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cond-mat.mtrl-sci2021
Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials
Carla Verdi, Ferenc Karsai, Peitao Liu +2
Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with first-principles accuracy. It is not yet clear, however…
cond-mat.mtrl-sci2021★ 63 cited
Phase Transitions of Zirconia: Machine-Learned Force Fields Beyond Density Functional Theory
Peitao Liu, Carla Verdi, Ferenc Karsai +1
We present an approach to generate machine-learned force fields (MLFF) with beyond density functional theory (DFT) accuracy. Our approach combines on-the-fly active learning and $Δ…