Machine Learning-Driven SCAPS Modeling for Optimizing CH₃NH₃SnBr₃ Perovskite Solar Cells: Analytical Insights into Materials for Hole Transport and the Active Layer

This work explores the potential for integrating organic compounds, which serve as absorbers, with HTL to achieve steady, efficient PSCs. This study's proposed architecture is made up of ETL, HTL, and a CH₃NH₃SnBr₃ absorber. The effect of thickness, doping, and defect densities of absorber, HTL, and ETL layers and interface defect densities on a solar device's output is investigated utilizing the SCAPS-1D model. The FTO/SnS₂/CH₃NH₃SnBr₃/Ni structure has a <i>V</i>_OC of 0.991 V, a <i>J</i>_SC of 28.796 mA cm^-2, a PCE of 23.88%, and an FF of 83.69%. Concerns about stability, rapid oxidation of Sn²⁺ to Sn⁴⁺, and high defect density limit the efficiency of CH₃NH₃SnBr₃-based solar cells. The FTO/SnS₂/CH₃NH₃SnBr₃/HTL/Ni structure is investigated to prevent Sn oxidation, increase stability, and improve charge transport for improved performance. The analyzed structure is integrated with BiI₃/SnS/WSe₂/PTAA/CuS/CuI/C₆TBTAPH₂/CBTS layers as an HTL, resulting in a maximum <i>V</i>_OC of 1.128 V, a <i>J</i>_SC of 34.014 mA cm^-2, a PCE of 33.70%, and an FF of 87.83% with the FTO/SnS₂/CH₃NH₃SnBr₃/CBTS/Ni structure. The performance matrix of the investigated best optimum solar cell was predicted by ML with an accuracy rate of roughly 83.75%. This study's useful design and important discoveries could result in the creation of an inexpensive CH₃NH₃SnBr₃ thin-film solar cell.