1 citations · 1 across the 1 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025★ 1 cited
Application of pretrained universal machine-learning interatomic potential for physicochemical simulation of liquid electrolytes in Li-ion battery
Suyeon Ju, Jinmu You, Gijin Kim +3
Achieving higher operational voltages, faster charging, and broader temperature ranges for Li-ion batteries necessitates advancements in electrolyte engineering. However, the compl…
physics.comp-ph2020
Training machine-learning potentials for crystal structure prediction using disordered structures
Changho Hong, Jeong Min Choi, Wonseok Jeong +6
Prediction of the stable crystal structure for multinary (ternary or higher) compounds with unexplored compositions demands fast and accurate evaluation of free energies in explori…