526 citations · 4.4k across the 56 of their papers we have counts for
56 papers
Sub-micrometer phonon mean free paths in metal-organic frameworks revealed by machine-learning molecular dynamics simulations
Penghua Ying, Ting Liang, Ke Xu +4
Metal-organic frameworks (MOFs) are a family of materials that have high porosity and structural tunability and hold great potential in various applications, many of which requirin…
A high-performance GPU implementation of the electron-phonon Wannier interpolation and the related transport properties
Zhe Liu, Bo Zhang, Zheyong Fan +1
The electron-phonon Wannier interpolation (EPWI) method is an efficient way to compute the properties of electron-phonon interactions (EPIs) accurately. This study presents a GPU-a…
Large-scale machine-learning molecular dynamics simulation of primary radiation damage in tungsten
Jiahui Liu, Jesper Byggmastar, Zheyong Fan +2
Simulating collision cascades and radiation damage poses a long-standing challenge for existing interatomic potentials, both in terms of accuracy and efficiency. Machine-learning b…
Tuning the lattice thermal conductivity in van-der-Waals structures through rotational (dis)ordering
Fredrik Eriksson, Erik Fransson, Christopher Linderälv +2
It has recently been demonstrated that MoS2 with irregular interlayer rotations can achieve an extreme anisotropy in the lattice thermal conductivity (LTC), which is for example of…
Magic angle in thermal conductivity of twisted bilayer graphene
Yajuan Cheng, Zheyong Fan, Tao Zhang +5
We report a local minimum in thermal conductivity in twisted bilayer graphene (TBG) at the angle of 1.08, which corresponds to the 'magic angle' in the transition of severa…
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…