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20232025
most citedBridging electronic and classical density-functional theory using universal machine-learned functional approximations

17 citations · 17 across the 3 of their papers we have counts for

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physics.chem-ph2025

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…