10 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments
Xuqiang Shao, Yuqi Zhang, Di Zhang +10
Constructing efficient and diverse datasets is essential for the development of accurate machine learning potentials (MLPs) in atomistic simulations. However, existing approaches o…
cond-mat.mtrl-sci2024★ 10 cited
Picturing the Gap Between the Performance and US-DOE's Hydrogen Storage Target: A Data-Driven Model for MgH2 Dehydrogenation
Chaoqun Li, Weijie Yang, Hao Liu +5
Developing solid-state hydrogen storage materials is as pressing as ever, which requires a comprehensive understanding of the dehydrogenation chemistry of a solid-state hydride. Tr…