1 citations · 1 across the 4 of their papers we have counts for
4 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…
User-defined Electrostatic Potentials in DFT Supercell Calculations: Implementation and Application to Electrified Interfaces
Samuel Mattoso, Jing Yang, Florian Deißenbeck +5
Introducing electric fields into density functional theory (DFT) calculations is essential for understanding electrochemical processes, interfacial phenomena, and the behavior of m…
Macro-Dipole-Constrainted Learning of Atomic Charges for Accurate Electrostatic Potentials at Electrochemical Interfaces
Jing Yang, Bingxin Li, Samuel Mattoso +3
Large thermal fluctuations of the liquid phase obscure the weak macroscopic electric field that drives electrochemical reactions, rendering the extraction of reliable interfacial c…
SPEA -- an analytical thermodynamic model for defect phase diagram
Jing Yang, Ahmed Abdelkawy, Mira Todorova +1
We propose an analytical thermodynamic model for describing defect phase transformations, which we term the statistical phase evaluation approach (SPEA). The SPEA model assumes a B…