Development of machine-learned interatomic potentials to predict structure, transport, and reactivity in platinum-based fuel cells

Kamron Fazel, Sam Brown, Jacob Clary +5

Machine-learned interatomic potentials (MLIPs) have rapidly progressed in accuracy, speed, and data efficiency in recent years. However, training robust MLIPs in multicomponent sys…