5 citations · 8 across the 2 of their papers we have counts for
2 papers
physics.comp-ph2024★ 5 cited
Thermal Conductivity Calculation using Homogeneous Non-equilibrium Molecular Dynamics Simulation with Allegro
Kohei Shimamura, Shinnosuke Hattori, Ken-ichi Nomura +2
In this study, we derive the heat flux formula for the Allegro model, one of machine-learning interatomic potentials using the equivariant deep neural network, to calculate lattice…
physics.comp-ph2022★ 3 cited
Construction of Machine-Learning Interatomic Potential Under Heat Flux Regularization and Its Application to Power Spectrum Analysis for Silver Chalcogenides
Kohei Shimamura, Koura Akihide, Fuyuki Shimojo
We propose a data-driven approach for constructing machine-learning interatomic potentials (MLIPs) trained under a regularization with the aim of avoiding nonphysical heat flux. Sp…