463 citations · 776 across the 9 of their papers we have counts for
3 papers · 1 filter
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…
Anisotropic and high thermal conductivity in monolayer quasi-hexagonal fullerene: A comparative study against bulk phase fullerene
Haikuan Dong, Chenyang Cao, Penghua Ying +3
Recently a novel two-dimensional (2D) C based crystal called quasi-hexagonal-phase fullerene (QHPF) has been fabricated and demonstrated to be a promising candidate for 2D e…
GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
Zheyong Fan, Yanzhou Wang, Penghua Ying +17
We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in [Fan et al., Phys. Rev. B 104, 104309 (2…