1 citations · 1 across the 2 of their papers we have counts for
2 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…
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…