Modeling Reactions on the Solid-Liquid Interface with Next Generation Extended Lagrangian Quantum-Based Molecular Dynamics.
- 1Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.
- 2Department of Physics, University of Illinois Urbana-Champaign, Urbana-Champaign, Illinois 61820, United States.
- 3Computing and Artificial Intelligence Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.
Abstract
We present a series of simulations of the oxygen reduction reaction (ORR) using a novel framework for atomistic simulations of surface catalysis under electrochemical bias. The framework makes use of quantum-mechanical extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) simulations, which provide the speed and accuracy required for explicit atomistic treatment of both electrode and electrolyte. Simulations of solvated O₂ near nitrogen-doped graphene (NG) were performed to gain insight into the ORR, and different mechanisms were observed, depending on the applied bias. Under higher bias the ORR occurred by an outer-sphere mechanism, without adsorption of O₂ to NG. In this mechanism, electron transfer between the catalyst and the O₂ was mediated by the solvent. Under lower bias the ORR occurred by an inner-sphere mechanism involving adsorption of O₂ to NG, leading to direct electron transfer. Our extensive, all-atom quantum-mechanical molecular dynamics simulations also show clear differences between the kinetics of the ORR on this ideally polarizable electrode and commonly used kinetic theories, leading to new insights regarding mechanistic changes with varied overpotentials. Combining quantum accuracy with explicit solvation and electrostatic potential bias, XL-BOMD opens a route to predictive, atomistic insight into electrocatalytic processes, as demonstrated with the ORR.
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BibTeX
@article{grove2026modeling,
title = {{Modeling Reactions on the Solid-Liquid Interface with Next Generation Extended Lagrangian Quantum-Based Molecular Dynamics.}},
author = {Rae A Corrigan Grove and Kevin G Kleiner and Joshua Finkelstein and Ivana Matanovic and Michael E Wall and Travis E Jones and Anders M N Niklasson and Christian F A Negre},
journal = {The journal of physical chemistry. C, Nanomaterials and interfaces},
year = {2026},
month = sep,
doi = {10.1021/acs.jpcc.6c06025},
url = {https://europepmc.org/article/MED/42899130},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Modeling Reactions on the Solid-Liquid Interface with Next Generation Extended Lagrangian Quantum-Based Molecular Dynamics.
AU - Rae A Corrigan Grove
AU - Kevin G Kleiner
AU - Joshua Finkelstein
AU - Ivana Matanovic
AU - Michael E Wall
AU - Travis E Jones
AU - Anders M N Niklasson
AU - Christian F A Negre
PY - 2026
DA - 2026/09/30
JO - The journal of physical chemistry. C, Nanomaterials and interfaces
DO - 10.1021/acs.jpcc.6c06025
UR - https://europepmc.org/article/MED/42899130
AB - We present a series of simulations of the oxygen reduction reaction (ORR) using a novel framework for atomistic simulations of surface catalysis under electrochemical bias. The framework makes use of quantum-mechanical extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) simulations, which provide the speed and accuracy required for explicit atomistic treatment of both electrode and electrolyte. Simulations of solvated O₂ near nitrogen-doped graphene (NG) were performed to gain insight into the ORR, and different mechanisms were observed, depending on the applied bias. Under higher bias the ORR occurred by an outer-sphere mechanism, without adsorption of O₂ to NG. In this mechanism, electron transfer between the catalyst and the O₂ was mediated by the solvent. Under lower bias the ORR occurred by an inner-sphere mechanism involving adsorption of O₂ to NG, leading to direct electron transfer. Our extensive, all-atom quantum-mechanical molecular dynamics simulations also show clear differences between the kinetics of the ORR on this ideally polarizable electrode and commonly used kinetic theories, leading to new insights regarding mechanistic changes with varied overpotentials. Combining quantum accuracy with explicit solvation and electrostatic potential bias, XL-BOMD opens a route to predictive, atomistic insight into electrocatalytic processes, as demonstrated with the ORR.
SN - 1932-7447
SN - 1932-7455
ER -