1 citations · 1 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2026
Unlocking Multi-Component Bulk-Materials Molecular Dynamics with a Small-Footprint Machine Learning Interatomic Potential
Yucheng Ouyang, Xin Chen, Ying Liu +8
Bulk materials, as opposed to nanomaterials, require molecular dynamics (MD) simulations on a large spatial scale (~10^9 atoms or more) to adequately capture their atomic-scale phy…
cond-mat.mtrl-sci2025
ProME: An Integrated Computational Platform for Material Properties at Extremes and Its Application in Multicomponent Alloy Design
Xingyu Gao, William Yi Wang, Xin Chen +8
We have built an integrated computational platform for material properties at extreme conditions, ProME (Professional Materials at Extremes) v1.0, which enables integrated calculat…
physics.comp-ph2023★ 1 cited
TensorMD: Scalable Tensor-Diagram based Machine Learning Interatomic Potential on Heterogeneous Many-Core Processors
Xin Chen, Yucheng Ouyang, Zhenchuan Chen +7
Molecular dynamics simulations have emerged as a potent tool for investigating the physical properties and kinetic behaviors of materials at the atomic scale, particularly in extre…