Arthur France-Lanord

Overcoming Sampling Limitations Using Machine-Learned Interatomic Potentials: The Case of Water-in-Salt Electrolytes

Abstract Machine-learned interatomic potentials hold the promise to enable the modeling of highly concentrated liquids over meaningful time scales, far from reach for current ab initio electronic structure methods. Here we evaluate the performances of various MACE potentials in m...