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physics.comp-ph2019★ 976 cited
A Performance and Cost Assessment of Machine Learning Interatomic Potentials
Yunxing Zuo, Chi Chen, Xiangguo Li +8
Machine learning of the quantitative relationship between local environment descriptors and the potential energy surface of a system of atoms has emerged as a new frontier in the d…
physics.comp-ph2017★ 165 cited
Accurate Force Field for Molybdenum by Machine Learning Large Materials Data
Chi Chen, Zhi Deng, Richard Tran +3
In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning tech…