Application of machine learning potentials to predict grain boundary properties in fcc elemental metals

Takayuki Nishiyama, Atsuto Seko, Isao Tanaka

Accurate interatomic potentials are in high demand for large-scale atomistic simulations of materials that are prohibitively expensive by density functional theory (DFT) calculatio…