Deep-potential enabled multiscale simulation of gallium nitride devices on boron arsenide cooling substrates

High-efficient heat dissipation plays critical role for high-power-density electronics. Experimental synthesis of ultrahigh thermal conductivity boron arsenide (BAs, 1300 W m −1 K −1 ) cooling substrates into the wide-bandgap semiconductor of gallium nitride (GaN) devices has been realized. However,...

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Published in:Nature communications Vol. 15; no. 1; p. 2540
Main Authors: Wu, Jing, Zhou, E, Huang, An, Zhang, Hongbin, Hu, Ming, Qin, Guangzhao
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 25-03-2024
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Summary:High-efficient heat dissipation plays critical role for high-power-density electronics. Experimental synthesis of ultrahigh thermal conductivity boron arsenide (BAs, 1300 W m −1 K −1 ) cooling substrates into the wide-bandgap semiconductor of gallium nitride (GaN) devices has been realized. However, the lack of systematic analysis on the heat transfer across the GaN-BAs interface hampers the practical applications. In this study, by constructing the accurate and high-efficient machine learning interatomic potentials, we perform multiscale simulations of the GaN-BAs heterostructures. Ultrahigh interfacial thermal conductance of 260 MW m −2 K −1 is achieved, which lies in the well-matched lattice vibrations of BAs and GaN. The strong temperature dependence of interfacial thermal conductance is found between 300 to 450 K. Moreover, the competition between grain size and boundary resistance is revealed with size increasing from 1 nm to 1000 μm. Such deep-potential equipped multiscale simulations not only promote the practical applications of BAs cooling substrates in electronics, but also offer approach for designing advanced thermal management systems. Efficient heat dissipation is critical to optimize high-power devices. Here, the authors report high interfacial thermal conductance in GaN-BAs heterostructures and investigate the competition between grain size and boundary resistance by multiscale simulations.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-024-46806-7