104 citations · 221 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2024★ 104 cited
Molecular dynamics simulations of heat transport using machine-learned potentials: A mini review and tutorial on GPUMD with neuroevolution potentials
Haikuan Dong, Yongbo Shi, Penghua Ying +9
Molecular dynamics (MD) simulations play an important role in understanding and engineering heat transport properties of complex materials. An essential requirement for reliably pr…
cond-mat.mtrl-sci2023★ 54 cited
Mechanisms of temperature-dependent thermal transport in amorphous silica from machine-learning molecular dynamics
Ting Liang, Penghua Ying, Ke Xu +4
Amorphous silica (a-SiO) is a foundational disordered material for which the thermal transport properties are important for various applications. To accurately model the intera…
physics.comp-ph2023★ 63 cited
Accurate prediction of heat conductivity of water by a neuroevolution potential
Ke Xu, Yongchao Hao, Ting Liang +4
We propose an approach that can accurately predict the heat conductivity of liquid water. On the one hand, we develop an accurate machine-learned potential based on the neuroevolut…