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- Great Bay University3 papers
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4 papers · 1 filter
Insight into the effect of force error on the thermal conductivity from machine-learned potentials
Wenjiang Zhou, Nianjie Liang, Xiguang Wu +3
Machine-learned potentials (MLPs) have been extensively used to obtain the lattice thermal conductivity via atomistic simulations. However, the impact of force errors in various ML…
SSRESF: Sensitivity-aware Single-particle Radiation Effects Simulation Framework in SoC Platforms based on SVM Algorithm
Meng Liu, Shuai Li, Fei Xiao +3
The ever-expanding scale of integrated circuits has brought about a significant rise in the design risks associated with radiation-resistant integrated circuit chips. Traditional s…
Isotope engineering of carrier mobility via Fröhlich electron-phonon interaction
Wenjiang Zhou, Te-Huan Liu, Bai Song
Isotope effects on phonon properties and transport have been predicted and observed for decades. However, despite the crucial impact of electron-phonon interactions, the effect of…
Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics
Xiguang Wu, Wenjiang Zhou, Haikuang Dong +5
Machine learned potentials (MLPs) have been widely employed in molecular dynamics (MD) simulations to study thermal transport. However, literature results indicate that MLPs genera…