21 citations · 22 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…
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…
cond-mat.mtrl-sci2022★ 21 cited
Comparative study of first-principles approaches for effective Coulomb interaction strength between localized -electrons: lanthanide metals as an example
Bei-Lei Liu, Yue-Chao Wang, Yu Liu +6
As correlation strength has a key influence on the simulation of strongly correlated materials, many approaches have been proposed to obtain the parameter using first-principles ca…