首页|Findings from Nanjing University of Aeronautics and Astronautics Reveals New Fin dings on Machine Learning (Impart of Heterogeneous Charge Polarization and Distr ibution On Friction At Watergraphene Interfaces: a Density-functional-theory Ba sed …)
Findings from Nanjing University of Aeronautics and Astronautics Reveals New Fin dings on Machine Learning (Impart of Heterogeneous Charge Polarization and Distr ibution On Friction At Watergraphene Interfaces: a Density-functional-theory Ba sed …)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingfrom Nanjing, People’s Republic of China, by NewsRx journalists, research stated, “Accurately characterizingfricti on behaviors at water-solid interfaces remains a challenge because of the dynami c nature of watermolecules and temporal variations in solid surface charges. By using a density-functional-theory (DFT)based machine learning (ML) technique a nd long-time ML-parametrized molecular dynamics simulations,we have systematica lly investigated water-induced charge polarization and redistribution on graphen e, aswell as its impact on friction at water-graphene interfaces.”
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningNanjing University of Aeron autics and Astronautics
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