首页|Researchers from Yunnan Normal University Report New Studies and Findings in the Area of Machine Learning (Combined Machine Learning and High-throughput Calcula tions Predict Heyd-scuseriaernzerhof Band Gap of 2d Materials and Potential ... )
Researchers from Yunnan Normal University Report New Studies and Findings in the Area of Machine Learning (Combined Machine Learning and High-throughput Calcula tions Predict Heyd-scuseriaernzerhof Band Gap of 2d Materials and Potential ... )
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting originating from Kunming, People’s Repub lic of China, by NewsRx correspondents, research stated, “We present a novel tar get-driven methodology devised to predict the Heyd-Scuseria-Ernzerhof (HSE) band gap of two-dimensional (2D) materials leveraging the comprehensive C2DB databas e. This innovative approach integrates machine learning and density functional t heory (DFT) calculations to predict the HSE band gap, conduction band minimum (C BM), and valence band maximum (VBM) of 2176 types of 2D materials.”
KunmingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningYunnan Normal University
NETL
NSTL
