Modeling Reactions on the Solid-Liquid Interface With Next Generation Extended Lagrangian Quantum-Based Molecular Dynamics

Abstract

We present a framework for atomistic simulations of surface catalysis under electrochemical bias. The framework makes use of extended Lagrangian Born-Oppenheimer quantum-based molecular dynamics (XL-BOMD) simulations, which provide the speed and accuracy required for explicit atomistic treatment of both electrode and electrolyte. Simulations of solvated O$_2$ near nitrogen-doped graphene (NG) were performed to gain insight into the oxygen reduction reaction (ORR). Different mechanisms were observed, depending on the applied bias. Under high bias ORR occurred by an outer sphere mechanism, without adsorption of O$_2$ to NG. In this mechanism, electron transfer between the catalyst and the O$_2$ was mediated by the solvent. Under low bias ORR occurred by an inner sphere mechanism involving adsorption of O$_2$ to NG, leading to direct electron transfer. Combining quantum accuracy with explicit solvation and bias, XL-BOMD opens a route to predictive, atomistic insight into electrocatalytic processes beyond the reach of traditional methods.