Hai-Kuan Dong (Haikuan Dong)

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 6

Top Topics

Escherichia Coli

Highly Efficient

Crystal Structure

Molecular Dynamics

Top Venues

Journal of physics. Condensed matter : an Institute of Physics journal

Physical chemistry chemical physics : PCCP

The Journal of chemical physics

This page only lists publications with an associated author ORCID identifier.

Publications

Zheyong Fan, Yang Xiao, Yanzhou Wang, Penghua Ying, Shunda Chen, Hai-Kuan Dong
Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials. Journal of physics. Condensed matter : an Institute of Physics journal (2024)
Zheyong Fan, Yang Xiao, Yanzhou Wang, Penghua Ying, Shunda Chen, Hai-Kuan Dong
Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials. Journal of physics. Condensed matter : an Institute of Physics journal 36 (24) (2024)
Yong-Bo Shi, Shu-Han Lv, Zhu-Feng Shao, Hai-Kuan Dong, Shuo Cao, Ping Qian
A first-principles study of 1D and 2D C 60 nanostructures: strain effects on band alignments and carrier mobility. Journal of physics. Condensed matter : an Institute of Physics journal 35 (22) (2023)
Yong-Bo Shi, Shu-Han Lv, Zhu-Feng Shao, Hai-Kuan Dong, Shuo Cao, Ping Qian
A ﬁrst-principles study of 1D and 2D C60 nanostructures : strain eﬀects on band alignments and carrier mobility. Journal of physics. Condensed matter : an Institute of Physics journal (2023)
Yongbo Shi, Yuanyuan Chen, Hai-Kuan Dong, Hao Wang, Ping Qian
Investigation of phase transition, mechanical behavior and lattice thermal conductivity of halogen perovskites using machine learning interatomic potentials. Physical chemistry chemical physics : PCCP (2023)
Zheyong Fan, Yanzhou Wang, Penghua Ying, Keke Song, Junjie Wang, Yong Wang, Zezhu Zeng, Ke Xu, Eric Lindgren, J Magnus Rahm, Alexander J Gabourie, Jiahui Liu, Hai-Kuan Dong, Jianyang Wu, Yue Chen, Zheng Zhong, Jian Sun, Paul Erhart, Yanjing Su, Tapio Ala-Nissila
GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations. The Journal of chemical physics 157 (11) (2022)