3 papers
cs.LG2025
Ensemble Learning of Machine Learning Force Fields
Bangchen Yin, Yue Yin, Yuda W. Tang +1
Machine learning force fields (MLFFs) are a promising approach to balance the accuracy of quantum mechanics with the efficiency of classical potentials, yet selecting an optimal mo…
physics.chem-ph2025
LOCAL: A Locality-based Active Learning Framework for Predicting the Stability of Dual-Atom Catalysts
Yue Yin, Jiangshan He, Runze Li +4
Dual-atom catalysts supported on nitrogen-doped graphene (DAC/NG) are emerging as a family of promising catalysts that can overcome intrinsic limitations of single-atom catalysts.…
physics.chem-ph2025
Oxidation States in Solids from Data-Driven Paradigms
Yue Yin, Hai Xiao
The oxidation state (OS) is an essential chemical concept that embodies chemical intuition but cannot be computed with well-defined physical laws. We establish a data-driven paradi…