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Extending the limit of molecular dynamics with ab initio accuracy to 10
  billion atoms

Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms

5 January 2022
Zhuoqiang Guo
Denghui Lu
Yujin Yan
Siyu Hu
Rongrong Liu
Guangming Tan
Ninghui Sun
Wanrun Jiang
Lijun Liu
Yixiao Chen
Linfeng Zhang
Mohan Chen
Han Wang
Weile Jia
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms"

3 / 3 papers shown
Title
DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials
DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials
K. Han
Bowen Deng
Amir Barati Farimani
Gerbrand Ceder
46
1
0
28 May 2025
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in
  Materials Science
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science
Santiago Miret
Kin Long Kelvin Lee
Carmelo Gonzales
Marcel Nassar
Matthew Spellings
85
19
0
31 Oct 2022
Learning Local Equivariant Representations for Large-Scale Atomistic
  Dynamics
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics
Albert Musaelian
Simon L. Batzner
A. Johansson
Lixin Sun
Cameron J. Owen
M. Kornbluth
Boris Kozinsky
133
470
0
11 Apr 2022
1