Accurate description of ion migration in solid-state ion conductors from machine-learning molecular dynamics

Machine-learning molecular dynamics provides predictions of structural and anharmonic vibrational properties of solid-state ionic conductors with ab initio accuracy. This opens a path towards rapid design of novel battery materials.