Gallium oxide (${\mathrm{Ga}}_2{\mathrm{O}}_3$) has attracted significant interest for its unique potential, especially in power electronics. However, its low and anisotropic thermal conductivity poses a major challenge for heat dissipation. Here, we explore an effective cooling strategy centering on the heterogeneous integration of β-${\mathrm{Ga}}_2{\mathrm{O}}_3$ devices with cubic boron arsenide (cBAs), an emerging material with an ultrahigh thermal conductivity κ of ∼1300 ${\mathrm{W}\mathrm{m}}^{-1}{\mathrm{K}}^{-1}$. Machine-learned potentials for representative β-${\mathrm{Ga}}_2{\mathrm{O}}_3/\mathrm{cBAs}$ interfaces are trained, enabling accurate and efficient calculation of the interfacial thermal conductance G via nonequilibrium molecular dynamics. At 300 K, remarkable G values of 681 ± 29 ${\mathrm{MW}\mathrm{m}}^{-2}{\mathrm{K}}^{-1}$ and 752 ± 32 ${\mathrm{MW}\mathrm{m}}^{-2}{\mathrm{K}}^{-1}$ are predicted for $\mathrm{Ga}$-$\mathrm{As}$ and $\mathrm{O}$-$\mathrm{B}$ bonding across the interface, respectively, which are primarily attributed to the well-matched phonon density of states considering the similar Debye temperatures of β-${\mathrm{Ga}}_2{\mathrm{O}}_3$ and cBAs. Moreover, finite-element simulations directly show a notable device temperature reduction when comparing cBAs with other substrates. The simultaneously ultrahigh κ and G highlight cBAs as an ideal substrate for ${\mathrm{Ga}}_2{\mathrm{O}}_3$ electronics.

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• Heat transfer
• Phonons
• Thermal boundary conductance
• Thermal conductivity
• Solid-solid interfaces
• Transparent conducting oxides
• Machine learning
• Molecular dynamics