Interpretable Machine Learning Analysis of Perovskite Solar Cells Based on SCAPS-1D Simulations: Insights into Performance-Limiting Mechanisms
This work presents an interpretable machine learning framework to investigate the factors influencing the efficiency of perovskite solar cells. A dataset of approximately 5,000 simulations was generated using SCAPS-1D simulations by varying key parameters, including bandgap, defect density, carrier mobility, doping con...