Thermal boundary conductance of metal-diamond interfaces predicted by machine learning interatomic potentials

KZ Adnan and MR Neupane and TL Feng, INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 235, 126227 (2024).

DOI: 10.1016/j.ijheatmasstransfer.2024.126227

Thermal boundary conductance (TBC) across metal-diamond interfaces plays a critical role in the thermal management of future diamond-based ultrawide bandgap semiconductor devices. Molecular dynamics is a sophisticated method to predict TBC but is limited by the lack of reliable potential describing metal-diamond interfaces. In this work, we report the development of machine learning interatomic potentials and the prediction of TBCs of several technologically promising metal- diamond interfaces using nonequilibrium molecular dynamics. The predicted TBCs of relaxed Al, Mo, Zr, and Au-diamond interfaces are approximately 284, 93, 30, and 40 MW/m(2)K, respectively, after quantum corrections. The dependence of TBCs on pressure is also studied. The corresponding thermal boundary resistances are equivalent to 0.83-mu m thick of Al, 1.5-mu m Mo, 0.73-mu m Zr, and 7.9-mu m Au, respectively. We find that the conventional simple models, such as the acoustic mismatch model and diffuse mismatch model, even including the full-band phonon dispersion from first principles, largely misestimate the TBC values because of their inability to include the interfacial structural and bonding details as well as inelastic transmission. The quantum- corrected TBC values for the metal-diamond interfaces correlate well with the quantum-corrected phonon specific heat of metals, instead of diamond. Additionally, it is found that the Debye temperature shows a stronger correlation with the TBC than the elastic modulus does. The low TBC values between metals and diamond need to be considered in future diamond-based semiconductor devices.

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