Diamond offers excellent heat sink for high power high-electron-mobility transistors based on III-nitrides. However

the GaN/diamond interfaces suffer from low thermal conductance due to phonon mismatch. Although AlN interlayers can mitigate this issue

processing-induced carbon vacancies and subsurface disorder near the AlN/diamond interface recreate a new thermal bottleneck. In this study

we employ deep learning-enhanced non-equilibrium molecular dynamics (NEMD) simulations to investigate atomic-scale thermal transport across AlN/diamond interfaces

with a particular focus on quantifying the impact of carbon vacancies. Results show interfacial thermal conductance (ITC) for AlN-Al/C(1 1 1) depends non-monotonically on the carbon vacancy concentration. The ITC peaks at 151.7 MW·m

−2

K

−1

at a carbon vacancy concentration of 2.4% due to the formation of resonant vibrational states that br

idge the phonon gap and promote phonon delocalization

enabling efficient tunneling across the interface. However

beyond this optimal concentration

vacancy clustering induces destructive phonon interference

strong scattering

and severe localization effects

leading to a sharp decline in ITC. This work provides a pathway for optimizing AlN thermal bridges to achieve low thermal resistance in GaN-on-diamond devices through precise control of vacancy concentration and crystallinity.