Wu, Jing ; Zhou, E. ; Huang, An ; Zhang, Hongbin ; Hu, Ming ; Qin, Guangzhao (2024)
Deep-potential enabled multiscale simulation of gallium nitride devices on boron arsenide cooling substrates.
In: Nature Communications, 15 (1)
doi: 10.1038/s41467-024-46806-7
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
High-efficient heat dissipation plays critical role for high-power-density electronics. Experimental synthesis of ultrahigh thermal conductivity boron arsenide (BAs, 1300 W m−1K−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−2K−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.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2024 |
Autor(en): | Wu, Jing ; Zhou, E. ; Huang, An ; Zhang, Hongbin ; Hu, Ming ; Qin, Guangzhao |
Art des Eintrags: | Bibliographie |
Titel: | Deep-potential enabled multiscale simulation of gallium nitride devices on boron arsenide cooling substrates |
Sprache: | Englisch |
Publikationsjahr: | 25 März 2024 |
Ort: | London |
Verlag: | Nature |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Nature Communications |
Jahrgang/Volume einer Zeitschrift: | 15 |
(Heft-)Nummer: | 1 |
Kollation: | 9 Seiten |
DOI: | 10.1038/s41467-024-46806-7 |
Zugehörige Links: | |
Kurzbeschreibung (Abstract): | High-efficient heat dissipation plays critical role for high-power-density electronics. Experimental synthesis of ultrahigh thermal conductivity boron arsenide (BAs, 1300 W m−1K−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−2K−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. |
ID-Nummer: | Artikel-ID: 2540 |
Zusätzliche Informationen: | An Author Correction to this article was published on 16 April 2024 |
Fachbereich(e)/-gebiet(e): | 11 Fachbereich Material- und Geowissenschaften 11 Fachbereich Material- und Geowissenschaften > Materialwissenschaft 11 Fachbereich Material- und Geowissenschaften > Materialwissenschaft > Fachgebiet Theorie magnetischer Materialien |
Hinterlegungsdatum: | 14 Jun 2024 12:23 |
Letzte Änderung: | 14 Jun 2024 13:29 |
PPN: | 519163567 |
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