MODELLING ENERGY CONVERSION MECHANISMS IN SEMICONDUCTOR SOLAR CELLS USING QUANTUM PHYSICS

The efficiency of semiconductor solar cells remains fundamentally constrained by classical models, particularly the Shockley–Queisser (SQ) limit. To overcome this bottleneck, this study proposes a quantum-physics-based modeling framework for analyzing energy conversion mechanisms in emerging photovoltaic materials. A synthetic dataset encompassing ten semiconductors ranging from traditional silicon to novel perovskites and metal oxides was constructed based on key parameters: bandgap energy, quantum efficiency, crystal structure, and conversion efficiency. Statistical analyses revealed that quantum efficiency is the strongest linear predictor of performance, with a Pearson correlation coefficient of +0.98. Conversely, bandgap energy showed a moderate negative correlation (−0.43), consistent with theoretical expectations that efficiency peaks near the 1.3–1.6 eV range. The results are validated against contemporary advances in charge transport optimization, tandem architectures, and quantum dot integration, as evidenced by recent literature. This study contributes a multivariable modeling approach that synthesizes quantum mechanical principles with empirical design, offering predictive insights for material selection and device optimization. The findings advocate for integrative strategies that span photon absorption, carrier transport, and band engineering. This work lays a foundation for further investigations that incorporate exciton dynamics and temperature effects, ultimately supporting the development of high-efficiency quantum solar cells.