Development of High-Efficiency Perovskite Solar Cells and Their Integration with Machine Learning

Perovskite solar cells, as a rising star in third-generation photovoltaic technologies, have attracted extensive attention due to their high light absorption, tunable bandgap, and high power conversion efficiency, indicating substantial potential for future applications. Starting from the development history of perovskite solar cells, this review systematically comprehends the technological breakthroughs in the continuous improvement of power conversion efficiency since their invention, outlining the research status and technical bottlenecks. A detailed analysis is provided on the material characteristics and limitations of the lead-based perovskite systems. Critical obstacles towards commercialization are also identified, such as operational instability and the challenges associated with large-scale manufacturing. Finally, the potential role of machine learning in the discovery and design of new perovskite materials is highlighted, and future development directions have been outlined. Special focus is placed on the innovative applications of machine learning in material composition screening, material properties prediction, and process parameter optimization, with the aim of constructing a closed-loop research framework. The review aims to offer valuable insights and references for advancing the performance and industrial applications of perovskite solar cells.