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physics.comp-ph2026
NEP-CG and NEP-AACG: Efficient coarse-grained and multiscale all-atom-coarse-grained neuroevolution potentials
Zheyong Fan, Wenjun Zhang, Zhenhao Zhang +3
Machine-learned coarse-grained (CG) models often suffer from noisy training data, limiting their accuracy and transferability. We propose a method to generate low-noise training da…
physics.comp-ph2025
PYSED: A tool for extracting kinetic-energy-weighted phonon dispersion and lifetime from molecular dynamics simulations
Ting Liang, Wenwu Jiang, Ke Xu +4
Machine learning potential-driven molecular dynamics (MD) simulations have significantly enhanced the predictive accuracy of thermal transport properties across diverse materials.…
physics.comp-ph2025
Probing the ideal limit of interfacial thermal conductance in two-dimensional van der Waals heterostructures
Ting Liang, Ke Xu, Penghua Ying +9
Probing the ideal limit of interfacial thermal conductance (ITC) in two-dimensional (2D) heterointerfaces is of paramount importance for assessing heat dissipation in 2D-based nano…