This review highlights the potential of emerging inorganic chalcogenide–silicon tandem solar cells, which address efficiency and stability limitations of single-junction devices and offer a less-toxic, more stable alternative for tandem applications.

In the Kesterite family, the Cu₂ZnSn(S,Se)₄ (CZTSSe) thin-film solar cells (TFSCs) have demonstrated the highest device efficiency with non-stoichiometric cation composition ratios. These composition ratios have a strong influence on the structural, optical, and electrical properties of the CZTSSe absorber layer. So, in this work, a machine learning (ML) approach is employed to evaluate effect composition ratio on the device parameters of CZTSSe TFSCs. In particular, the bi-metallic ratios like Cu/Sn, Zn/Sn, Cu/Zn, and overall Cu/(Zn+Sn) cation composition ratio are investigated. To achieve this, different machine learning algorithms, such as decision trees (DTs) and classification and regression trees (CARTs), are used. In addition, the output performance parameters of CZTSSe TFSCs are predicted by both continuous and categorical approaches. Artificial neural networks (ANN) and XGBoost (XGB) algorithms are employed for the continuous approach. On the other hand, support vector machine and k-nearest neighbor’s algorithms are also used for the categorical approach. Through the analysis, it is observed that the DT and CART algorithms provided a critical composition range well suited for the fabrication of highly efficient CZTSSe TFSCs, while the XGB and ANN showed better prediction accuracy among the tested algorithms. The present work offers valuable guidance towards the integration of the ML approach with experimental studies in the field of TFSCs.

The CN/BO-24 composite, having 24 wt% of Bi₂O₂CO₃–Bi₄O₇ (BO) loaded on g-C₃N₄, degrades 98.3% rhodamine B within 45 min, surpassing both pristine g-C₃N₄ (90.6%) and BO (9.4%).

The solar power generation market has experienced rapid growth in recent years, with the industry increasingly shifting towards building-integrated solar solutions due to limitations in ground-based installation sites. Building-integrated photovoltaics (BIPVs) have gained attention for their potential to efficiently utilize land resources and enhance the spatial utilization of buildings. While current BIPV systems primarily focus on utilizing roof surfaces for solar energy generation, exploring building façades (vertical surfaces) for solar power generation is essential for future advancements. To address this challenge, a novel approach is required to reduce the weight of conventional silicon solar modules. This study aimed to design, manufacture, and demonstrate thin-film solar modules that are lightweight and flexible for attachment to building exteriors. The manufactured thin-film solar modules had a conversion efficiency of 13.8% and achieved technical completeness by obtaining KS certification (KS C 8562) for thin-film solar modules. A demonstration study of a curved roof solar module was conducted to verify the performance and applicability of curved thin-film solar modules. The demonstration system had a capacity of 7.36 kWp, and its output was analyzed over 27 months. During this period, the monthly average capacity factor was 15%, demonstrating superior results compared with the utilization rate in the same region.