60th Annual Report on Research 2015

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Reports: ND554684-ND5: Spectro-Electrochemical Microscopy of Single Nanoparticle Electrocatalysts

The objective of this project is to correlate the catalytic activity of gold nanoparticle electrocatalysts with nanoparticle morphology and surface chemistry for the reduction of CO₂ using single particle spectro-electrochemical microscopy. Our project’s central hypothesis is that the catalytic activity of gold nanoparticle electrocatalysts strongly depends on size, shape, crystal facet and surface chemistry, and that possibly only a few catalytic 'hot spots' dominate the signal in ensemble measurements. The project goals are: (1) Establish the relationship between the electron density of a single gold nanoparticle and the induced spectral changes of the plasmon scattering response (wavelength maximum, intensity, linewidth) as a function of nanoparticle morphology. (2) Determine the catalyst activity for the CO₂ reduction using different gold nanoparticle electrocatalysts. (3) Identify the spatial extent of active catalytic sites on single gold nanoparticles using super-resolution electrochemical luminescence (ECL) microscopy. We have made considerable progress on both our first goal and our project hypothesis. We have achieved reproducible and reversible electrochemical tuning of the plasmon response in gold nanoparticles in a three electrode cell with sodium chloride as the electrolyte. Additionally, our hyperspectral setup allows us to collect either time-resolved spectra as a function of cell potential or spectra from multiple nanoparticles simultaneously at a constant potential. Figure 1 shows the spectroelectrochemical setup (a) and model hyperspectral image (b, left) as well as voltage dependent single particle spectra (b, right). Below, in (c) are shown cartoons of the electrochemical range and Stern layer chemistries.  Potential-dependent hyperspectral imaging gave us the means to observe heterogeneity within a nanoparticle population (Figure 2). A series of hyperspectral images at each potential was used to identify the steady-state potential induced plasmon resonance shift. Figure 2a shows an example spectral image compiled at open circuit potential, with circled nanoparticles noting subsets identified by their potential-dependent spectral behavior. Each scattering center in the series was located and fit with a single Lorentzian function. Single gold nanoparticles were distinguished from clusters by imposing a coefficient of determination cutoff, R² > 0.95.  Because we achieved a large signal-to-noise ratio, spectra were well-fit. Shifts as small as 1 meV were detectible. Figures 2b-e support our project hypothesis that within each sample of nanoparticles are heterogeneous surface chemistries that can dominate catalytic response. By investigating many nanoparticles under potential control in this cathodic range (0 to -800 mV), we found that the majority of nanoparticles demonstrated behavior not predicted by charge density tuning, as shown in Figure 2b. If charge density tuning were the only mechanism, the plasmon resonance of all gold nanoparticles would blue shift linearly upon application of negative electrochemical potentials, due to an increase in free electron density that results from electrons flowing from the potentiostat circuit into the nanoparticles and substrate in establishing the electrical potential difference between the bulk electrolyte and the nanoelectrodes. However, spectra for half of the single gold nanoparticles that met the selection criteria (R² > 0.95) showed significant irreversible changes in their scattering spectra including significant resonance broadening, large increases in scattering intensity, and the loss of their original Lorentzian response. These nanoparticles are highlighted with red circles in Figure 2a and representative spectra at the potential vertices are shown in Figure 2c. We attribute this to an electrochemically irreversible reaction underpotential reaction, probably with ions from the reference electrode, as the chemical identity (silver vs. platinum) was found to influence the prevalence of such reactions (data not shown). One-fourth of the nanoparticles also showed large increases in intensity, spectral broadening, and plasmon resonance red shifts not predicted by the charge density tuning model. The scattering spectra of nanoparticles in this subset maintained their Lorentzian line shape throughout the entire experiment, but their scattering spectra only returned to initial conditions after the application of a sufficient positive potential. These nanoparticles are highlighted by cyan circles in Figure 2a and example spectra are shown from a single nanoparticle in Figure 2d. Further investigations are required to elucidate the mechanisms and potentially complex behaviors reported in Figures 2c and d. Just under a quarter of the single gold nanoparticles followed the predicted charge density tuning model, indicated by green circles in Figure 2a and example spectra from a nanoparticle in this subset in Figure 2e. Nanoparticles in this subset were well-fit throughout the experiment (R² > 0.95), show small changes in FWHM (ΔΓ < 20 meV) and demonstrated completely reversible plasmon resonance shifts. The change in peak resonance energy as a function of potential for this subset of nanoparticles is shown in Figure 2e as a mean resonance shift with associated standard error for all nanoparticles in this subpopulation. The return to initial resonance energy is a strong indicator that the spectral tuning mechanism for this subset of nanoparticles is electrochemically reversible, fitting the charge density tuning model. The most valuable electrochemical techniques are not steady-state techniques, but rather are dynamic in nature. The ability to precisely and quickly vary the potential at an electrode surface allows researchers to characterize electrodes, investigate fine potential structure, and determine reaction kinetics. Thus, we developed dynamic single-particle spectroelectrochemistry (Figure 3). The potential was swept in a sawtooth pattern at 10 mV/s between 0 and -800 mV, as shown in Figure 3a. Scattered light from a single nanoparticle was directed to the spectrograph and spectra were recorded every 2.5 seconds. Each spectrum was independently fit with a single Lorentzian and the parameters of the fit determined the resonance energy, E_Res, and full width at half maximum, Γ. E_Res and Γ are shown in Figure 3b as solid and dashed white lines, respectively.  The reversible spectral tuning shown in Figure 3 is consistent with the charge density tuning model.     In summary the mechanisms underlying spectroelectrochemical tuning of the plasmon resonance vary from nanoparticle to nanoparticle. The methodology developed in Year 1 allows in-depth study of the multiple mechanisms by measuring the effects of other electrolytes, ion concentrations, nanoparticle morphology and size, potential ranges, and electrode materials on the catalytic efficiency of individual and distributions of nanoparticles.