Atomistic understanding of hydrogen coverage on RuO2(110) surface under electrochemical conditions from ab initio statistical thermodynamics
Lei Zhang, Jan Kloppenburg, Chia-Yi Lin, Luka Mitrovic, Simon Gelin,, Ismaila Dabo, Darrell G. Schlom, Jin Suntivich, Geoffroy Hautier

TL;DR
This study uses ab initio thermodynamics and Monte Carlo simulations to model hydrogen coverage on RuO2(110) surfaces under electrochemical conditions, successfully reproducing experimental cyclic voltammetry features and elucidating dehydrogenation mechanisms.
Contribution
The paper introduces a combined ab initio and statistical thermodynamics approach to accurately model hydrogen coverage and electrochemical behavior of RuO2(110), aligning with experimental CV data.
Findings
Reproduces the two-peak CV pattern observed experimentally.
Identifies hydrogen desorption sequence on RuO2(110) surface.
Shows OER occurs on fully dehydrogenated surface above 1.23 V.
Abstract
Understanding the dehydrogenation of transition metal oxide surfaces under electrochemical potential is critical to the control of important chemical processes such as the oxygen evolution reaction (OER). Using first principles computations, we model the thermodynamic dehydrogenation process on RuO(110) and compare the results to experimental cyclic voltammetry (CV) on single crystal. We use a cluster expansion model trained on *ab initio* energy data coupled with Monte Carlo (MC) sampling to derive the macroscopic electrochemical observables, i.e., experimental CV, from the energetics of different hydrogen coverage microstates on well-defined RuO(110). Our model reproduces the unique "two-peaks" cyclic voltammogram observed experimentally with current density peak positions and shapes in good qualitative agreement. We show that RuO(110) starts as a water-covered surface…
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Taxonomy
TopicsElectrocatalysts for Energy Conversion · Electron and X-Ray Spectroscopy Techniques · Machine Learning in Materials Science
