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Zheyong Fan

Showing results (1-10 of 37) with videos related to

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Journal of Physics. Condensed Matter : an Institute of Physics Journal|December 23, 2021
Improving the accuracy of the neuroevolution machine learning potential for multi-component systemsZheyong Fan
Journal of Physics. Condensed Matter : an Institute of Physics Journal|December 5, 2023
Combining the D3 dispersion correction with the neuroevolution machine-learned potentialPenghua Ying, Zheyong Fan
Journal of Chemical Information and Modeling|January 29, 2026
Improving Robustness and Training Efficiency of Machine-Learned Potentials by Incorporating Short-Range Empirical PotentialsZihan Yan, Zheyong Fan, Yizhou Zhu
Medical Physics|February 4, 2023
Technical note: TERMA scaling as an effective heterogeneity correction model for convolution-based external-beam photon dose calculationsLinda Laakkonen, Zheyong Fan, Ari Harju
Physical Chemistry Chemical Physics : PCCP|September 20, 2018
Heat transport in pristine and polycrystalline single-layer hexagonal boron nitrideHaikuan Dong, Petri Hirvonen, Zheyong Fan, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|September 14, 2021
GPU_PBTE: an efficient solver for three and four phonon scattering rates on graphics processing unitsBo Zhang, Zheyong Fan, C Y Zhao, et al.
Nanoscale Research Letters|October 18, 2012
Enhanced thermoelectric performance in three-dimensional superlattice of topological insulator thin filmsZheyong Fan, Jiansen Zheng, Hui-Qiong Wang, et al.
Nanotechnology|September 8, 2011
Mechanical properties of grafold: a demonstration of strengthened grapheneYongping Zheng, Ning Wei, Zheyong Fan, et al.
ACS Nano|December 8, 2023
Tuning the Through-Plane Lattice Thermal Conductivity in van der Waals Structures through Rotational (Dis)orderingFredrik Eriksson, Erik Fransson, Christopher Linderälv, et al.
Physical Review Letters|July 23, 2021
Ultrahigh Convergent Thermal Conductivity of Carbon Nanotubes from Comprehensive Atomistic ModelingGiuseppe Barbalinardo, Zekun Chen, Haikuan Dong, et al.
Pageof 4

Showing results (1-10 of 37) with videos related to

Sort By:
Pageof 4
Journal of Physics. Condensed Matter : an Institute of Physics Journal|December 23, 2021
Improving the accuracy of the neuroevolution machine learning potential for multi-component systemsZheyong Fan
Journal of Physics. Condensed Matter : an Institute of Physics Journal|December 5, 2023
Combining the D3 dispersion correction with the neuroevolution machine-learned potentialPenghua Ying, Zheyong Fan
Journal of Chemical Information and Modeling|January 29, 2026
Improving Robustness and Training Efficiency of Machine-Learned Potentials by Incorporating Short-Range Empirical PotentialsZihan Yan, Zheyong Fan, Yizhou Zhu
Medical Physics|February 4, 2023
Technical note: TERMA scaling as an effective heterogeneity correction model for convolution-based external-beam photon dose calculationsLinda Laakkonen, Zheyong Fan, Ari Harju
Physical Chemistry Chemical Physics : PCCP|September 20, 2018
Heat transport in pristine and polycrystalline single-layer hexagonal boron nitrideHaikuan Dong, Petri Hirvonen, Zheyong Fan, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|September 14, 2021
GPU_PBTE: an efficient solver for three and four phonon scattering rates on graphics processing unitsBo Zhang, Zheyong Fan, C Y Zhao, et al.
Nanoscale Research Letters|October 18, 2012
Enhanced thermoelectric performance in three-dimensional superlattice of topological insulator thin filmsZheyong Fan, Jiansen Zheng, Hui-Qiong Wang, et al.
Nanotechnology|September 8, 2011
Mechanical properties of grafold: a demonstration of strengthened grapheneYongping Zheng, Ning Wei, Zheyong Fan, et al.
ACS Nano|December 8, 2023
Tuning the Through-Plane Lattice Thermal Conductivity in van der Waals Structures through Rotational (Dis)orderingFredrik Eriksson, Erik Fransson, Christopher Linderälv, et al.
Physical Review Letters|July 23, 2021
Ultrahigh Convergent Thermal Conductivity of Carbon Nanotubes from Comprehensive Atomistic ModelingGiuseppe Barbalinardo, Zekun Chen, Haikuan Dong, et al.
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