Article pubs.acs.org/JPCC
Electrochemical and AFM Study of the 2D-Assembly of Colloidal Gold Nanoparticles on Dithiol SAMs Tuned by Ionic Strength Daniel García Raya,† Christophe Silien,‡ Manuel Blázquez,† Teresa Pineda,† and Rafael Madueño*,† †
Institute of Fine Chemistry and Nanochemistry, Department of Physical Chemistry and Applied Thermodynamics, University of Córdoba, Campus de Rabanales, Ed. Marie Curie 2a planta, E-14014 Córdoba, Spain ‡ Department of Physics and Energy, and Materials and Surface Science Institute, University of Limerick, Limerick, Ireland S Supporting Information *
ABSTRACT: Colloidal deposition of gold nanoparticles (AuNPs) on 1,8octanedithiol self-assembled monolayer (ODT-SAM) Au(111) surfaces is accomplished by spontaneous adsorption from solutions with different ionic strengths under diffusion-controlled transport. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) show that AuNPs|ODT-SAM| Au(111) ensembles efficiently promote electron transfer (ET) across an ODT insulating monolayer as a function of the surface coverage of the particles (θ), which is tuned by controlling both deposition time and ionic strength conditions. ET rate constants are obtained by fitting EIS data to a Randles circuit and thus, θ can be determined according to the partially blocked electrodes theory. Saturation particle densities (Γmax) and surface coverage (θmax) values are in good agreement with those determined by atomic force microscopy (AFM) measurements indicating the validity of the electrochemical approach. θmax and adsorption kinetics of AuNPs assembly are interpreted in terms of a random sequential adsorption (RSA) model based on long-range repulsive electrostatic interactions between particles treated as softspheres. Consequently, physicochemical parameters of the colloidal nanoparticles are extracted.
■
INTRODUCTION The “bottom-up” approach has emerged in the field of nanoscience and nanotechnology as a promising and versatile strategy to design hybrid functional nanostructured materials integrated by a plethora of different organic and inorganic constituents via the concept of individual building blocks selfassembly.1−6 The combination of micro- and nanoparticles (NPs) with controlled size, stoichiometry, and morphologies,3,7,8 and self-assembled monolayers (SAMs) as building blocks allows the creation of one-9,10 (1D), two-11 (2D), or three-dimensional12 (3D) architectures with different configurations and degrees of order on a substrate. Such NPs arrangements determine the physical and chemical properties of the constructs in prospect of applications in areas such as catalysis, nanoelectronics, optoelectronics and energy conversion, molecular recognition, and bioelectrochemistry.1−6,13,14 In fact, these assembled nanostructures have shown great interest in the development of devices where chemical, optical or biological stimuli can be transduced into readable electrical responses. Nanoparticles Confinement into 2D Arrangements: Electron Relay and SERS Active Surfaces. Of particular interest is the assembly of 2D arrays of metallic, semiconductor or magnetic NPs on a surface in a controlled manner down to the nanometer scale, either by their well-defined packing and/ or precise location into patterned structures or by tuning their interparticle distance in a random distribution.15−22 Furthermore, the ability of metallic NPs to act as electron relay stations © 2014 American Chemical Society
and plasmonic photon-absorbing antennae provides unprecedented capabilities to mediate the electron transfer (ET) communication with the underlying surface5,17−19,23−26 and to produce highly localized enhanced electromagnetic fields as a function of the gap between adjacent particles and a planar substrate22,27,28 (SERS active surfaces). Therefore, tailoring of the local environment and the spatial distribution of NPs becomes a key aspect to manipulate the optical and electrical effects of the nanomaterials and the interaction with inorganic, organic, or biological systems. From a fundamental point of view, the study of simple or long-range interfacial ET processes of single molecules or biomolecules is important to unravel the origin of charge transfer mechanisms for the efficiently NPpromoted recovery of the electrical conductivity and the improvement of the bioelectrochemical signal sensitivity in the electrode ensembles.14,29−32 As aforementioned, this effect is reminiscent both of the strong interfacial field enhancement of the NPs surface plasmon delocalization and of coherent multiET. Among different NPs, gold nanoparticles (AuNPs) are widely adopted because of their good biocompatibility and wellestablished protocols for the synthesis of monodisperse core sizes with well-defined nanoscaled dimension properties in the range of 1 to 100 nm.13,14,33 Then, 2D assembly of AuNPs can be achieved by specific interactions between the nanoparticle Received: March 18, 2014 Revised: June 10, 2014 Published: June 10, 2014 14617
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
the electrical surface properties of the particles, their size, and geometry.42,45,48−50 Such interactions include van der Waals forces, but especially electrostatic ones, that can be tuned by the pH and ionic strength of the solution allowing one to test model predictions according to the DLVO theory.42,45,48 The random sequential adsorption (RSA) model provides an approximated treatment for the energy calculation of the electrostatic interactions involved between ideal spherical particles, but useful enough to get insight into important physicochemical parameters of the system, such as NPs effective radius, NPs surface charge and potential, interparticle distance, and attainable limiting surface coverages (θmax).42,45,48−50 Albeit the experimental study of the ionic strength dependent colloidal adsorption has dealt with bigger NPs, e.g., tens of nanometers43,44,46,47,51 and micrometer size range,11,42 however, the behavior of small AuNPs has been scarcely tackled as it is claimed in this work according to a RSA scenario based on long-range repulsive electrostatic interactions. Quantitative determination of particle density (i.e., NPs surface coverage) and adsorption kinetics is a necessary condition to check the validity of the RSA model approximations. For this purpose, there exists a large variety of indirect and direct experimental methods.45 Although the indirect methods are the simplest to implement, their main disadvantage is the impossibility to observe directly the NP surface distribution and unequivocally determine their surface concentration below 10% with the required accuracy. On the other hand, direct methods such as atomic force microscopy (AFM) and scanning electron microscopy (SEM) provide the required quantitative verification of the theoretical predictions, even for rather low surface coverages at a 1% order or below, and a way to check the results generated by indirect methods. In spite of the broad potential of colloidal assembly and the possibility to apply the RSA model predictions to extract important physicochemical information in these systems, there are few works in the literature devoted to this for AuNPs systems. Furthermore, up to our knowledge, such studies have not been addressed by the use of both indirect electrochemical and direct AFM characterization techniques. This work studies the role of the ionic strength in the adsorption kinetics, particle density, and distribution of AuNPs assembly onto 1,8-octanedithiol SAM modified Au(111) singlecrystal surfaces by electrochemical and AFM techniques. In this framework, electrochemical spectroscopy impedance (EIS) is demonstrated to be a simple and convenient indirect method not only to elucidate the promoted ET in the AuNPs|Dithiol SAM|Metal ensembles, but also to access to the limiting AuNPs surface coverages and the deposition kinetics under diffusioncontrolled transport at different ionic strength conditions. Interestingly, this has also allowed usto verify the validity of theoretical predictions supported by approximated models, such as the random sequential adsorption (RSA) approach, in the deposition process of AuNPs.
surface or its protective organic shell and a properly functionalized substrate. Surface Functionalization: A Platform for NPs Attachment. Self-assembled monolayers (SAMs) provide great versatility on surface functionalization due to the high affinity of bifunctional organic compounds to bind to substrates, and to self-organize through lateral intermolecular interactions into well-ordered structures, bearing terminal groups (e.g., −SH, −NH2, −COOH, −CN, etc.) exposed to the interface that are able to attach electrostatically18,19,21−25,27,28,34,35 or covalently15,17,20,22,27,34,36,37 AuNPs. The formation of SAMs with organic monothiols is usually well-understood and widely controlled to an outstanding level.1,2 However, surface functionalization based on high quality and well-organized dithiol monolayers with exposed −SH terminal groups in an up-right configuration still remains challenging in prospect of reproducibility and proper technological applications. Thus, control of the experimental assembly conditions and preparation strategies are of interest in order to produce different molecular arrangements with tunable layer thickness on a metallic substrate.37−39 Metallic electrodes coated with ωsubstituted alkanethiol SAMs are the most common studied because of their excellent insulating properties that act as energy barriers greatly reducing the ET rate across the films upon increasing the linker chain length.24,26,40,41 As a result, the ET of redox probes is blocked, and these SAMs serve as ideal model systems to study the ET kinetics mediated by AuNPs| SAM|Metal constructs, where the particle density and their distribution have a significant impact to return the electronic communication with the collector surface and to provide controlled SERS effects. In this sense, we have recently proposed the spontaneous assembly of HS−(CH2)8−SH monolayers (ODT-SAMs) into single-crystal Au(111) surfaces from a lyotropic medium to avoid the uncontrolled formation of multilayers by intermolecular S−S bonding and/or lying down phases due to the high affinity of both −SH functional groups to anchor at gold surfaces.37 In this work, the insertion of dithiol compounds into micelles is employed as a valid approach to form insulating monolayers of standing-up ODT molecules that serve as a platform to covalently attach AuNPs with controlled surface coverage (θ) placed at a fixed nanogap distance away from the substrate. Colloidal Assembly: A Solution-Based Strategy to Control NPs Distribution on a Surface. Therefore, colloidal assembly appears to be the simplest and most flexible method of building up NPs layers of controlled properties and tunable particle density onto a homogeneously functionalized surface in a systematic way. This solution-based method exhibits some main advantages, such as precise control of monolayer coverages and 2D distribution of NPs over large areas by changes in the deposition time, temperature, pH, ionic strength, and bulk concentration of NPs, together with the flexibility to produce multifunctional ensembles and multilayers by applying the layer by layer deposition technique. For charged colloidal solutions, such experimental conditions govern the kinetics of the diffusion-controlled deposition process and the extent of the repulsive electrostatic interactions between particles.20,21,42−47 The latter aspect will determine their average interparticle distance, i.e., the particle density and θ, and their arrangement into a random distribution onto the planar substrate. Description of NPs interactions provides a framework to calculate the interaction energies that control their localized adsorption behavior, which requires the knowledge of
■
EXPERIMENTAL SECTION Chemicals. 1,8-Octanedithiol (ODT), Triton X-100, potassium ferrocyanide and ferricyanide, perchloric acid, tetrachloroauric acid, sodium citrate trihydrate, and semiconductor-grade-purity potassium hydroxide were purchased from Sigma-Aldrich. The rest of the reagents were from Merck analytical grade. All solutions were prepared with ultrapure 14618
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
μS/cm to 10−15 μS/cm). The pH and conductivity were measured with a Crison Basic 20 pH meter and a Crison Basic 30 conductimeter, respectively. The deposition of AuNPs was carried out by contacting an ODT-SAM/Au(111) surface in the hanging meniscus configuration with AuNPs solutions of different ionic strengths. The ionic strength was adjusted by adding trisodium citrate and the actual values were obtained by using a conductivity calibration curve (Figure S2, Supporting Information). UV−visible extinction spectra were acquired with a Jasco V-670 UV− vis−NIR spectrophotometer and 0.2 cm path length cuvettes in order to check the stability of the AuNPs solutions (Figure S3, Supporting Information). Adsorption times from several seconds to hours were assayed to control the AuNP surface coverage. After the deposition step, the substrates were thoroughly rinsed with water and immediately used for the electrochemical characterization. Once the electrochemical measurement was carried out, the AuNP|ODT-SAM|Au(111) samples were washed with water and dried with nitrogen prior to imaging with atomic force microscopy (AFM). Electrochemical and Atomic Force Microscopy (AFM) Characterization. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) curves were recorded on an Autolab (Ecochemie model Pgstat30) instrument attached to a PC with proper software (GPES and FRA) for the total control of the experiments, data acquisition, and analysis. AuNP layers were analyzed by using atomic force microscopy (AFM) in the tapping mode under ambient conditions (air). AFM images were acquired with use of a Nanoscope III atomic force microscope (Digital Instruments, Santa Barbara, CA). Silicon nitride cantilevers of 100 μm length (spring constant 42 N/m and resonant frequency 320 kHz) with integrated sharpened tips were used (5−10 nm diameter). The number of particles per unit area deposited on the ODTSAM surface was determined from the AFM images recorded at least at seven different positions on each sample to ensure reproducibility over large-scale surface areas and to allow counting of at least 1000 particles by using image analysis free software (Gwyddion 2.32).
water produced by a Millipore system (18.2 MΩ and organic content 0.5 at low immersion times (1−6 min) (Figure 1d−f). These results indicate that the average center-to-center separation (d) of adjacent nanoelectrodes is higher than their individual diffusion layer thicknesses which allow radial diffusion. It is accepted that to hold this assumption, d should be at least 12-fold the particle radius a,17,19,37 giving to particle separations higher than 78 nm and a particle density (Γ) lower than 1.6 × 1010 NP·cm−2.37 On the other hand, for Au(111)|ODT-SAM|AuNPs ensembles formed at higher ionic strengths (κa > 0.5), the CVs exhibit peaked features characteristic of macroelectrode behavior. The observed trend consists of an increase of the peak current parallel to a peak-to-peak potential separation decrease when the κa parameter is increased (Figure 2). Finally, a reversible CV profile is achieved, in agreement with higher particle populations and average distances lower than 78 nm, where the diffusion layers of the individual nanoparticles merge resembling the response for the bare gold electrode (FigureS4b, Supporting Information).17,36 This phenomenon has been explained in terms of a possible uneven particle distribution17,36 or a tunneling resistance dependent on the number of linker molecules attached to the AuNP ensembles.19 The trends observed by CV can be rationalized by comparing with electrochemical impedance spectroscopy (EIS) results. Figures 3 and 4 show the EIS response (Nyquist plots) of the AuNP|ODT-SAM|Au(111) constructs. This impedance behavior can be analyzed by using a Randles-like equivalent circuit (Scheme 1). Two main frequency regions corresponding to different time scales of the electrode processes can be distinguished: (i) a semicircle at high frequencies indicating kinetically controlled faradaic reactions related to the charge transfer resistance of the redox probe across the interface (Rm and RAuNPs) and (ii) a straight line at low frequencies indicating mass transport diffusion-controlled redox probe reactions (W impedance). The EIS data were analyzed by using both equivalent circuits (Scheme 1) to determine Rm, RAu, and RAuNPs values. The apparent ET rate constants (kapp ET ) can be calculated by the following expression:
Figure 1. Cyclic voltammograms in 2.5 mM K3Fe(CN)6 + 0.1 M KNO3 for a Au(111)/ODT-SAM modified electrode before (magenta line) and after different immersion times in gold colloidal solutions at pH 4.5 with different ionic strength (i.e., screening parameter κa): (a) 0.21, (b) 0.40, (c) 0.50, (d) 0.62, (e) 1.23, and (f) 1.95. Electrochemical response for a bare single-crystal Au(111) electrode (black line). Sweep rate: 0.1 V/s.
pinhole sites in the monolayer and we use this fact to evaluate the film quality. AuNPs attachment is carried out upon contact of insulating ODT-SAM|Au(111) surfaces with colloidal solutions at fixed ionic strengths for different times. The adsorption should take place by strong covalent bonding between the −SH terminal groups of the monolayer and AuNPs surface. The control on the surface coverage and interparticle separation can be accomplished through changes in the modification time18,19,22,27 and by electrostatic screening controlled adsorption. 20,21 According to the Derjaguin−Landau− Verwe−-Overbeed (DLVO) theory, electrostatic forces can be modulated by variation of the solution ionic strength. In fact, the increase of ionic strength has a screening effect in the repulsive electrostatic interactions of the surface charged neighboring nanoparticles, as a consequence of the decrease in the Debye screening length, κ−1. Thus, changes in the double-layer thickness allow tuning the spatial extent of the interparticle interactions and eventually, the particle separation. For convenient comparison of the screening effect at particles with different radius a, the dimensionless screening parameter, κa, is frequently used. As can be seen in Figure 1, the increase in the immersion time and κa parameter leads to a progressive recovery of the ferricyanide current signal due to a higher surface density of AuNPs acting as mediator relay stations. For each ionic strength condition, current signals typically reach maximum values with no further detectable changes for immersion times higher than 16 h. Figure 2 shows the CVs obtained at immersion times of 16 h as a function of the screening parameter κa. It is worth noting that different diffusion limited transport regimes are clearly discernible in the voltammetric profiles. These observations are related to the surface distribution and
RET =
RT app n2F 2kET AC
(1)
where R is the gas constant, T the temperature, F the Faradaýs constant, n the number of electrons, A the geometric area of the 14620
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
electrode, and C the solution concentration of the redox couple. The EIS obtained for the bare Au(111) electrode (Figure 4) shows a small semicircle in the region of high frequencies that allow us to determine an average value of kapp Au = 0.011 ± 0.002 cm/s, which is in good agreement within values reported for the quasireversible redox reaction of the ferricyanide probe.18,58−60 In contrast, the apparent ET rate constant obtained for the ODT-SAM is kapp = 3.5 × 10−7 cm/s. m Assuming that an expected value of around 3 × 10−6 cm/s would be obtained for an ideal defect-free ODT layer under ET tunneling conditions, we can assume that the monolayers formed behave as an efficient barrier that prevents the approach of the redox probe to the gold surface.37 The ET is promoted and the apparent rate constant is clearly enhanced upon surface decoration with AuNPs distributed on top of an electrochemically blocking ODT modified surface. It can be seen in Figures 3 and 4 that an increase of the modification time and κa parameter runs parallel with a decrease in the charge transfer resistance (RAuNP), and a gradual appearance of the Warburg element. This effect provides a strong indication of electron coupling between the conducting nanoparticles and the substrate as a function of the surface particle density. Thus, the evolution of the electrochemical response can be correlated to the surface coverage of AuNPs. Considering that the theory of partially blocked electrodes56 as modified by Fermin et al.18 applies in the present case, the relationship between rate constants, surface coverage (θ), and particle number density (Γ) is given by eqs 2 and 3:
Figure 3. Impedance (Nyquist) plots in 2.5 mM K3Fe(CN)6 + 0.1 M KNO3 for a Au(111)|ODT-SAM modified electrode before (magenta line) and after different immersion times in gold colloidal solutions at pH 4.5 of different κa: (a) 0.21, (b) 0.40, (c) 0.50, (d) 0.62, (e) 1.23, and (f) 1.95. The solid black lines represent the fits to the Randles equivalent circuit.
app app app kAuNP = kAu θ = kAu Γπa 2
(2)
RT app 2 n2F 2kAu πa RAuNPAC
(3)
Γ=
kapp AuNP
kapp Au
where and correspond to the average apparent ET rate constants for the array of AuNPs and the bulk Au electrode, respectively. This implies that the ET rate constant value for a single AuNP coincides with that of the bulk gold app app electrode (kapp Au ), and the limiting value of kAuNP = kAu is attained when θ = 1, that is, for a closed-packed assembly of AuNPs.18,24,25,37 At this point, it is important to note that this assumption is correct when no parallel pathways for the ET other than the AuNPs|ODT-SAM|Au(111) mediated transfer are taking place. If the binding of AuNPs to the SAM provokes a significant disruption of the monolayer ordering or there is a direct contact between the particles and the gold substrate, then the penetration of redox molecules through pinholes and/or collapsed sites could also give similar electrochemical responses. In this sense, Gooding et al.25 have unambiguously shown that the nanoparticles are directly positioned on the distal end of amine-terminated alkanethiol SAMs of different length. On the other hand, many recent studies have reported that ET remains unaffected by the thickness of the linker inserted between the electrode and the NPs if charging of NPs is induced by redox species in solution.5,23,24,34,61 Moreover, it has also been concluded that the ET between the redox species and the AuNPs is the rate-limiting step with a heterogeneous apparent rate constant for each individual “nanoelectrode” 5,18,37 similar to that of the bulk gold electrode (kapp This Au ). mechanism implies that the charge transfer step from the Fermi
Figure 4. Impedance (Nyquist) plots in 2.5 mM K3Fe(CN)6 + 0.1 M KNO3 for an Au(111)|ODT-SAM modified electrode before (magenta squares) and after 16 h of immersion time in gold colloidal solutions of different κa. Nyquist plot of a bare single-crystal Au(111) electrode (black squares). Nyquist plots for bare gold and NPs ensembles adsorbed from solutions of κa 0.21, 0.4, and 0.5 are scaled up 4-, 12-, 6-, and 3-fold, respectively, for better clarity of their overall shape when compared to the remaining plots of higher charge-tranfer resistance.
Scheme 1. Typical Randles Circuita
a
The Cdl element corresponds to the surface double layer interfacial capacitance, while Rm, RAu, and RAuNP elements correspond to the heterogeneous redox charge-transfer resistances across the ODT-SAM, the bare gold, and the AuNPs ensemble, respectively. Rs and W elements correspond to the uncompensated solution resistance and the Warburg impedance associated to diffusion-controlled processes.
14621
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
densely packed arrangements of NPs on the ODT functionalized surface. Langmuir-type adsorption isotherms can provide a rough estimation of colloidal kinetics, in spite of more complex surface exclusion behaviors that might be present for such systems. The model is based on reversible molecular adsorption dealing with the exclusion of independent adsorption sites. In such a case, the Langmuir model approximation describes the adsorption kinetics for particles with negligible surface lateral interactions. Under this assumption, the time dependence of Γ and θ is given by the following equation:
level of AuNPs to the bulk metal surface must be greatly facilitated even in the presence of insulating SAMs. In a very elegant way, Allongue et al.62 have fully accounted for all these observations concluding that ET between two metals under an applied potential difference is intrinsically easier by many orders of magnitude than the transfer between a metallic surface and redox species in solution. Consequently, the metallic NP/SAM/bulk metal construct can effectively short circuit, and the potential is mainly applied to the external NP/solution electrolyte interface. This is confirmed even for low fractional coverage of metal NPs of a few nanometers in size or for any structure that increases the density of states (DOS) at the redox Fermi energy, and for very long alkyl chain molecular linkers independently of their electronic properties. Only very small NPs (around 1 nm), where size quantization effects become important, or extremely thick insulating SAMs ensembles may fall in the kinetics regime where NPs mediated ET is hindered.26,61,62 Therefore, we can confirm that the channeled AuNPs charge transfer to the Au(111) surface should be unaffected by the ODT insulating barrier under all the experimental conditions tested in this work. Furthermore, any structural change or disruption in the monolayer is not required to explain the trend observed in the ET recovery by both EIS and CV techniques. Figure 5 shows the time evolution of AuNPs number density, Γ, and fractional surface coverage, θ, as a function of the ionic
A = A max
kad [1 − e−(kad + kd)t ] kad + kd
(4)
where Amax would correspond to the number density of adsorption sites and kad and kd are the adsorption and desorption constants, respectively. Assuming that kd ≪ kad, when the desorption of AuNPs is neglected, then Amax corresponds to the number density of active sites (Γmax) or the maximum attainable fractional coverage (θmax), respectively, and kad is the pseudo-first-order rate constant for NPs adsorption.18 In general, Figure 5 shows that the experimental data are well fitted to eq 4, and the Γmax and kad values obtained by nonlinear curve fitting are gathered in Table 1. Table 1. Maximum Particle Density (Γmax), Adsorption Rate Constant (kad), and Interparticle Distance (d) Parameters As a Function of the Colloidal Solutions κa Used for NPs Assembly κa 0.21 0.40 0.50 0.62 1.23 1.95
Figure 5. Plot of the AuNPs number density, Γ, and fractional surface coverage, θ, as a function of adsorption time and the screening parameter, κa from 0.21 to 1.95. Solid lines account for the fitting of the experimental data to a Langmuir-type model. Inset: Enlarged view of experimental data and fitted curves for the colloidal adsorption kinetics at κa values of 0.21, 0.40, and 0.50.
Γmax (NPs·cm−1) (1.4 (2.4 (5.5 (2.2 (6.5 (2.8
± ± ± ± ± ±
0.2) 0.2) 0.4) 0.4) 0.3) 0.1)
× × × × × ×
9
10 109 109 1010 1010 1011
kad (s−1)
d (nm) 272 205 135 67 39 19
(1.1 (1.4 (1.6 (3.3 (5.6 (4.3
± ± ± ± ± ±
0.4) 0.4) 0.6) 1.8) 1.5) 0.5)
× × × × × ×
10−4 10−4 10−3 10−3 10−4 10−4
Considering the average interparticle distance (d) determined from the Γmax values obtained in this analysis and comparing with the behavior observed by CV, it can be concluded that the dynamics for the NPs mediated ET reflects a microelectrode-type behavior that evolves to a macroelectrode-type regime once the κa parameter values are higher than 0.5 (Figure S4, Supporting Information). Such a transition is also confirmed for κa > 0.50 as a function of the deposition time for AuNPs assembly indicating a nice agreement between CV and EIS measurements (Table S2, Supporting Information). Fermin et al.18 have reported an adsorption rate constant value of (3.3 ± 0.6) × 10−4 s−1 for 19 nm AuNPs electrostatically deposited onto surfaces functionalized with mercaptoundecanoic acid (MUA) and a positively charged poly-L-lysine electrolyte. Although slightly different experimental conditions were used in their study than in our case, the kad values calculated here are essentially of the same magnitude. The differences observed in the kad values (Table 1) are not correlated with changes of the AuNPs concentration in the solutions (Figure S3, Supporting Information). Thus, this behavior might be related either to an uneven homogeneity of the adsorption sites on the ODT-SAM or adsorption kinetics changes arising from ionic strength effects. This aspect will be
strength as determined by substituting the RAuNP values obtained from EIS data fitting in eq 3 (Table S2, Supporting Information). A rapid increase at shorter times followed by a transition region where the deposition rate decreases asymptotically up to where the surface coverage levels off is observed. Under these conditions, the adsorption of AuNPs becomes limited by surface exclusion effects. Hence, interactions among immobilized AuNPs become important because of the influence of electrostatic and/or entropy steric effects, especially at high coverages, for what submonolayer decorated surfaces are typically encountered. With increasing κa parameter, the maximum coverage values become markedly larger, in agreement with the DLVO theory that takes into account that the effective particle radius is shortened due to the screening of the double layer electric field at the surroundings of every NP. Such screening effect gives rise to weakened repulsive interactions and smaller average interparticle distances, which indeed leads to an overall higher Γ and more 14622
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
treated in the following section by a further analysis based on a random sequential adsorption (RSA) model. Film Distribution and Kinetics of AuNPs Colloidal Adsorption: An AFM and Electrochemical Comparative Study. We have first approached the adsorption kinetics of small colloidal particles by employing a Langmuir-type model as previously described for similar systems by Fermin et al.18 However, an alternative explanation of the adsorption of the particles is also given by a random sequential adsorption (RSA) model.63 In this framework, particle deposition is explained as a nonequilibrium process of noninteracting bodies that are placed at random sites onto a uniform planar surface. Then, particles considered like hard-disks or spheres are sequentially placed at the available surface sites left by the already deposited particles. Accordingly, deposition of monodisperse particles is only governed by geometric exclusion effects, where the maximum fractional coverage attainable at infinite adsorption times is determined by the jamming limit, θjam = 0.547.63 The RSA model has been modified to take into account experimental parameters affecting the adsorption kinetics and the predicted θjam fractional coverage. Therefore, experimental conditions such as pH,64 ionic strength,43−47 external deposition forces,43,45,47 particle or surface charges,64,65 and particle size or polidispersity45−47 have been demonstrated to be influencing parameters in the particle−particle43−45 and particle−surface interactions45,64−66 that may play a crucial role in controlling the deposition kinetics and θmax. Here, we will focus on the study of the influence of longrange repulsive electrostatic interactions of AuNPs in the low nanometer size range over its surface spatial arrangement by changes in the ionic strength of the colloidal solution. When the localized adsorption of charged NPs takes place, the RSA model must be modified to account for the lateral electric double layer interactions between particles, where the hard sphere radius, a, is replaced by an effective soft sphere radius, aeff, larger than their actual size.21,42,44,48 As a result, the extent of the interparticle Coulomb repulsion relates to the thickness of the electrical double layer, i.e., the Debye length, κ−1, which allows tuning the particle separation and θmax below θjam. Hence, a substantial increase of the distance of closest approach within NPs and rather low θmax can be achieved upon decreasing ionic strength, I, and thus, for an increase of κ−1. This effect becomes significant when κ−1 is larger than the particle radius a (κa < 1). Therefore, it is worth noting that small particle sizes (a < 50 nm), like those used in this study, are desirable to overcome the experimental difficulty of preparing very low ionic strength solutions (I < 10−4 M) with the required accuracy to access to low θ values typically below 0.1.43,44,47 We have used atomic force microscopy (AFM) to study the spatial distribution of the NPs assemblies as a function of the screening parameter κa. The upper limit corresponds to unstable solutions of 13 nm AuNPs deposited at κa = 1.95 (I = 8.35 mM). Figure 6 shows tapping-mode AFM images acquired under ambient conditions for the AuNPs assemblies prepared in the same conditions as those used for the electrochemical characterization. Γ was estimated from digital analysis counting at different sample’s areas (Table 2). Because the particle size and AFM tip radius are of the same order of magnitude, convolution effects lead to an apparent enlargement of the size of the imaged particles. The height profiles of the AFM images reveal that particles adsorb preferentially to the
Figure 6. AFM images of AuNPs assembled onto functionalized ODTAu(111) from colloidal solutions with different screening parameters κa: (a) 0.21 and t = 15 min, and (b−f) 0.21, 0.4, 0.5, 0.62, 1.95, respectively, where saturation coverage was obtained after t = 16 h. Areas of aggregated AuNPs with height profiles larger than 20 nm are surrounded by black circles.
Table 2. Maximum Particle Density (Γmax) and Fractional Surface Coverage (θmax) of Assembled AuNPs and Effective (aeff) and Hydrodynamic (ap) Radii Parameters As a Function of κa κa 0.21d 0.40 0.50 0.62 1.23 1.95
Γmaxa (NPs·cm−2) (1.9 (2.1 (5.2 (2.5 (6.0 (1.1
± ± ± ± ± ±
0.2) 0.4) 0.8) 0.3) 0.9) 0.2)
× × × × × ×
109 109 109 1010 1010 1011
θmaxa/θmaxb
aeffc/apb (nm)
0.0025/0.0025 0.0028/0.0038 0.0069/0.0080 0.033/0.033 0.080/0.099 0.146/0.157e
47/37 31/32 27/21 23/14 16/10 13/9
AFM measurements. bLimiting values of θ and ap for diffusioncontrolled deposition transport conditions obtained by extrapolation and linear regression of EIS data, respectively. cEffective radius of soft gold spheres obtained from the RSA model by numerical solution of eqs 5−7. dΓ15 min = (3.2 ± 0.5) × 108 NP·cm−2. eCorrected value. a
surface in monolayer coverage for κa < 0.62 (FigureS5a, Supporting Information). However, for κa > 0.62, the accuracy of the analysis becomes limited due to the deposition of layers formed not only by isolated particles, but also by doublets and larger cluster areas of 14623
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
aggregates according to their height profiles (FigureS5b, Supporting Information). In such cases, simple counting of cluster grains clearly underestimates the number of individual particles attached to the surface in the aggregated areas (Figure 6f). Then, equivalent Γ values of the particles directly bound to the surface were calculated from the total projected area (Atc) of the aggregated regions and that occupied by an individual particle (ANP = πa2/2). This approach should deliver good results within a 10% error for a low polydispersity of the individual NPs size distribution.44 Nonetheless, a slight coverage overestimation should be assumed even though the contribution of the convolution effects between the tip and large aggregates, possibly formed by an attached innermost layer of closely arranged individual particles, would be less significant.45 It is clearly shown in Table 2 that θmax increases with κa in agreement with the DLVO theory. Moreover, the values are well below θjam as predicted by the RSA model when the particles are treated as interacting soft spheres. Such interactions can be evaluated by solving the Poisson− Boltzmann equation, but two interacting particles cannot be solved analytically and approximations are needed. In our case, we have discarded the low surface potential approximation because citrate AuNPs have been described to possess a high surface potential ranging from 80 to 130 mV.21,67,68 Then, the approximations based on a far field effective potential or the sum of repulsive electrostatic interactions formulated by Sader49 and Ohshima,50 respectively, are perfectly valid and used here because of their accuracy for all values of κa. The analytical expression for the double layer particle−particle repulsive interaction potential, Upp(r), is given by ⎛ 4πεε γkTa 2 ⎞ 1 o ⎟Y 2 e−κ[(r / a) − 2] Upp(r) = ⎜ 2 e ⎝ ⎠ r
⎛ yp ⎞ Y = 8 tanh⎜ ⎟ ⎝4⎠
Figure 7. Dependence of the saturation coverages, θmax, obtained from AFM and EIS data with κa. The solid line represents θmax calculated from eqs 5−7 by assuming a modified RSA model based on soft spheres with an effective radius aeff. Corrected θmax from EIS data is included for extensive regions of aggregated NPs at the surface (dark yellow scatter symbol).
uppermost layers of the large clusters that would be also able to mediate the ET response at the ensembles. This extra coverage is not accounted for in the analysis of AFM data, as in that case, the projected area equivalent to a single layer of NPs was only considered. A rough estimation of the extra particle density for larger clusters (34% of the total covered area for κa = 1.95 from AFM analysis), with an average grain size of 50−60 nm, can be made by assuming that directly channeled ET or electron hoping take place from all the individual NPs in the multilayer patches, even though they were not in close contact with the functionalized surface.24 When this contribution is subtracted to account only for a single layer of attached AuNPs, the corrected θmax amounts to a similar value to that found for AFM data and predicted by the RSA model (see Figure 7 and Table 2). Such agreement between the RSA model and the experimental data would give rise to an apparent controversy, that is, the θmax attainable would be more similar for a layer of individual particles than for a modal distribution of particles and clusters different in size. This could be explained on the basis of a constant ψp, where θmax are mainly determined by spatial exclusion effects as is demonstrated by the qualitative similarities reported between the universal κa curves for different types of particles, i.e., gold, polystyrene, and silica, and sizes ranging from 13 to 530 nm.69 In other words, if clusters of 50−60 nm average in size and ψp = −140 mV were only present in the colloidal solution (κa = 9), then θmax would yield a value of 0.38 for the RSA far-field potential approximation, but due to exclusion effects θ only achieves a value of 0.05, which is limited by the competitive surface coadsorption with smaller particles of 13 nm (θ = 0.093). This eventually leads to the aforementioned modal distribution of particles (Figure 6f) with a total θmax = 0.143 equiv to that expected for the adsorption of individual NPs. As is illustrated in Figure 6f, both individual particles and aggregates deposited at the surface appear to be randomly distributed upon their adsorption. Then, independently of the size of the particles, the sites available at the surface and the AuNPs surface potential seem to be the determining factors here for the attainable θmax predicted by the RSA theory for long-range repulsive interactions and relatively large particle separations (low θ). Similarly, Adamczyk et al.70 reported that an increase of preadsorbed small polystyrene particles resulted in a considerable decrease in adsorption rate of larger ones, so their surface coverage attained after a long time becomes much lower than that expected for uncovered surfaces. This behavior has been properly interpreted by the electrostatic repulsion between small and large particles according to the 2D RSA
(5)
1 1+
1−
2κa + 1 (κa + 1)2
yp
()
tanh2
4
(6)
where r is the center-to-center distance between particles, yp = ψp(e/kT) the dimensionless particle surface potential, and γ is a constant (1 < γ < e). The distance between particles, r, when Upp drops below the thermal energy, kT, and repulsive interactions start to compete with the Brownian motion of the particles, can be calculated numerically by solving eqs 5 and 6 as a function of the dimensionless screening parameter κa, for a fixed surface potential value, ψp. According to the RSA model and considering that r = 2aeff, being aeff is the effective hard sphere radius expanded due to the electric double layer particle interactions, then θmax relates to aeff as follows: θmax
⎛ a ⎞2 = θjam⎜ ⎟ ⎝ aeff ⎠
(7)
In Figure 7, θmax calculated numerically from eqs 5−7 for ψp = −140 mV is plotted (solid line) versus κa. As can be observed, the experimental data obtained from AFM and EIS measurements nicely fit to the calculated values. This ψp value also agrees with that reported by Poelsema et al.21 for nanocolloidal gold particles 13 nm in diameter electrostatically deposited on APTES-derivatized Si/SiO2 substrates at κa ≥ 1. The higher θmax determined by EIS at κa = 1.95 might be associated with the extra contribution of AuNPs in the 14624
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
be experimentally determined from the slope of θ(t) vs t1/2 representations by linear regression of the data. To calculate the average diameter of particles, dp, eq 9 can be obtained by substituting the diffusion coefficient, D, for the Stokes−Einstein formula, and the mass, mp, for the equivalent diameter of a AuNP with spherical shape:
model by considering the concept of a steric barrier. In the same argumentation line, when polydisperse solutions are employed, Semmler et al.46 have also described that although the size distribution of the deposited particles changes with time, and whereby the small particles are adsorbed preferentially, rather similar θ vs t plots were obtained for both monodisperse and polydisperse samples confirmed by RSA simulation. In spite of this being out of the scope of this work, additional adsorption experiments would be needed to corroborate this observation by means of controlling the relative concentration and size of the clusters in the colloidal solution, in order to check if any change arises in the 2D size distributions without altering θmax for a fixed ionic strength. Finally, relying on the good agreement observed in θ obtained by the AFM and EIS techniques, the kinetics of particle adsorption at different ionic strengths was evaluated according to the diffusional RSA model by using the EIS data. During the early stages of the adsorption process, surface exclusion effects do not operate. Thus, in the absence of convective transport, the growth of the layer is hence limited by diffusion up to θ increases significantly and blocking effects cannot be neglected anymore. Under these conditions the dependence of the surface concentration of particles, Γs, with time can be expressed by eq 8: Γs(t ) 2 = Cb mp
Dt π
1/7 ⎛ ⎞2/7 12 ⎟ ⎛ kT ⎞ ⎜ dp = ⎜ 2 ⎟ ⎜ ⎟ ⎝ ρp π SD ⎠ ⎝ 3η ⎠
(9)
where ρp = 19.3 g/cm3 is the density of the gold core, η = 0.01 g/cm·s is the water viscosity, T = 298 K, and SD = Δ(Γs/Cb)/ Δt1/2, the slope of the dependence of Γs or θ normalized by Cb on t1/2. Recently, this approach has been successfully accomplished for AgNPs assembled on polyelectrolyte modified surfaces by using direct methods such AFM and SEM to determine dp.71,72 The SD values and hence the “dynamic” diameter of the particles, dp, have been found to be independent of the NPs weight concentration (Cb) and the ionic strength of the colloidal solutions, which has also been confirmed by measurements of the hydrodynamic radii of the particles by dynamic light scattering (DLS) or spectroscopic techniques.43,44,71−73 However, Poelsema et al.74 have found that the diffusion coefficient, D, and the rate constant of adsorption for nanocolloidal gold are much lower than that reported for other particle systems in accordance with the Stokes−Einstein relation. They assumed that the underestimation of D might be related to the large surface charge of the gold colloids which would lead to a higher hydrodynamic radius (ap = dp/2) than that predicted by the Stokes−Einstein formula. As illustrated in Table 2, such an assumption would perfectly agree with the qualitative parallel trend observed for the hydrodynamic radii ap = dp/2 and the effective radius aeff with the ionic strength. In fact, when the electric double layer of the colloids is more efficiently screened (κa = 1.95), dp tends to fit with the AuNPs core diameter (13 nm), even though the presence of particle aggregates of bigger size can also contribute to slightly increase the calculated dp mean value. Unfortunately, as far as we know, there are no systematic studies by DLS of the hydrodynamic AuNPs radius as a function of the ionic strength that would help to obtain insight into these observations. Therefore, the origin of this difference in behavior still remains unclear and would need further investigation. Besides determining particle size, deposition kinetics provides a way to obtain practical parameters, such as Γmax or θmax (data included in Figure 7). As is shown in Figures 5 and 8, the adsorption rate does not remain constant at times higher than 1 h, and gradually decreases as θ slowly approaches a saturation value. Under these circumstances, the RSA model predicts a linear dependence of θ on t−1/2.43,45 Then, a linear extrapolation of θ when t−1/2 → 0 (t → ∞) would allow the determination of θmax. This method can be used to avoid excessively long deposition time experiments. This is strictly valid when transport is controlled by forced convection and the thickness of the diffusion layer is of the order of the particle diameter. Then for small particles, low coverages, and nonconvective controlled transport, a deviation from the RSA model should take place. In such a case, the bulk flux is supposed to decrease indefinitely with t−1/2 and therefore, θ would not be linear on t−1/2 but approximately proportional to
(8)
where D is the diffusion coefficient, Cb is the weight concentration of particles in the bulk solution (g/cm3), and mp is the mass weight of a single AuNP. Hence, eq 8 predicts that Γs(t) and, therefore, θ(t) = Γs(t)/πa2 are linearly dependent with t1/2. This relationship was verified in Figure 8a at short adsorption times (t < 1 h). Relevant information, such as particle size, can be straightforwardly extracted from the kinetics measurements. An estimation of AuNPs diameter can
Figure 8. Kinetics of AuNPs adsorption on ODT modified Au(111) surfaces determined by EIS measurements for a bulk weight particle concentration Cb = 1.38 × 10−4 g/cm3 and different ionic strengths, κa: (dark green) 1.95, (pink) 1.23, (blue) 0.62, (light green) 0.50, (red) 0.40, and (black) 0.21. (a) Dependence of surface coverage, θ, on t1/2. Dashed and solid lines (inset) denote linear regression fits of the data for t < 1 h. (b) Dependence of θ on t−1//2. Dashed and solid lines (inset) denote a nonlinear (parabolic) dependence of θ for long adsorption times (t > 1 h). 14625
dx.doi.org/10.1021/jp502692q | J. Phys. Chem. C 2014, 118, 14617−14628
The Journal of Physical Chemistry C
Article
t−1/4.45 Such behavior resembles that experimentally observed in our case under nonforced transport conditions, where a nonlinear dependence of θ on t−1/2 is found for longer times (t > 1 h). In summary, EIS measurements provide a useful and convenient electrochemical tool to evaluate the AuNP surface coverage and adsorption kinetics of colloidal systems in a simple way. The extent of the validity of the results of the electrochemical method has been directly explored by AFM with a reasonable agreement between both techniques, even for low coverages (
