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

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 dependenc

SUBMITTER: Wu J 

PROVIDER: S-EPMC10963741 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature