Design and Development of Perovskite Materials Using Machine Learning Techniques

The rapid advancement of perovskite material with the help of machine learning (ML), along with applications and the challenges, is discussed here. The development of high conversion efficiency perovskite materials is the key to modernizing third-generation solar cells, but with inefficient traditional trial-and-error methods, achieving the goal is very time-consuming. With ML, the latest technology, it is possible to predict the behavior of perovskite materials by knowing the features such as the structure, atomic or molecular characteristics, and chemical composition. As a result, ML is getting popular in the materials field. This chapter explores the integration of ML in the design and development of perovskite materials. It also mines specific methods employed in machine learning for designing perovskite materials, followed by a discussion of their applications in photovoltaic, sensor, catalytic perovskite, and light-emitting diodes (LEDs) devices. Finally, challenges in this area are addressed, along with an outline of future possibilities for research and development.