5 citations · 12 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Projected gradient descent algorithm for crystal structure relaxation under a fixed unit cell volume
Yukuan Hu, Junlei Yin, Xingyu Gao +2
This paper is concerned with crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and form…
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…
A force-based gradient descent method for atomic structure relaxation
Yukuan Hu, Xingyu Gao, Yafan Zhao +2
Force-based algorithms for atomic structure relaxation, such as conjugate gradient methods, usually get stuck in the line minimization processes along s…