17 citations · 17 across the 4 of their papers we have counts for
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Molecular Dynamics Simulations of SrTiO with Oxygen Vacancies using Neural Network Potentials
Kazutaka Nishiguchi, Ryota Yamamoto, Meguru Yamazaki +4
A precise analysis of point defects in solids requires accurate molecular dynamics (MD) simulations of large-scale systems. However, ab initio MD simulations based on density funct…
Active Learning of a Neural Network Potential for Large-Scale Atomistic Simulations of Polymer Electrolyte Membranes
Yuta Yoshimoto, Naoki Matsumura, Meguru Yamazaki +3
Machine learning interatomic potentials (MLIPs) can achieve near density-functional-theory (DFT) accuracy at force-field computational cost; however, long-time, large-scale molecul…
Generator of Neural Network Potential for Molecular Dynamics: Constructing Robust and Accurate Potentials with Active Learning for Nanosecond-scale Simulations
Naoki Matsumura, Yuta Yoshimoto, Tamio Yamazaki +5
Neural network potentials (NNPs) enable large-scale molecular dynamics (MD) simulations of systems containing >10,000 atoms with the accuracy comparable to ab initio methods and pl…