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cs.AI2026
An Ontology for Machine Learning Interatomic Potentials
Daniel Hernández, Jong Hyun Jung, Yuji Ikeda +11
Machine learning interatomic potentials (MLIPs) approximate quantum-mechanical energies and forces---conventionally computed by density functional theory (DFT) or wave-function met…
cond-mat.mtrl-sci2026★ 1 cited
Temperature dependence of the Gibbs energies of formation of point defects in B2 MoTa from ab initio calculations
Xiang Xu, Fritz Körmann, Sergiy Divinski +2
Using B2 MoTa, the strongest B2 former among group V/VI refractory binaries, as a model system, we compute temperature-dependent Gibbs energies of formation of vacancies and antisi…