Stark effect or coverage dependence? Disentangling the EC-SEIRAS vibrational shift of sulfate on Au(111)

Infrared spectroscopy is a widely employed analytical tool in (electrochemical) surface science as the spectra contain a wealth of information about the interaction of interfacial adsorbates with their environment. Separating and quantifying individual contributions, for example, of co-adsorbates, the substrate or electric field effects, on the overall spectral response, however, is often non-trivial as the various interactions manifest themselves in similar spectral behavior. Here, we present an experimental approach to differentiate between and quantify potential-induced coverage dependence and field-related Stark effects observed in a sulfate band shift of 93.5 ± 1.5 cm−1/V in electrochemical infrared spectra of the showcase sulfate/Au(111) interface. In combination with a simple linear model equation used to describe the potential-induced peak shift of the sulfate stretch vibration, we determine the coverage dependence contribution to be 15.6 ± 1.2 cm−1/θSO and the Stark effect to amount to 75.6 ± 2.7 cm−1/V. Our work provides a novel route to gain fundamental insight into interfacial adsorbate interactions in electrochemical surface science.J.H.K.P. and K.F.D. gratefully acknowledge financial support by the Max Planck Graduate Center with the Johannes Gutenberg University Mainz (MPGC). U.E.Z. is grateful for financial support from the Alexander von Humboldt Foundation. J.M.F. thanks MCINN-FEDER (Spain) for support through Project No. CTQ2016-76221-P. K.F.D. acknowledges generous support through the Emmy Noether Program of the Deutsche Forschungsgemeinschaft (No. DO1691/1-1) and through the “Plus 3” Program of the Boehringer Ingelheim Foundation

Role of OH Intermediates during the Au Oxide Electro-Reduction at Low pH Elucidated by Electrochemical Surface-Enhanced Raman Spectroscopy and Implicit Solvent Density Functional Theory

Molecular understanding of the electrochemical oxidation of metals and the electro-reduction of metal oxides is of pivotal importance for the rational design of catalyst-based devices where metal(oxide) electrodes play a crucial role. Operando monitoring and reliable identification of reacting species, however, are challenging tasks because they require surface-molecular sensitive and specific experiments under reaction conditions and sophisticated theoretical calculations. The lack of molecular insight under operating conditions is largely due to the limited availability of operando tools and to date still hinders a quick technological advancement of electrocatalytic devices. Here, we present a combination of advanced density functional theory (DFT) calculations considering implicit solvent contributions and time-resolved electrochemical surface-enhanced Raman spectroscopy (EC-SERS) to identify short-lived reaction intermediates during the showcase electro-reduction of Au oxide (AuOx) in sulfuric acid over several tens of seconds. The EC-SER spectra provide evidence for temporary Au-OH formation and for the asynchronous adsorption of (bi)sulfate ions at the surface during the reduction process. Spectral intensity fluctuations indicate an OH/(bi)sulfate turnover period of 4 s. As such, the presented EC-SERS potential jump approach combined with implicit solvent DFT simulations allows us to propose a reaction mechanism and prove that short-lived Au-OH intermediates also play an active role during the AuOx electro-reduction in acidic media, implying their potential relevance also for other electrocatalytic systems operating at low pH, like metal corrosion, the oxidation of CO, HCOOH, and other small organic molecules, and the oxygen evolution reaction.J.H.K.P. and K.F.D. gratefully acknowledge financial support by the Max Planck Graduate Center with the Johannes Gutenberg University Mainz (MPGC). K.F.D. acknowledges generous support through the Emmy Noether Program of the Deutsche Forschungsgemeinschaft (DO1691/1−1) and through the “Plus 3” Program of the Boehringer Ingelheim Foundation. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreements No. 665667 and No. 798532. This work was supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID s836