Ministry of Industry and Information Technology

output

20142026

most citedNSFnets (Navier-Stokes Flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

1.2k citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing 2023 · cond-mat.mtrl-sciShow all

3 papers · 2 filters

cond-mat.mtrl-sci2023★ 20 cited

Dissimilar thermal transport properties in $κ$ -Ga $_{2}$ O $_{3}$ and $β$ -Ga $_{2}$ O $_{3}$ revealed by machine-learning homogeneous nonequilibrium molecular dynamics simulations

Xiaonan Wang, Jinfeng Yang, Penghua Ying +3

The lattice thermal conductivity (LTC) of Ga $_{2}$ O $_{3}$ is an important property due to the challenge in the thermal management of high-power devices. We develop machine-learned neur…

cond-mat.mtrl-sci2023★ 8 cited

Strain effects in twisted spiral antimonene

Ding-Ming Huang, Xu Wu, Kai Chang +4

van der Waals (vdW) layered materials exhibit fruitful novel physical properties. The energy band of such materials depends strongly on their structures and a tremendous variation…

cond-mat.mtrl-sci2023★ 28 cited

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization

Li Huang, Xianghua Kong, Qi Zheng +17

Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, we show surface kagome electronic states…

Dissimilar thermal transport properties in κ-Ga2​O3​ and β-Ga2​O3​ revealed by machine-learning homogeneous nonequilibrium molecular dynamics simulations

Strain effects in twisted spiral antimonene

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization

Dissimilar thermal transport properties in $κ$ -Ga $_{2}$ O $_{3}$ and $β$ -Ga $_{2}$ O $_{3}$ revealed by machine-learning homogeneous nonequilibrium molecular dynamics simulations