Spectral Response of Plasmonic Gold Nanoparticles to Capacitive

May 23, 2017 - *E-mail: [email protected]., *E-mail: [email protected]., *E-mail: ... Hoener, Byers, Heiderscheit, De Silva Indrasekara, Hoggard, Chang, ...
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Spectral Response of Plasmonic Gold Nanoparticles to Capacitive Charging: Morphology Effects Benjamin S. Hoener,† Hui Zhang,‡ Thomas S. Heiderscheit,† Silke R. Kirchner,† Agampodi S. De Silva Indrasekara,† Rashad Baiyasi,† Yiyu Cai,† Peter Nordlander,‡,§,∥ Stephan Link,*,†,‡ Christy F. Landes,*,†,‡ and Wei-Shun Chang*,† †

Department of Chemistry, ‡Department of Electrical and Computer Engineering, §Department of Physics and Astronomy, and Materials Science and Nanoengineering, Rice University, 6100 Main Street, Houston, Texas 77005, United States

∥

S Supporting Information *

ABSTRACT: We report a study of the shape-dependent spectral response of the gold nanoparticle surface plasmon resonance at various electron densities to provide mechanistic insight into the role of capacitive charging, a topic of some debate. We demonstrate a morphology-dependent spectral response for gold nanoparticles due to capacitive charging using single-particle spectroscopy in an inert electrochemical environment. A decrease in plasmon energy and increase in spectral width for gold nanospheres and nanorods was observed as the electron density was tuned through a potential window of −0.3 to 0.1 V. The combined observations could not be explained by existing theories. A new quantum theory for charging based on the random phase approximation was developed. Additionally, the redox reaction of gold oxide formation was probed using single-particle plasmon voltammetry to reproduce the reduction peak from the bulk cyclic voltammetry. These results deepen our understanding of the relationship between optical and electronic properties in plasmonic nanoparticles and provide insight toward their potential applications in directed electrocatalysis.

T

approximation, the Drude model was applied to quantify spectral shifts due to charge density change in the nanoparticles under electrochemical potentials. This model predicts that the LSPR energy decreases as electron density in the nanoparticle is decreased,15,16,27,44,45 matching previous experimental observations in both aqueous15,19,27 and nonaqueous21 electrolyte solutions. However, the fwhm is predicted to decrease as charge density is decreased, in contrast with several experimental reports.21,32,37 In addition, several experimental groups have demonstrated an increase in scattering intensity as charge density is increased, inconsistent with the predictions by the Drude model.19,21,32 To explain this discrepancy, the Dahlin32 and Atwater37 groups introduced a modified dielectric layer at the nanoparticle surface to account for the surface damping and refractive index change induced while applying an electrochemical potential. However, those measurements were performed at the ensemble level, which includes inhomogeneous broadening of the spectra due to the size and shape heterogeneity inherent in chemically synthesized nanoparticles.46 More recently, Borisov and co-workers demonstrated theoretically that the increase of the electron density results in an enhancement of electron spill-out, leading to a red shift of the plasmon energy,18 opposite to the observed experimental trends. To resolve these disagreements between the exper-

he localized surface plasmon resonances (LSPR) of metallic nanoparticles have attracted great attention for many energy applications including photovoltaic cells,1 photocatalysts,2−8 and electrocatalysts.9,10 In addition to efficient light absorption due to the LSPR, metallic nanoparticles provide a larger surface-to-volume ratio compared to flat surfaces and achieve higher selectivity and activity during catalytic reactions.11−13 Under application of an electrochemical potential, the LSPR can be modified in several ways, e.g., by tuning the Fermi energy of the nanoparticle,14−21 solvent polarizability,22 ion adsorption,19,23−26 and chemical reactions.19,26−31 Owing to the high optical sensitivity of the LSPR to electron density, chemical damping, and refractive index changes,15,19,23−26,32−34 it is possible to monitor physical and chemical processes on the surface of the electrocatalysts by probing the spectral change of the nanoparticles, e.g., resonance energy, full width at half-maximum (fwhm), and peak intensity. Such spectroelectrochemical measurements can have advantages compared to conventional electrochemical approaches because of the simplicity of measuring photons compared to the more difficult task of quantifying electron-transfer events at single-nanoparticle electrodes.35,36 Spectroelectrochemical measurements have been performed to monitor electrochemical processes of plasmonic nanoparticles at both ensemble23,32,37 and single-particle levels.15,16,19,24,26,28,29,33,34,38−41 Capacitive charging,15,17,19,21 ion adsorption,19,23,26,32 and other redox reactions14,24,27−30,33,34,42,43 were previously investigated. As a first © 2017 American Chemical Society

Received: April 18, 2017 Accepted: May 23, 2017 Published: May 23, 2017 2681

DOI: 10.1021/acs.jpclett.7b00945 J. Phys. Chem. Lett. 2017, 8, 2681−2688

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The Journal of Physical Chemistry Letters

Supporting Information and Figure S1 for sample preparation). The ferrocyanide redox couple was used to calibrate the reference electrode (Figure S2). The consistency of the ferrocyanide redox couple and AuxOx reduction peak (Figure S3) in the bulk CV curve over multiple cycles demonstrates the stability of the quasi-reference electrode. The scattering spectra of single AuNRs were measured using a home-built singleparticle dark-field microscope equipped with a spectrometer and CCD camera which was synchronized with the potentiostat (see Methods in the Supporting Information). Single-nanoparticle measurements were employed to remove inhomogeneous broadening of the line width always present in ensembles of chemically prepared samples due to size and shape heterogeneity.46 At positive potentials, the scattering spectra of a single AuNR showed a decrease in energy (Figure 1b) arising from capacitive charging and oxidation of the Au surface. For AuNRs in 100 mM NaF electrolyte, the electrochemical reaction that occurs at the lowest positive potential is adsorption of hydroxide/water and oxidation of the gold surface.31,47−50 Previous work using electrochemical shellisolated nanoparticle-enhanced Raman spectroscopy has shown that for a pH 6 electrolyte solution,31 a AuO stretching mode from ∼520−580 nm appears at ∼0.20 V relative to our calibrated quasi-reference electrode (Figure S2). The formation of AuxOx changes the local refractive index around the AuNR and shifts the plasmon spectrum.19,26,32,33 Therefore, the oxidation reaction can be tracked by the spectral changes in the LSPR. Several groups have reported electrochemically produced AuxOx on a gold film at a potential of 1.2−1.6 V and estimated a AuxOx thickness of 0.4−1.1 nm.51 We expect the AuxOx layer should be less than 1 nm thick around the AuNRs because the applied potential was smaller than 0.7 V in our experiment. By determining the potentials where the oxidation reaction occurs and the associated spectral features for single AuNRs, we can identify which spectral changes are due to only capacitive charging. Figure 1 shows the spectral changes of the same AuNR as the maximum potential of a CV scan was increased. In the bulk CV (Figure 1c), Faradaic current was observed at positive potentials and a reduction peak at 0 V appeared during cycles to higher positive potential ranges. The reactions observed in the bulk CV were correlated with changes in the single-particle spectra. The change of resonance energy (ΔEres, Figure 1d) decreased and the change of fwhm (ΔΓ, Figure 1e) increased slowly at ∼0.2 V in the negative to positive direction, corresponding to anion adsorption−gold oxidation consistent with previous reports.31,47−50 The oxidation current in the bulk CV was due to the reaction on the AuNRs but also the onset of oxygen evolution reactions,52 as shown in Figure S4. In the positive to negative direction, ΔEres increased (Figure 1d) and ΔΓ (Figure 1e) decreased sharply over a very small potential range (0.1−0 V) which matched the sharp AuxOx reduction peak in the bulk CV (Figure 1c and Figure S4). This result agrees with previous studies measuring gold oxidation in nonreactive electrolyte solutions where a sharp reduction peak is observed in the bulk CV compared to a broad oxidation shoulder.31,49,50 The different rate and potential for the oxidation and reduction lead to a hysteresis, which became larger at more positive potentials shown in Figure 1d,e. However, no AuxOx reduction or hysteresis were observed in the potential range of −0.3−0.1 V (magenta lines in Figure 1c− e). Therefore, at potentials higher than ∼0.2 V, we observed the

imental and theoretical studies, and, more importantly, to reveal the physical picture of pure electron charging, single-particle measurements and an improved theory are needed to fully understand the optical response of the plasmon to the change of electron density in the nanoparticle within the pure charging regime. In this work we measured the optical response of gold nanospheres (AuNSs) and gold nanorods (AuNRs) of different size and shape due to capacitive charging, which was achieved using a low applied potential window (−0.3−0.1 V) and a nonreactive electrolyte (100 mM NaF). Increasing LSPR energy and decreasing spectral line width were observed with increasing electron density as a more negative potential was applied, while the opposite trend was observed as the potential was increased. A larger energy shift was seen in smaller volume compared to larger volume AuNRs within the same potential range. These experimental results can be explained by a pure nanoparticle charging effect within a quantum mechanical approach. Additionally, the redox reaction of gold oxide was probed by the changes in the resonance energy and fwhm of a single AuNR using single-particle plasmon voltammetry (spPV), reproducing the reduction peak from the bulk cyclic voltammetry (CV). In order to directly compare spectral changes due to capacitive charging only, we first determined the potential at which Au oxidation occurred in our system. The scheme of the electrochemical cell is displayed in Figure 1a where AuNRs on an ITO substrate, a Pt wire, and an insulated Pt wire were used as working, counter, and quasi-reference electrodes, respectively, all connected to a potentiostat (see Methods in the

Figure 1. (a) Spectroelectrochemical cell diagram with indium tin oxide (ITO) coated working electrode (purple), Pt wire counter electrode (silver), insulated Pt quasi-reference electrode (red), and 100 mM NaF electrolyte solution. Au nanoparticles were deposited on the ITO surface. (b) Single AuNR scattering spectra at working electrode potentials: 0.0 (blue), 0.3 (orange), 0.5 (yellow), and 0.7 V (purple). (c) Bulk current from working electrode cycling from −0.3 V to +0.1 V (magenta), + 0.4 V (blue), + 0.5 V (green), + 0.6 V (red), and +0.7 V (black). (d) ΔEres and (e) ΔΓ of a Lorentzian fit to the scattering spectra of the same AuNR averaged over 3 cycles as a function of applied potential with the same color code as in panel c. The arrows indicate the potential scan direction. Shaded areas indicate standard error. 2682

DOI: 10.1021/acs.jpclett.7b00945 J. Phys. Chem. Lett. 2017, 8, 2681−2688

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The Journal of Physical Chemistry Letters effects of AuNR oxidation on the LSPR, which was then reduced at ∼0 V. In order to study the optical response of Au nanoparticles to capacitive charging, we used AuNRs and AuNSs and limited the maximum potential to 0.1 V (based on results shown in Figure 1) to avoid oxidation. Figure 2a shows experimental spectra at −0.3 and 0.1 V for a AuNS (red) and a AuNR (blue). The distinct differences in peak resonance energy and line shape of

the scattering spectra of the AuNRs and AuNSs were used to separate the two populations within the same cell, but they were also verified by correlated scanning electron microscopy (SEM) analysis (Figure S5). The Lorentzian fits of the AuNS peak (Figure 2b) and the AuNR longitudinal mode (Figure 2c) demonstrate that very small shifts in peak resonance energy (dotted lines) on the order of a few millielectronvolts can be detected using this method. It is important to note that such sensitivity and reproducibility is possible only by comparing spectral changes within the same cell, which eliminates the possibility of small potential differences due to slight variations in cell geometries. Comparing ΔEres and ΔΓ for a single nanoparticle with the corresponding bulk CV demonstrates that the spectral changes from −0.3 V to +0.1 V are primarily due to capacitive charging. ΔEres of an example AuNR (blue) averaged over 3 cycles (Figure 2d) showed no hysteresis and was linear, in contrast with the large, nonlinear ΔEres caused by chemical reactions on the nanoparticle surface (Figure 1). Additionally, compared to the strong increase in ΔΓ caused by chemical interface damping during redox reactions (Figure 1e) at oxidative conditions, a much smaller increase of only around 1 meV was observed from −0.3 V to +0.1 V (Figure 2e). Finally, no redox peaks were present in the bulk CV (Figure S6) at these smaller positive potentials. Reversible tuning of the plasmon resonance and fwhm was achieved for single AuNRs and AuNSs as the electron density was tuned via the applied potential (Figure 2d,e). As the potential was shifted to positive values, the electron density within the AuNSs and AuNRs decreased because of lowering of the Au Fermi level.17 Importantly, a slight increase in fwhm was observed when applying a positive potential (Figure 2e). Although small, ΔEres and ΔΓ due to capacitive charging for AuNSs and AuNRs were consistent for a large number of nanoparticles. Hyperspectral images27 (see Methods in the Supporting Information) of a AuNS/AuNR sample were taken at −0.3 and +0.1 V. Peak energy and fwhm of individual nanoparticles at 0.1 V were subtracted from those at −0.3 V to determine ΔEres and ΔΓ. The cumulative distribution functions in Figure 2f,g show that for a sample size consisting of 352 AuNRs and 1013 AuNSs, the mean ΔEres was 2 ± 1 meV for the AuNRs and 1 ± 2 meV for the AuNSs. The mean ΔΓ was −1 ± 5 meV for AuNRs and −2 meV ± 10 meV for AuNSs. While most particles fall within the range expected based on the example single-particle results, the cumulative distributions demonstrate that some nanoparticles exhibit much larger resonance changes over the same potential range. As previously demonstrated,27 heterogeneity in reactivity between nanoparticles means that a small population of AuNRs could be oxidized even at low positive potentials. The experimental trends in energy shift and fwhm shown in Figure 2 are not consistent with the Drude model. The optical response of AuNSs and AuNRs to change in electron density was simulated using Mie theory55 (Figure S7) and the finite element method (Figure S8). The Johnson and Christy53 data set modified using the Drude model was used to obtain the permittivity of gold as a function of electron density in the simulations. The simulated ΔEres increase with increasing electron density was consistent with our experiments (Figure 2d,f). However, the predicted fwhm increase with increasing electron density was opposite from the experimental results. While the discrepancy between the Drude model predictions and experimental fwhm trends have previously been attributed

Figure 2. (a) Scattering spectra of single 94 × 41 nm AuNRs (blue) and 65 nm AuNSs (red) with applied potential at +0.1 V (light color) and −0.3 V (dark color). (b, c) Lorentzian fit to the spectra in panel a for a single AuNS (b) and a single AuNR (c) at +0.1 V (light) and −0.3 V (dark). Dotted lines indicate peak resonance energies. (d, e) ΔEres (d) and ΔΓ (e) for a single AuNS (red) and AuNR (blue) averaged over 3 cycles. Shaded areas correspond to the standard error. (f, g) Cumulative distribution functions for ΔEres (f) and ΔΓ (g) for 1013 AuNS (red) and 352 AuNRs (blue) measured hyperspectrally between −0.3 V and +0.1 V. 2683

DOI: 10.1021/acs.jpclett.7b00945 J. Phys. Chem. Lett. 2017, 8, 2681−2688

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The Journal of Physical Chemistry Letters to interface damping by electrolyte ion interactions,19,23,24,32 the damping should be minimized in our experiments because only a low concentration of a nonreactive electrolyte (100 mM NaF) at mild electrochemical potentials was used and no reactions were observed in the bulk CV (Figure S6). In addition, the experimental results show that ΔEres for the AuNRs is larger than that for AuNSs. Theory based on the Drude-modified permittivity predicted the opposite trend, resulting in larger ΔEres for the AuNSs (see analytical solution in the Supporting Information). Therefore, we must conclude that simulations using the Drude-modified permittivity are not sufficient to explain the optical response of single plasmonic nanoparticles due to capacitive charging. To understand the experimental results we clearly have to go beyond a simple classical Drude model. The conventional quantum mechanical method for the calculation of optical properties of small nanostructures are the time-dependent density functional theory (TDDFT) or the time-dependent local density approximation (TDLDA) which are equivalent for linear excitations. These approaches have been extensively used to calculate the optical response of small nanoparticles54−56 and generally give absorption spectra in excellent agreement with experimental results.54,55 However, in both approaches the line widths of the optical resonances are not calculated, but input parameters are chosen to fit the measured peaks. In order to account for both optical response parameters Eres and Γ, we therefore have to go beyond TDDFT. Here we used a semiclassical approach (SCA) derived rigorously from the random phase approximation (RPA) in the limit where the frequency of the incident light is larger than the single-particle excitation energies of the system.57,58 This approximation is valid in the case of gold nanoparticles for frequencies below the interband transition threshold. In the SCA, the optical response is expressed in terms of the equilibrium electron density distribution of the nanoparticle. The widths of the plasmon resonances are determined by the electron density profile around the surface of the nanoparticle. For a classical stepfunction density profile, the approach yields plasmon resonances in perfect agreement with a classical Drude model. For a realistic evanescent density profile, the surface plasmon samples regions of different electron density resulting in a broadening of the mode. The SCA has successfully been used in several applications ranging from atoms to composite nanostructures.57−60 Here we focus on the charging effect on the optical response of nanoparticles and neglect dielectric background and substrate effects in our calculations. The SCA absorption cross section as a function of frequency, ω, for a spherical AuNS is obtained from σabs(ω) =

2π ω Im α(ω + i0+) c

4πe 2ρ (r )

where ωp2(r ) = m0 is the local plasma frequency with e and m being the electron charge and electron mass, respectively. ρ0(r) is the local charge density at radial position r, and the Coulomb Green function is given by θ(r − r ′)r ′ θ(r ′ − r )r where θ(r − r′) is a step G(r , r′) = + r3 r ′2 function. The smaller intrinsic damping with higher electron density at the AuNS surface originates from the narrower plasmon energy distribution predicted by the SCA. In the classical approach, the charges are uniformly distributed inside a nanoparticle and drop abruptly to zero at the boundary (Figure 3a, black line). The

Figure 3. (a) Positive background distribution (black) and electron density distribution (red) for a 4 nm diameter nanoparticle. (b) Physical origin of broadening introduced by the SCA. (c) Accumulated electron density distribution Δn(r) as a function of r when the charging ratio α varies from 95% to 102% (from bottom to top). (d) Electron density distribution with α = 95% (cyan) and 100% (red). (e) TDLDA absorption spectra for α from 95% to 102% (following the arrow direction) and (f) SCA absorption spectra for α ranging from 95% to 102% (following the arrow direction) from SCA. (g) SCA calculated ΔEres and (h) ΔΓ as a function of α.

corresponding absorption consists of one single resonance band ωsp (top panel of Figure 3b), as predicted by classical Mie theory.61 However, quantum mechanical effects such as electron spill-out and Friedel oscillations15 introduce a nonuniform electron distribution around the surface (Figure 3a, red line). Such a nonuniform distribution could in principle be viewed as a sequence of thin shells (bottom panel of Figure 3b), each of which has a distinct electron density. Thus, the dominant resonance, ωsp, would become surrounded by a series of side bands due to the individual shells, leading to finite broadening in the absorption spectra. A narrower spectral width is consequently expected for a steeper drop of the electron density across the boundary. The SCA, which includes such nonuniformity but does not require the introduction of a

(1)

where c is the speed of the light and 0+ is an infinitesimal positive number. The polarizability α(ω) can be written as α(ω) = −

∫0

∞

dr r 3 f (r , ω)

(2)

[ω 2 − ωp2(r )]f (r , ω) =−

2 1 dωp ⎡ d ⎢1 + 3 dr ⎣ dr

∫0

∞

⎤ dr′r′2 G(r , r′) f (r′, ω)⎥ ⎦

(3) 2684

DOI: 10.1021/acs.jpclett.7b00945 J. Phys. Chem. Lett. 2017, 8, 2681−2688

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The Journal of Physical Chemistry Letters sequence of shells, predicts narrower plasmon resonances for a steeper electron distribution drop at the surface (Figure S9). A negatively charged nanoparticle has a steeper electron drop across the boundary, leading to a narrower line width and higher energy in the absorption spectrum. Using our firstprinciples TDLDA approach,58 we simulated the electron distribution of a 4 nm diameter AuNS corresponding to different charging levels. To visualize the electron distribution for charged nanoparticles, we plotted the accumulated electron r density distribution, ΔN (r ) = ∫ [n(r′) − n0(r′)]r′2 dr′ (Fig0 ure 3c), where n(r) and n0(r) are the local electron density as a N function of charging. α = Ntot where Ntot is the number of

We further investigated the volume dependence of the optical response of AuNRs on the capacitive charging and found that smaller AuNRs exhibit a higher sensitivity to the applied potential. Large (94 × 41 nm) and small (49 × 22 nm) AuNRs of similar aspect ratio were mixed and deposited on an ITO substrate which was assembled into an electrochemical cell to avoid possible systematic errors due to comparing different cells. The scattering measurements show no hysteresis in ΔEres versus potential for a single AuNR (Figure S10), and no redox peaks were observed in the bulk CV (Figure S11), indicating spectral shifts were caused by capacitive charging only. Because the scattering cross section of the AuNR is proportional to the volume squared,62 the scattering intensities of the AuNRs were compared (Figure 4a, inset) to categorize AuNRs as having

0

electrons in the charged nanoparticle and N0 is the number of electrons in the neutral nanoparticle. The electron density for the neutral nanoparticle was taken as n0 = 1.0 × 1022 cm−3. Figure 3c demonstrates that the excess or depletion of electrons are mostly located inside the nanoparticle surface with a small portion contributing to spill-out. For the positively charged nanoparticles, the electron depletion induces a smaller amplitude electron density inside the nanoparticle, leading to a more gradual slope of the electron drop across the boundary. This result is explicitly shown in Figure 3d where the electron densities for a positively charged (95%) and neutral (100%) nanoparticle are compared. Figure 3e,f shows the calculated absorption spectra of the AuNS with an electron density ranging from 0.95 to 1.02 using TDLDA and SCA. The dispersion of the peak energies is essentially the same in both approaches and follows Ntot , as expected for plasmonic nanoparticles. As mentioned above, the TDLDA cannot predict the damping of the plasmon; therefore, the resonances obtained from the TDLDA have the same width. However, the SCA spectra display a clear narrowing of the plasmon resonance with increasing number of electrons. The calculated ΔEres and ΔΓ are plotted in panels g and h of Figure 3, respectively. The absorption exhibits an increasing ΔEres and decreasing ΔΓ with increasing electron density, consistent with the experimental observations shown in Figure 2. It is interesting to note that the negatively charged AuNSs exhibit both a higher electron density (Figure 3d) and a steeper electron density drop despite a larger spill-out effect compared to the neutral AuNS. The larger ΔEres and smaller ΔΓ for the negatively charged AuNS originates from these two effects, respectively. The increased electron density at the surface for a negatively charged nanoparticle is a universal effect due to Coulomb repulsion and is also consistent with the results from the Drude model. The shape of the induced electron distribution during capacitive charging does not depend on nanoparticle size. Previous results predicted a red shift and broadening of the plasmon band when the particles were negatively charged arising from larger screening charges on the nanoparticle surface due to electron spill-out.18 Our SCA calculation shows a clear blue shift of the plasmon spectrum because of an increased electron density despite a spill-out effect, in agreement with classic Mie theory calculations. Additionally, the SCA calculation shows that the electron distribution at the nanoparticle surface plays a crucial role in the broadening of the plasmon band for the charged nanoparticles. The most likely explanation for this inconsistency is the inability of the TDDFT approach to account for the broadening introduced by a nonuniform surface charge distribution.

Figure 4. (a) Change in resonance energy from −0.3 V to +0.1 V of small (22 × 49 nm, blue) and large (41 × 94 nm, red) AuNRs separated by scattering intensity. Correlated SEM (inset) demonstrates the scattering intensity is greater for large volume AuNRs (red) compared to small volume AuNRs (blue). (b, c) Change in resonance energy (b) and fwhm (c) from −0.3 to 0.1 V for large volume (red) and small volume (blue) AuNRs as a function of resonance energy at −0.3 V. The lines in panel b are least-squares fits of the data.

large and small volumes with peak intensities higher and lower than 0.2, respectively. This separation threshold was confirmed using correlated SEM imaging (Figure 4a, inset). To enhance the signal-to-noise ratio for the small AuNRs and reduce the error between measurements, single-particle chronocoulometry was employed (see Methods in the Supporting Information and Figure S12). ΔEres (−0.3 V vs 0.1 V) for large AuNRs (Figure 4a, red) was smaller compared to the value for small AuNRs (Figure 4a, blue). In the subpopulation sorted by volumes, 2685

DOI: 10.1021/acs.jpclett.7b00945 J. Phys. Chem. Lett. 2017, 8, 2681−2688

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The Journal of Physical Chemistry Letters ΔEres decreases with increasing resonance energy of neutral AuNRs for both the large (Figure 4b, red symbol) and small (Figure 4b, blue symbol) volume AuNRs. This observation indicates a larger energy shift for the AuNRs with larger aspect ratio, inconsistent with theoretical predictions using the Drudemodified dielectric permittivity of Au (analytical solution in the Supporting Information). Additionally, the slope of a linear fit to the data was greater for the small volume AuNRs (blue line) compared to the large volume AuNRs (red line). This result suggests that within the same potential window, ΔEres with respect to the change of aspect ratio is more sensitive for AuNRs with a smaller volume. Interestingly, while the change in resonance energy increased for smaller AuNRs, the change in fwhm was independent of size and aspect ratio for the AuNRs (Figure 4c). The small and large AuNRs had similar (1.0 ± 0.8 vs 0.9 ± 0.4 meV) decreases in fwhm at −0.3 V compared to 0.1 V. The size dependence of ΔEres arose from different charge densities for the same applied potential, confirmed by the SCA simulations. The size-dependent optical response to capacitive charging was performed using AuNSs with 4 and 6 nm diameters because the SCA currently is capable of modeling only spherical nanoparticles. Applying a voltage, Vext, induces charges located on the surface of the nanoparticle, changing the confining potential. For a charged metallic sphere, the induced change of the confining potential can be written as18,55 Q ΔV = − R ≅ Vext , where R denotes the radius of the nanoparticle and Q its excess charge. Hence, the accumulated charge on the surface scales linearly with the radius of the nanoparticle. The electron density of the nanoparticle is 1 therefore ∝ R2 causing a larger electron density variation for smaller nanoparticles for the same applied voltage and leading to larger ΔEres and ΔΓ (Figure S13). The R2 dependence of the charge density variation for a given applied voltage, Vext, is not universal, because it is derived from the induced potential of surface-located charges for a NS. For other shapes like NRs, such scaling laws may change. However, the conclusion of higher induced charge density change under applied potential for smaller nanoparticles remains independent of the shape. It is also noted that the measured fwhm change for AuNRs is similar for the different sizes of nanoparticles (Figure 4c), inconsistent with the prediction by the SCA. Because damping mechanisms for AuNRs are also size-dependent,63 additional line width increases due to charging in small AuNRs may be offset by contributions from radiation damping in large AuNRs. A more complex analysis and modeling considering radiation damping are required in order to fully understand this observation. Finally, we demonstrated spPV26 to monitor the oxidation and reduction of the AuNR surface. When oxidation reactions occurred at higher positive potentials, the sharp reduction peak of a single AuNR could be measured solely by changes in the LSPR. Figure 5 shows the spPV signal of a single AuNR compared with the bulk current from the ITO working electrode. The spPV signal is generated by taking the difference between adjacent resonance energy and fwhm measurements with a constant potential step (dEres/dV, dΓ/dV) during a CV scan. Because the reduction reaction causes such a sharp decrease in the resonance energy and fwhm (Figure 1), a peak is observed in the derivative for each cycle. The spPV peak was confirmed to be the single AuNR reduction peak by comparison to the reduction peak of the AuNRs in the bulk

Figure 5. dEres/dV (blue) and dΓ/dV (red) of a single AuNR compared to the bulk CV for the gold redox reaction. The peaks obtained using dEres/dV and dΓ/dV match well with the peak at ∼0 V in the bulk CV due to the reduction of AuxOx.

CV. While previous reports determined single-particle redox potentials by depositing the nanoparticles on a Au film,26,42 these results probed redox reactions using the optical signal from the electrocatalysts alone. In this work we investigated the optical response of Au nanoparticles of different size and shape due to oxidation reactions and capacitive charging by single-particle spectroelectrochemical measurements. Using AuNRs, a large nonlinear decrease in LSPR energy and line width broadening were observed when applying positive potentials beyond 0.2 V, which was assigned to the onset oxidation potential of Au consistent with the bulk CV. No redox events in the bulk CV and the linear behavior of ΔEres and ΔΓ with voltage in singleparticle measurements in the potential window of −0.3 to 0.1 V confirmed that only capacitive charging occurred in this potential range. While ITO stability in aqueous electrolyte solution and gold redox reactions limited the potential range of capacitive charging,52 using nonaqueous electrolyte solutions21 and more stable electrode materials will be important to increase the potential range for plasmonic charge density tuning applications. In the pure charging regime, ΔEres increased and ΔΓ decreased with larger electron density by applying more negative potentials. This observation is not consistent with the theoretical prediction using a Drude-modified dielectric constant of Au. A theory based on the high-frequency limit of the RPA was developed, and the simulated results agreed with the experimental observation in the capacitive charging regime. Smaller volume AuNRs demonstrated larger LSPR energy shifts compared to those with a larger volume under the same potential range of −0.3 to 0.1 V. This result arose from the larger electron density change for the smaller AuNRs and was confirmed by a SCA calculation. Additionally, we demonstrated spPV with a single AuNR to probe the redox reaction of Au and observed the reduction peak at ∼0 V, matching the result obtained by bulk CV. These results provide insights into the morphology dependence of the spectral response caused by capacitive charging and pave the way for the use of plasmonic nanoparticles in electrocatalysis.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpclett.7b00945. Bulk CV for reference calibration, gold oxide reduction, and demonstration of capacitive current, along with an 2686

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The Journal of Physical Chemistry Letters

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explanation of chronocoulometric experiments; linear relationship between resonance energy and potential for all capacitive charging experiments in the main text; derivation of the Mie−Drude model and the corresponding theoretical spectral change in charge density for a AuNS; COMSOL simulations of a AuNR and SCA absorption spectra and spectral shifts due to change in charge density of a 4 and 6 nm Au sphere; TEM characterization showing the size distribution within the AuNR and AuNS samples used and correlated SEM and scattering measurements to demonstrate the relationship between shape and spectra used to separate particles optically (PDF)

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: cfl[email protected]. *E-mail: [email protected]. ORCID

Peter Nordlander: 0000-0002-1633-2937 Stephan Link: 0000-0002-4781-930X Christy F. Landes: 0000-0003-4163-6497 Wei-Shun Chang: 0000-0002-0251-4449 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The DOE BES (DE-SC0016534) supported B.S.H., who performed experiments, collected and analyzed data, and wrote the manuscript with direction from W.-S.C., C.F.L., and S.L. C.F.L., S.L, and P.N. acknowledge the Robert A. Welch Foundation [Grant C-1787 to C.F.L, Grant C-1664 to S.L., and C-1222 to P.N.] and the National Science Foundation [CBET-1438634]. C.F.L also thanks the ACS PRF [54684ND5], and S.L. and P.N. acknowledge support from the Air Force Office of Scientific Research [MURI FA9550-15-1-0022].

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