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20222026
most citedMachine-learning interatomic potential for molecular dynamics simulation of ferroelectric KNbO3 perovskite

32 citations · 32 across the 6 of their papers we have counts for

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cond-mat.mtrl-sci2026

Atomistic prediction of magnetic behaviour across chemistry, structure and temperature

Ruosong Shi, Chengbing Chen, Bicheng Liu +15

Controlling magnetic phases and properties through composition and external conditions is central to the development of magnetic materials. Atomistic foundation models offer a rout…