首页|Investigators from Tsinghua University Target Machine Learning (Performance Comparisons of Nequip and Dpmd Machine Learning Interatomic Potentials for Tobermorites)
Investigators from Tsinghua University Target Machine Learning (Performance Comparisons of Nequip and Dpmd Machine Learning Interatomic Potentials for Tobermorites)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators publish new report on Machine Learn ing. According to news reporting originating inBeijing, People’s Republic of Ch ina, by NewsRx editors, the research stated, “Machine Learning InteratomicPoten tials (MLIPs) present a significant advancement in fitting molecular potential e nergy surfaces andpredicting molecular crystal structures and mechanical proper ties by closely approximating first-principles(FP) calculations results while s ubstantially reducing computational time. In this work, utilizing datasetsderiv ed from FP calculations, neural equivariant interatomic potentials (NequIP) and Deep PotentialMolecular Dynamics (DPMD) was implemented to develop MLIPs for to bermorite 9, 11, 14 & Aring;.”
BeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningMolecular DynamicsPhysicsTsinghua University
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