Jinfeng Yang

κ

-Ga

_{2}

_{3}

and

β

-Ga

_{2}

_{3}

revealed by machine-learning homogeneous nonequilibrium molecular dynamics simulations

20 citations · 32 across the 2 of their papers we have counts for

collaborators

2 papers

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-sci2022★ 12 cited

Reliable and Broad-range Layer Identification of Au-assisted Exfoliated Large Area MoS $_{2}$ and WS $_{2}$ Using Reflection Spectroscopic Fingerprints

Bo Zou, Yu Zhou, Yan Zhou +9

The emerging Au-assisted exfoliation technique provides a wealth of large-area and high-quality ultrathin two-dimensional (2D) materials compared with traditional tape-based exfoli…

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

Reliable and Broad-range Layer Identification of Au-assisted Exfoliated Large Area MoS2​ and WS2​ Using Reflection Spectroscopic Fingerprints

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

Reliable and Broad-range Layer Identification of Au-assisted Exfoliated Large Area MoS $_{2}$ and WS $_{2}$ Using Reflection Spectroscopic Fingerprints