High-energy Al ion implantation is an indispensable technique for achieving precise doping in fabricating 4H‑SiC devices. However, it inevitably introduces interfacial damage and residual stress that can compromise subsequent manufacturing processes and device reliability. Conven
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High-energy Al ion implantation is an indispensable technique for achieving precise doping in fabricating 4H‑SiC devices. However, it inevitably introduces interfacial damage and residual stress that can compromise subsequent manufacturing processes and device reliability. Conventional destructive characterization techniques cannot provide real-time, in‑situ, nondestructive monitoring under process conditions, creating a major bottleneck in quality control. Here, we establish a predictive modeling framework that integrates multiscale simulations with advanced, non‑destructive micro‑Raman spectroscopy to systematically investigate the evolution of high-energy Al ion implantation–induced interface defects and residual stress in 4H-SiC. Simulation results reveal a linear relationship between the implantation dose and the formation of vacancies and interstitial defects, while the stress accumulation tends to saturate at higher doses due to a dynamic equilibrium among defect interactions. Complementary micro‐Raman spectroscopy corroborates the simulations, showing that the damaged interface layer deepens from approximately 300 nm at a dose of 1014 ions cm−2 to nearly 500 nm at 1016 ions cm−2, consistent with Monte Carlo predictions. Furthermore, the molecular dynamics simulations capture a trend of the implantation stress evolution with strong concurrence with the Raman-measured residual stress. This combined computational–experimental approach elucidates the fundamental mechanisms governing defect formation and residual stress in ion‑implanted 4H‑SiC, establishes implantation dose as the pivotal role of 4H-SiC in defect density and residual stress, and underscores the utility of optical‑based characterization in real‑time, non‑invasive quality control for advanced manufacturing.