526 citations · 2k across the 23 of their papers we have counts for
12 papers · 1 filter
Anisotropic and isotropic elasticity and thermal transport in monolayer C networks from machine-learning molecular dynamics
Qing Li, Haikuan Dong, Penghua Ying +1
Two-dimensional fullerene networks have recently attracted increasing interest due to their diverse bonding topologies and mechanically robust architectures. In this work, we devel…
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
Ting Liang, Ke Xu, Eric Lindgren +16
While machine-learned interatomic potentials offer near-quantum-mechanical accuracy for atomistic simulations, many are material-specific or computationally intensive, limiting the…
Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy enabled by neuroevolution potential on desktop GPUs
Xiaoye Zhou, Yuqi Liu, Benrui Tang +5
First-principles molecular dynamics simulations of heat transport in systems with large-scale structural features are challenging due to their high computational cost. Here, using…
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…
General-purpose machine-learned potential for 16 elemental metals and their alloys
Keke Song, Rui Zhao, Jiahui Liu +25
Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicabil…
Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials
Zheyong Fan, Yang Xiao, Yanzhou Wang +3
We propose an efficient approach for simultaneous prediction of thermal and electronic transport properties in complex materials. Firstly, a highly efficient machine-learned neuroe…
Exactly equivalent thermal conductivity in finite systems from equilibrium and nonequilibrium molecular dynamics simulations
Haikuan Dong, Zheyong Fan, Ping Qian +1
In a previous paper [Physical Review B \textbf{103}, 035417 (2021)], we showed that the equilibrium molecular dynamics (EMD) method can be used to compute the apparent thermal cond…
Heat transport across graphene/hexagonal-BN tilted grain boundaries from phase-field crystal model and molecular dynamics simulations
Haikuan Dong, Petri Hirvonen, Zheyong Fan +3
We study the interfacial thermal conductance of grain boundaries (GBs) between monolayer graphene and hexagonal boron nitride (h-BN) sheets using a combined atomistic approach. Fir…
Thermal conductivity reduction in carbon nanotube by fullerene encapsulation: A molecular dynamics study
Haikuan Dong, Zheyong Fan, Ping Qian +2
Single-walled carbon nanotubes (SWCNTs) in their pristine form have high thermal conductivity whose further improvement has attracted a lot of interest. Some theoretical studies ha…
Heat transport in pristine and polycrystalline single-layer hexagonal boron nitride
Haikuan Dong, Petri Hirvonen, Zheyong Fan +1
We use a phase field crystal model to generate large-scale bicrystalline and polycrystalline single-layer hexagonal boron nitride (h-BN) samples and employ molecular dynamics (MD)…
Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials
Zheyong Fan, Haikuan Dong, Ari Harju +1
The standard equilibrium Green-Kubo and nonequilibrium molecular dynamics (MD) methods for computing thermal transport coefficients in solids typically require relatively long simu…