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physics.comp-ph2020★ 55 cited
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…
physics.comp-ph2020★ 3 cited
Derivative structure enumeration using binary decision diagram
Kohei Shinohara, Atsuto Seko, Takashi Horiyama +3
A derivative structure is a nonequivalent substitutional atomic configuration derived from a given primitive cell. The enumeration of derivative structures plays an essential role…