A multi-valued machine-learned dipole model with oxidation-number corrections enables electric-field-driven molecular dynamics for liquids and solids, demonstrated on water and LiNbO3.
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Electric-Field Driven Nuclear Dynamics of Liquids and Solids from a Multi-Valued Machine-Learned Dipolar Model
A multi-valued machine-learned dipole model with oxidation-number corrections enables electric-field-driven molecular dynamics for liquids and solids, demonstrated on water and LiNbO3.