A machine-learned force field plus a learned charge response accelerates finite-field simulations of the Au(100)/NaCl(aq) interface and predicts a voltage-driven reorientation of interfacial water at the anode.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.chem-ph 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Machine learning accelerated finite-field simulations for electrochemical interfaces
A machine-learned force field plus a learned charge response accelerates finite-field simulations of the Au(100)/NaCl(aq) interface and predicts a voltage-driven reorientation of interfacial water at the anode.