemical activation can then be estimated by:

i =σ Ef A

(1)

It gives an electric field Ef < 0.14 V m-1; for an electrode separation distance in the order of a few mm, it yields a potential difference within the electrolyte of less than 2 mV. This is in agreement with the fact that most of the applied potential is dropped at the electrode region under electrochemical conditions unlike in electrophoresis conditions, which involve much higher current densities. From zeta-potential measurements carried out under similar electrolytic conditions (0.1 M KNO3), the NPs under study are negatively charged, with a zeta potential of


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the order of ~ -20 ± 2 mV and would then develop an electrophoretic mobility of ca. mep = -1.6 10-8 m2 V-1 s-1 in good agreement with reported values.29 Under the given electrochemical conditions, the contribution of electrophoresis to the drift of the NP would result in vep = mep Ef < 2.4 nm s-1 which is 3 orders of magnitude lower than the drift experimentally estimated from the trajectory analysis (vNP ~ 8 µm s-1), ruling out the contribution of an electrophoretic drift from the bulk solution. The absence of NPs drift in the bulk solution indeed accounts for the observed population of NPs with unchanged apparent size or velocity in Figure 3. An electrophoretic process could also account for a drift at closer distance of the electrode or within the diffusion layer, as suggested from the different optical trajectory tracking. A local drift of the NPs would result from a local enhancement of the Ef and, based on the conservation of current flow and eq (1), from a local decrease in the solution conductivity, σ. Even if electrochemical processes generate in the electrode region local changes in ionic distribution, and therefore in solution conductivity, within the electrochemical diffusion layer, the decrease of σ by 3 orders of magnitude, as would be expected here, require the almost complete removal of the electrolyte within the diffusion layer which is impossible owing to the experimental current density and electrolyte content. We then propose that the accelerated motion of the NPs has a diffusive origin. The flow of current at the electrode is usually accompanied by the generation of a concentration gradient of the electrogenerated chemical species; these species can migrate along this gradient through a phoretic mechanism known as diffusiophoresis. This effect has been described under different experimental configurations providing an explanation for the motility and propulsion of microswimmers: heterogeneous objects, e.g. Janus particles, swimming directionally due to a selfgenerated gradient at the NP surface.30,31 It also applies to homogeneous objects, a gradient of


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chemical species in solution then generates a local difference in osmotic pressure at opposite poles of a NP propelling it towards regions of higher chemical species concentration (osmosis). This phenomenon has been demonstrated e.g. for fluorescent colloids and λ-DNA moving against a chemical gradient generated by microfluidics.32 This case is similar to the electrochemically situation encountered herein, where the electrochemical actuation allows the generation of the chemical gradient difference. Noteworthy, the velocity estimated herein is in the range of that measured for colloidal 200 nm spheres submitted to LiCl gradients.32 Here, this phenomenon is directly visualized for the first time on individual metallic NPs in an electrochemical environment. Diffusiophoresis. A modeling by finite-element method of the diffusive-convective transport of NPs during the electrochemical generation of chemical species was carried out on a macroscopic scale to validate the proposed diffusiophoretic mechanism. The mean-field model detailed in the SI, S 7, assumes the NP colloidal solution is a continuum of solution (described by a concentration, CNP, and a diffusion coefficient, DNP). At high enough oxidation potential (ca. > 0.5 V), the electrode surface undergoes an electrochemical process attributed to gold oxide formation according to: 2Au + 3H2O → Au2O3 + 6e- + 6H+

(2)

The production of the diffusion flux of H+ during the Au electrode oxidative transformation, associated to the flow of current, i, is estimated based on the following flux-current relationship:

DH+

∂[H + ] i d Γ Au = = ∂z z=0 FS 3dt

(3)

where DH+ is the diffusion coefficient of H+ whose gradient is estimated at the electrode surface (of area S, at position z = 0), and (3) corresponds to the transformation of Au, modeled as a limited reservoir with apparent surface concentration ΓAu (initially Γ0Au).


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Diffusiophoresis consists in the generation of a velocity drift of NPs in a gradient of a solute, here a gradient of [H+]; this is proportional to a mobility term, mNP, typically of the order of 100 µm2 s-1,32 and to the gradient of the logarithm of [H+] in the form:

vNP = mNP

∂ln[H + ] ∂z

(4)

The distribution and transport of NPs is then obtained from the Nernst-Planck equation:

∂CNP ∂  ∂C  =  DNP NP − vNP CNP   ∂t ∂z  ∂z

(5)

This equation coupled with that of diffusive transport of H+ were computed in the COMSOL V4.3 solver environment for 30 nm radius NPs (SI, S 5). The simulated evolution profiles with the electrode potential of (i) the electrode current (i-E), (ii) the NP concentration at the electrode surface (CNP-E), and (iii) the velocity of NP at the electrode surface (vNP-E) for a fast or slow surface transformation (2) are given in Figure 4a and in the SI, S 6, respectively; they show similar behaviors. These profiles suggest that as soon as current is flowing through the electrode a gradient of H+ is generated at the electrode-solution interface. This gradient of H+ produces a drift of the NPs in the solution towards the electrode surface where they concentrate. Figure 4b shows the concentration profile at the electrochemical peak potential for the (i) electrogenerated H+, and based on diffusiophoresis in the cell, the (ii) NPs distribution along with vNP developing in solution. The full potential and time evolutions of such profiles along the axial coordinate from the electrode surface are also provided in Movies S 5-7. From these figures it can be seen that vNP is highest in the first 60 µm from the electrode surface, where the electrogenerated H+ concentration gradient is the highest, in good agreement with the experimental 3D holographic and 2D Nanosight® optical monitoring of the process.


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This leads to a preconcentration of NPs at the electrode surface that extends 10 µm into the bulk solution. The simulated evolutions of vNP (Figure 4a and 4b) indicate velocities higher than 3 µm s-1 (and up to 5 µm s-1) which drive the NPs towards the electrode for more than 10 s when the electrode potential is swept at 0.02 V s-1. The proposed model, although relatively simple, predicts convective transport that expands in time and space, and with velocities in agreement with those observed experimentally. The model also predicts that the electrogenerated gradient of H+ leads to a preconcentration of the NPs in the electrode vicinity. The evolution of the NP concentration at the electrode surface with the electrode potential (Figure 4a) nicely reproduces the shape of the current-potential profile. This is also consistent with the experimental observation of the increase in NP adsorption events upon current increase during the CV as described in Figure 2c and from the correlation between both measurements as described in Figure 2b. Indeed, NP preconcentration near the electrode surface can also be attributed to near-wall hindered hydrodynamic transport, decreasing their velocity and causing adsorption.33 However, such an effect depends on the NP distance from the electrode surface as a function of its radius. A 50 nm NP should be ~ 500 nm from the electrode surface before the effect is apparent on its Brownian motion.10,33 Although the 3D trajectories of the NPs were tracked herein until they arrived at the electrode surface, MSD analysis was only carried out on the trajectory before they approached within 1 µm of the electrode surface. From example trajectories provided in Figure S 4b, the last 10 or so data points suggest a possible slowing down of the NP before adsorption. However, this occurs well after the observed diffusiophoresis step, therefore unlikely to be the cause of it.


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The experimental correlation between the number of NPs adsorption event at the electrode surface and the electrode current or potential (Figure 2b and 2c) also fits the theoretical correlation predicted for a diffusiophoresis mechanism (Figure 4a). Indeed, the rate of NPs observed in the electrode region is ~ 0.2 s-1 (6 NPs detected during 30 s in Figure 2c) before gold oxide formation, in good agreement with the collision frequencies of Pt or Ag NPs estimated from electrochemical impacts respectively 0.03 and 0.15 s-1 pM-1 for the 40 × 40 µm2 area observed here.4-6 From the adsorption events depicted in Figures 2b and c, this collision frequency increases by up to a factor of 8 to 1.6 s-1 during the Au oxide formation. Given the experimentally obtained results, a preconcentration factor of 10 is also expected for NPs of 30 nm radius when considering a NP mobility of 100 µm2 s-1. Nanoparticle Oxidation and Dissolution. As commented on above, when following the diffusiophoresis of NPs to the electrode surface, adsorption of NPs was monitored optically even though its characteristic time cannot be resolved here (< 0.025 s). For the adsorbed NPs, after a given onset potential, Isc starts to decay back to the optical noise level (e.g. green curve in Figure 2a). Such decay corresponds to the disappearance of the NP and different decay dynamics have been monitored (Figure 2a) that are slower than the characteristic time of the NP adsorption process and are associated to the NP dissolution according to the overall transformation: Ag → Ag+ + e-

(6)

The dynamics of this overall NP dissolution, characterized by its onset potential, Eon, and its kinetics (of apparent rate, k0) was thus investigated for different NP sizes and electrolyte nature (KSCN or KNO3). Figures 5a and S 9 provide selected typical examples of Isc profiles obtained from 3D monitoring for a colloidal solution of 30 nm Ag NPs undergoing oxidation-dissolution in KNO3 or KSCN solution, respectively, with potential scanning and as a function of time.


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Onset Potential. As highlighted above, dissolution is observed for preadsorbed NPs as well as for impacting NPs. Figure 5b summarizes the total number of NPs (adsorbed or mobile) observed dissolving with Eon. In a solution of aerated KNO3, values of Eon for Ag NP dissolution are higher than 0.6 V vs QRE (0.95 V vs SHE), they are larger than that measured for Ag NPs anodic stripping17,34 or than the standard potential for Ag/Ag+ transformation (0.8 V vs SHE). Moreover, the dissolution of mobile NPs monitored in Figures 1, 2 and 5a does not always take place immediately following the impact (or adsorption), even though the impact is recorded at potentials much higher than 0.6 V or even when sweeping back E to lower values (red trace in Figure 5a). The long contact time of NPs on an electrode surface under electrochemical activation has already been described as sticky impacts4,8,35 and is what is optically resolved here. It suggests a far more complex oxidative dissolution process than previously believed, for example as intervention of the NPs surface passivation by a thin oxide layer16 shifting the oxidative dissolution to more anodic potentials. This stresses the importance of optical monitoring for a complementary understanding of the surface processes associated to the electrochemistry of individual nanoobjects. Interestingly, when varying the NP size (30 or 50 nm radii single NPs), the size of the NP does not have a significant effect on the onset potential for their dissolution as previously observed from macroscopic electrochemical stripping experiments.34 The presence of SCN- ions has much more effect on Eon shifting at much lower potentials, by up to 0.4 V lower than that in a solution of NO3-. Indeed, the presence of SCN- ions, good ligands for Ag+,16,36 facilitates the overall Ag oxidation. The low solubility of AgSCN (Ks = 1012

M-2) is in favor of the formation of AgSCN during the Ag NPs oxidation as in (7), while the

existence of different soluble Ag(I) species (AgSCN, Ag(SCN)2-, Ag(SCN)32-, Ag(SCN)43-) will


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rule further dissolution of the NP according to the different reactions summarized for x = 0 - 3 by (8).36 Henceforth, in KSCN, the overall process for the oxidation/dissolution of Ag NPs is described by (7) and (8) far more complex than (6). Ag+ + SCN- → AgSCN + e-

(7)

AgSCNNP + x SCN- → Ag(SCN)x+1x-

(8)

Kinetic Analysis of Dissolution. The kinetics of the dissolution may be obtained from its optical monitoring at the level of individual NPs (Figures 5a and S 11). The evolution of Isc, or equivalently the scattering cross-section, is expected to reflect the evolution of the NP dimension, and eventually physical or chemical structure37 or environment,38,39 during a chemical transformation. Here, the evolution of Isc allows a quantitative analysis of the dissolution process if the theoretical optical response is known for the scattering Ag NPs of given sizes that have adsorbed on a thin optically transparent Au layer. A finite element modeling is proposed solving Maxwell’s equation and thereby calculating the light scattered by a Ag metallic nanosphere immobilized on a thin Au metallic layer (detailed in the SI, S 6). This model shows that the presence of the metallic substrate matters.40 Thereby, Isc is predicted to be proportional to the NP volume, Isc ∼ rNP3 for rNP < 50 nm, instead of the rNP6 scaling predicted by Mie’s theory for a NP surrounded by an homogeneous medium. The lower exponent reveals plasmonic cross-coupling between the adsorbed NP and the Au electrode. Optical monitoring of the intensity scattered by individual particles, Isc, then yields a direct estimate of the relative (volume) size decrease for each individual NP, rNP , during dissolution. A qualitative examination shows that the complete transformation of a NP takes place with characteristic times of 1 to 5 s. This is 2 to 50 times longer than those observed for Ag NP dissolution measured upon electrochemical impact experiments,5 and up to 5 times longer than


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that detected by SPR.16 In particular, along the large potential window explored here, the characteristic time of transformation is not significantly modified and some NPs can withstand much higher electrode potential incursions (> 0.3 V more anodic than the lowest Eon) without being dissolved much faster (Figure 5b). Together with the observed dissolution of some NPs performed at decreased driving force (starts at the reverse scan of the cyclic voltammetry), the dissolution, initiated after an induction period, is likely a mass-transfer limited process. The theoretical evolution of rNP at time t during individual NP dissolution under mass-transfer regime (outlined in the SI, S 8), or equivalently Isc, is expected to follow:

(9)

where r0,NP and I0,sc are the radius and scattering intensity before the onset time of dissolution, ton; D and C0, are the solution diffusion coefficient and concentration at the NP surface of Ag+ ions, respectively; MAg and ρAg are the molar mass and density of Ag. Examples of kinetic analysis on individual NPs dissolving are given in Figures 5a and S 11 (dashed lines) using the fitting with (9) and considering the modeled optical response (right hand side of (9)). The fit of the full Isc profile with this mass-transfer limited model is reasonable for all the dissolved NPs analyzed. The values of the apparent rate for the transformation of Ag NPs, k0 = 2ln2DC0MAg/ρAgr20,NP in (9), are collated in Figure 5c for the different experimental conditions, which highlights the independence between NP size and rate of dissolution. In the presence of SCN-, the fit yields an apparent rate for the transformation of a 30 nm radius Ag NPs of 0.35 ± 0.1 s-1. For a diffusion controlled process, (9) implies [Ag+] at the NP surface, C0, is ca. 13 µM during the NP dissolution (with D = 1.7 10-5 cm2 s-1). The obtained value is in excellent agreement with the solubility of Ag(I) species in a 0.05 M SCN- solution, estimated to be 15 µM.


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Hence, in the presence of SCN-, the mass transfer dissolution of NPs is driven by the solubility of the Ag(I) species (7 and 8). An increase in [SCN-] would result in an enhancement in the solubility of Ag(I) species, yielding an overall increase in the NPs dissolution rate (by up to 20 times) to values in agreement with those estimated by SPR.16 The dissolution kinetics in KNO3, and in the absence of SCN-, was also studied by fitting the evolution of the recorded optical signal with (9). For all features, the dissolution occurs within characteristic rates (Figure 5c) comparable to or smaller than those observed in KSCN. The data presented herein highlight the dissolution rate to be more homogenous for Ag NPs in KSCN but more stochastic for KNO3. Overall, in KNO3, estimated from the Isc profiles is also much lower than the value expected for a mass transfer controlled process or from what was observed from electrochemical NP impact experiments, suggesting, as proposed for KSCN, the intervention of an insoluble phase during Ag NPs, likely an Ag oxide shell.

In conclusion, light scattering microscopy in 2D and 3D holographic imaging have been employed with voltammetry to study both optically and electrochemically the transport and dissolution process of single NPs. The association of these techniques proves highly valuable to decipher each elementary step involved in the electrochemical processes: i) transport of the species to the electrode surface, ii) adsorption or interaction with the electrode surface, and iii) electrochemically driven physical-chemical reaction. Specific transport processes, such as diffusiophoresis, were found to be driven by the electrochemical activation, here a H+ electrogenerated gradient, resulting in an apparent acceleration and preconcentration of NPs within the vicinity (15 µm) of the electrode surface. The electrochemical dissolution of adsorbed NPs was then successfully monitored optically and allowed kinetic analysis to be carried out


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using the change in the intensity of the scattered light for each NP, which corresponds to a change in volume. The dissolution kinetics (1 to 5 s) was found to be slower than previously reported (0.3 to 1 s),6,16 suggesting the contribution of low solubility products. The results here are consistent with nanoimpact studies carried out by other groups (e.g. NP sticking, detachment, electrochemically-driven transports) as discussed above, but the diversity of behaviors observed herein cannot be detected unambiguously without the coupled optical monitoring. For example, it is observed here that the NP electrochemical dissolution may not be instantaneous upon the NP arrival or adsorption at the electrode. Moreover, optical microscopy is particularly useful to monitor slow dissolution processes that might be below the sensitivity of current nano-impact electrochemical measurements, although electrochemical impact experiments have allowed for the study of individual nanoobjects with unprecedented mechanistic insight. Although only the dissolution process is monitored here, without faradaic estimate of the prior electrochemical step due to the large electrode size used, our results suggest that NP sizing based only on their individual nano-impact electrodissolution should be considered carefully since events could be undetected when insoluble products are formed. It is suggested that the full diversity of behaviors of NPs may only be revealed by single nanoobject electrochemistry coupled to optical or independent (AFM, local-probe,…) structure monitoring. In particular, on-going research devoted to combining optical monitoring with electrochemical monitoring at micrometer or nanometer size electrode of individual nano-impacts electrochemistry will be promising as they would allow the decoupling of the whole processes (charge transfer and chemical transformation) associated to electrodissolution or more generally electrochemistry at single NPs. ASSOCIATED CONTENT


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Supporting Information. Additional information on 2D and 3D light scattering imaging, experimental details, volume reconstructions, NP tracking and MSD analysis, FEM optical and diffusiophoresis modeling. This material is available free of charge via the Internet at http://pubs.acs.org. AUTHOR INFORMATION Corresponding Authors *email: [email protected], [email protected] Funding Sources This work was supported by Université Paris Diderot, CNRS and laboratoire d’excellence Institut Pierre-Gilles de Gennes (Labex IPGG), “Investissements d’avenir” program ANR-10IDEX-0001-02 PSL and ANR-10-LABX-31. ANP thanks the “Research in Paris” program and Labex IPGG for funding. Notes The authors declare no competing financial interest ACKNOWLEDGMENT We are grateful to Christopher Batechelor-McAuley, Kristina Tschulik, and Richard G. Compton at the University of Oxford, UK, for their generous advice and suggestions. REFERENCES

1. Bai, C.; Liu, M. Angew. Chem. Int. Ed. 2013, 52, 2678-2683. 2. Stevenson, A. P.; Blanco Bea, D.; Civit, S.; Antoranz Contera, S.; Iglesias Cerveto, A.; Trigueros, S. Nanoscale Res. Lett. 2012, 7, 151. 3. Compton, R. G. ; Wildgoose, G. G. ; Rees, N. V. ; Streeter, I. ; Baron, R. Chem. Phys. Lett. 2008, 459, 1-17. 4. Xiao, X.; Bard, A. J. J. Am. Chem. Soc. 2007, 129, 9610-9612. 5. Xiao, X.; Fan, F. R.; Zhou, J.; Bard, A. J. J. Am. Chem. Soc. 2008, 130, 16669-16677. 6. Zhou, Y. G.; Rees, N. V.; Compton, R. G. Angew. Chem. Int. Ed. 2011, 50, 4219-4221.


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7. Huang, K.; Anne, A.; Bahri, M. A.; Demaille, C. ACS Nano 2013, 7, 4151-4163. 8. Kleijn, S. E.; Lai, S. C.; Miller, T. S.; Yanson, A. I.; Koper, M. T.; Unwin, P. R. J. Am. Chem. Soc. 2012, 134, 18558-18561. 9. Lai, S. C. S.; Lazenby, R. A.; Kirkman, P. M.; Unwin, P. R. Chem. Sci. 2015, 6, 1126-1138. 10. Kang, M.; Perry, D.; Kim, Y.-R.; Colburn, A. W.; Lazenby, R. A.; Unwin, P. R. J. Am. Chem. Soc. 2015, doi : 10.1021/jacs5b05856. 11. Dick, J. E.; Renault, C.; Kim, B. K.; Bard, A. J. Angew. Chem. Int. Ed. 2014, 53, 1185911862. 12. Amatore, C.; Arbault, S.; Chen, Y.; Crozatier, C.; Lemaitre, F.; Verchier, Y. Angew. Chem. Int. Ed. 2006, 45, 4000-4003. 13. Sun, T.; Yu, Y.; Zacher, B. J.; Mirkin, M. V. Angew. Chem. Int. Ed. 2014, 53, 14120-14123. 14. Gu, M.; Parent, L. R.; Mehdi, B. L.; Unocic, R.R.; McDowell, M. T.; Sacci, R. L.; Xu, W.; Connel, J. G.; Xu, P.; Abellan, P.; Chen, X.; Zhang, Y.; Perea, D. E.; Evans, J. E.; Lauhon, L. J.; Zhang, J.-G.; Liu, J.; Browning, N. D.; Cui, Y.; Arslan, I.; Wang, C.-M. Nano Lett. 2013, 13, 6106-6112. 15. Shan, X.; Diez-Perez, I.; Wang, L.; Wiktor, P.; Gu, Y.; Zhang, L.; Wang, W.; Lu, J.; Wang, S.; Gong, Q.; Li, J.; Tao, N. Nat. Nanotechnol. 2012, 7, 668-672. 16. Fang, Y.; Wang, W.; Wo, X.; Luo, Y.; Yin, S.; Wang, Y.; Shan, X.; Tao, N. J. Am. Chem. Soc. 2014, 136, 12584-12587. 17. Hill, C. M.; Pan, S. J. Am. Chem. Soc. 2013, 135, 17250-17253. 18. Meunier, A.; Jouannot, O.; Fulcrand, R.; Fanget, I.; Bretou, M.; Karatekin, E.; Arbault, S.; Guille, M.; Darchen, F.; Lemaitre, F.; Amatore, C. Angew. Chem. Int. Ed. 2011, 50, 5081-5084. 19. Batchelor-McAuley, C.; Martinez-Marrades, A.; Tschulik, K.; Patel, A. N.; Combellas, C.; Kanoufi, F.; Tessier, G.; Compton, R. G. Chem. Phys. Lett. 2014, 597, 20-25. 20. Squires, T. M.; Messinger, R. J.; Manalis, S. R. Nat. Biotechnol. 2008, 26, 417-426. 21. Orrit, M.; Bernard J. Phys. Rev. Lett. 1990, 65, 2716-2719. 22. Betzig, E. Opt. Lett. 1995, 20, 237-239. 23. Martinez-Marrades, A.; Rupprecht, J.F.; Gross, M.; Tessier, G. Opt. Express 2014, 22, 29191-29203. 24. Boika, A.; Bard, A. J. Anal. Chem. 2014, 86, 11666-11672. 25. Dhakshinamoorthy, A.; Garcia, H. Chem. Soc. Rev. 2012, 41, 5262-5284. 26. Xiu, Z. M.; Zhang, Q. B.; Puppala, H. L.; Colvin, V. L.; Alvarez, P.J. Nano Lett. 2012, 12, 4271-4275. 27. Malloy, A.; Carr B. Part. Part. Syst. Charact. 2006, 23, 197-204. 28. Fosdick, S. E.; Anderson, M. J.; Nettleton, E. G.; Crooks, R. M. J. Am. Chem. Soc. 2013, 135, 5994-5997. 29. Li, X; Lenhart, J. J.; Walker, H. W. Langmuir 2011, 28, 1095-1104. 30. Mano, N.; Heller, A. J. Am. Chem. Soc. 2005, 127, 11574-11575. 31. Lee, T. C.; Alarcon-Correa, M.; Miksch, C.; Hahn, K.; Gibbs, J. G.; Fischer, P. Nano Lett. 2014, 14, 2407-2412. 32. Palacci, J.; Abecassis, B.; Cottin-Bizonne, C.; Ybert, C.; Bocquet, L. Phys. Rev. Lett. 2010, 104, 138302. 33. Barnes, E.O.; Zhou, Y.-G.; Rees, N.V.; Compton, R. G. J. Electroanal. Chem. 2013, 691, 2834.


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34. Ward Jones, S. E.; Campbell, F. W.; Baron, R.; Xiao, L.; Compton, R. G. J. Phys. Chem. C 2008, 112, 17820-17827. 35. Tschulik, K.; Palgrave, R. G.; Batchelor-McAuley, C.; Compton, R. G. Nanotechnology 2013, 24, 295502. 36. Charlot, G. Les méthodes de la Chimie Analytique: Analyse quantitative minérale. Paris, 1966; p 20. 37. Liu, J.; Maaroof, A. I.; Wieczorek, L.; Cortie, M. B. Adv. Mater. 2005, 17, 1276-1281. 38. Noguez, C. J. Phys. Chem. C 2007, 111, 3806-3819. 39. Ringe, E.; McMahon, J. M.; Sohn,K.; Cobley, C.; Xia, Y.; Huang, J.; Schatz, G. C.; Marks, L. D.; Van Duyne, R. P.; J. Phys. Chem. C 2010, 114, 12511-12516. 40. Knight, M. W.; Grady, N. K.; Bardhan, R.; Hao, F.; Nordlander, P.; Halas, N. J. Nano Lett. 2007, 7, 2346-2350.


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FIGURES

Figure 1. Schematic diagram for holographic imaging where a holographic microscope records the transport and surface reaction processes during electrochemical activation of an Au electrode in an Ag NPs colloidal solution by whole volume inspection under laser light illumination, with selected images (8x8µm2) of the electrode surface showing NP attraction and dissolution.


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c)6 NP count

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5

E>0.6V

4

E 0.6 V).


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Figure 3. Transport analysis. (a) Example of MSDs tracked in 3D by holography for a 30 nm radius Ag NP (dark blue) and under electrochemical activation corresponding to a radius of 21 nm (red). Each MSD consists of 100 points recorded over 2.5 s. (b) A summary of the estimated apparent size distribution of Ag NPs tracked in the absence (blue) and in the presence (red) of electrochemical activation. Overlaid size distribution from NanoSight microscope performed at farther distance from the electrode (green) of 30 nm Ag NP solution whilst sweeping the electrode potential between 0.3 to 0.6 V.


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Figure 4. Diffusiophoresis modeling. (a) Simulated evolution profile of local NP concentration at an electrode generating diffusiophoresis for 30 nm radius NPs at the electrode surface with the electrode potential (red), with the theoretical CV (black) and the simulated fluid velocity profile in the channel due to diffusiophoresis (blue). (b) Simulated concentration profile along the normal to the electrode (electrode at z = 0) at the electrochemical peak potential of (I) electrogenerated H+ due to Au oxidation (black) , (II) subsequent NP concentration profile due to electrogenerated H+ (black) and (III) velocity profile of Ag NPs in solution (blue).


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Figure 5. a) Examples of change in scattered light intensity for 30 nm single Ag NPs undergoing electrochemical dissolution in KNO3 recorded by 3D holography (colored lines) fitted by modeled dissolution (dashed lines, eq 9) to extract rate of dissolution, along with complementary experimental CV trace overlaid (black solid line). b) Distribution for onset dissolution potential of Ag NPs in KNO3 (red, blue) or KSCN (black) for: 30 nm in radius (black and red), 50 nm in radius (blue). c) Summary of the characteristic dissolution rate obtained for a diffusioncontrolled model fitting for NPs of: 30 nm in KSCN (black); 30 nm (red), 50 nm (blue) in KNO3.


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Table of Contents Graphic

vdiff


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Deciphering the Elementary Steps of Transport ... - ACS Publications

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