Rapid direct-current (DC) surrogate modeling of gallium nitride (GaN) high-electron-mobility transistors (HEMTs) requires accurate prediction of the current-capability, conduction-loss, and self-heating indicators used in geometry screening. This work presents an electrothermal decoupled multiplicative physics-guided n...
Aluminum nitride (AlN) is an important thermal management material whose high lattice thermal conductivity is strongly suppressed by oxygen impurities. We investigate phonon scattering by oxygen-related defects using pretrained universal machine-learning interatomic potentials (MLIPs), molecular dynamics (MD), and phon...
Tantalum is a candidate material for advanced nuclear systems, but its irradiation damage mechanisms remain unclear. Using molecular dynamics with the UNEP-v1-Ziegler Biersack Littmark machine-learning potential, we simulated body-centered cubic Ta under 1–50 keV PKA irradiation at 300–900 K. Results show that threshol...
The microwave probed photoconductivity (MW-PC), differential absorption (DA) and light induced transient grating (LITG) techniques have been combined to examine carrier recombination and trapping characteristics in intrinsic GaN epi-layers, grown on Ammono substrates before and after neutron irradiation. Carrier lifeti...
Gallium oxide (Ga₂O₃), an ultra-wide bandgap semiconductor, is a promising platform for next-generation nuclear sensors in extreme environments. However, a key challenge remains: can radiation-induced damage be intrinsically mitigated during operation rather than passively tolerated? The interplay between defect format...
In laser directed energy deposition (LDED) additive manufacturing, monitoring internal defects based on melt pool features is critical for ensuring product quality, process efficiency, and operational safety. However, existing monitoring approaches remain constrained by two key limitations: (i) the scarcity of defect-l...
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