Design strategies for heterojunction silicon/CsSnBr3 lead-free tandem solar cells using machine learning and SCAPS-1D

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• Extensive Dataset and ML Application : We generated a dataset of 29,831 unique device configurations, systematically analyzed using advanced ML models, including XGBoost (XGB) and Convolutional Neural Networks (CNN), ensuring high predictive accuracy in device performance. • Optimized Tandem Structure : The proposed TSC configuration, featuring an optimized CsSnBr₃ top cell thickness of 0.59 µm, and best optimized transport layers achieves a power conversion efficiency (PCE) of 36.44 % with efficient current matching at 21.29 mA/cm². • Impact of Doping on Performance : A detailed study on the effect of doping density revealed that optimizing the acceptor density (NACsSnBr₃) between 1 × 10¹⁷ and 1 × 10¹⁹ cm⁻³ significantly enhances efficiency, reaching up to 36.44 % without recombination-induced losses. • This study highlights the practical challenges in fabricating the proposed high-efficiency CsSnBr₃/c-Si tandem solar cell, including doping limitations, material instability, and interface losses. It suggests mitigation strategies like SnF₂ doping, ALD-based Al₂O₃ encapsulation, and optimized deposition techniques to enhance stability, while acknowledging the gap between simulation and real-world performance. The integration of machine learning with SCAPS-1D simulations has led to significant advancements in optimizing tandem solar cells, particularly in perovskite/silicon architectures. This study focuses on enhancing CsSnBr 3 -based perovskite solar cells as the top cell in a tandem configuration, aiming to achieve efficient current matching and maximize power conversion efficiency. A dataset of 29,831 unique device configurations was generated, analyzing critical parameters such as bandgap alignment, dielectric permittivity, doping density, and charge transport properties using 10 different machine learning models. The optimized structure FTO/WS 2 /CsSnBr 3 /Cu 2 O/ITO/a-Si(n)/a-Si(i)/c-Si(p)/a-Si(i)/a-Si(p) demonstrated optimal short circuit current matching at 21.29 mA/cm², and open circuit voltage of 2.06 V achieving an impressive tandem solar cell efficiency of 36.44 %. This study also investigates how doping density impacts device performance, focusing on the delicate balance between carrier transport and recombination. The results underscore the importance of carrier behavior and interface optimization in maximizing the efficiency of perovskite/silicon tandem solar cells. By employing a data-driven approach, the research presents strategies for improving solar cell performance beyond 30 % efficiency, contributing to the development of affordable, scalable photovoltaic technologies for advancing future renewable energy solutions.