104 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Hong KongHK12 papers
- Bay InstituteUS9 papers
- Beihang UniversityCN9 papers
- Chinese Academy of SciencesCN8 papers
- Peking UniversityCN8 papers
- Southern University of Science and TechnologyCN8 papers
- Sun Yat-sen UniversityCN8 papers
- Chinese University of Hong KongHK7 papers
- Huazhong University of Science and TechnologyCN6 papers
- University of Science and Technology of ChinaCN5 papers
- Bohai UniversityCN4 papers
- California State University, NorthridgeUS4 papers
5 papers · 2 filters
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…
Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials
Penghua Ying, Wenjiang Zhou, Lucas Svensson +10
Path-integral molecular dynamics (PIMD) simulations are crucial for accurately capturing nuclear quantum effects in materials. However, their computational intensity and reliance o…
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…
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…
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…