Short-range machine-learning potentials trained on DFT accurately reproduce BaTiO3 phase transitions, switching, and defects even without explicit long-range Coulomb terms.
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Efficient local atomic cluster expansion for BaTiO$_3$ close to equilibrium
Short-range machine-learning potentials trained on DFT accurately reproduce BaTiO3 phase transitions, switching, and defects even without explicit long-range Coulomb terms.