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cond-mat.mtrl-sci2026
Atoms that Matter: Largest Materials Datasets Are 99% Redundant, and Local Chemistry Can Guide the Required 1%
Evgeny Moerman, Igor Poltavsky, Anton Charkin-Gorbulin +1
General-purpose machine-learning force fields (MLFFs) for materials are now trained on the order of million structures, assuming transferability requires such scale. We test…
physics.chem-ph2026★ 1 cited
MBD-ML: Many-body dispersion from machine learning for molecules and materials
Evgeny Moerman, Adil Kabylda, Almaz Khabibrakhmanov +1
Van der Waals (vdW) interactions are essential for describing molecules and materials, from drug design and catalysis to battery applications. These omnipresent interactions must a…