Physics-grounded machine learning for inverse design of TiO2/CuInGaS2/rGO–CuxS quantum-dot solar cells using surrogate modeling and SCAPS-based validation
The inverse design of multilayer heterojunction solar cells is difficult because device efficiency depends on coupled structural and electronic parameters, while extensive SCAPS-1D parameter sweeps become costly as the design space grows. This work develops a physics-grounded machine-learning framework for TiO 2...