88 citations · 92 across the 5 of their papers we have counts for
5 papers
Electrostatic Phenomenology Benchmarks for Machine-Learned Interatomic Potentials in Electrochemistry: Beyond the Energy-Force Metric
Barbara Sumić, Ria Vasdev, Sudheesh Kumar Ethirajan +8
Accurate treatment of long-range interactions in machine learning interatomic potentials (MLIPs) is essential for electrochemical simulations. However, aggregate energy and force e…
Water structuring at stacked graphene interfaces unveiled by machine-learning molecular dynamics
Dianwei Hou, Yevhen Horbatenko, Stefan Ringe +1
The wettability of monolayer and multilayer graphene remains a topic of longstanding debate. Here, we combined first-principles molecular dynamics simulations accelerated with the…
A nonlocal and nonlinear implicit electrolyte model for plane wave density functional theory
S M Rezwanul Islam, Foroogh Khezeli, Stefan Ringe +1
We have developed and implemented an implicit electrolyte model in the Vienna Ab initio Simulation Package (VASP) that includes nonlinear dielectric and ionic responses as well as…
Implicit Solvation Methods for Catalysis at Electrified Interfaces
Stefan Ringe, Nicolas G. Hörmann, Harald Oberhofer +1
Implicit solvation is an effective, highly coarse-grained approach in atomic-scale simulations to account for a surrounding liquid electrolyte on the level of a continuous polariza…
Function-Space Based Solution Scheme for the Size-Modified Poisson-Boltzmann Equation in Full-Potential DFT
Stefan Ringe, Harald Oberhofer, Christoph Hille +2
The size-modified Poisson-Boltzmann (MPB) equation is an efficient implicit solvation model which also captures electrolytic solvent effects. It combines an account of the dielectr…