Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics

Abstract

The emerging photovoltaic (PV) technologies, such as organic and perovskite PVs, have the characteristics of complex compositions and processing, resulting in a large multidimensional parameter space for the development and optimization of the technologies. Traditional manual methods are time-consuming and labor-intensive in screening and optimizing material properties. Materials genome engineering (MGE) advances an innovative approach that combines efficient experimentation, big database and artificial intelligence (AI) algorithms to accelerate materials research and development. High-throughput (HT) research platforms perform multidimensional experimental tasks rapidly, providing a large amount of reliable and consistent data for the creation of materials databases. Therefore, the development of novel experimental methods combining HT and AI can accelerate materials design and application, which is beneficial for establishing material-processing-property relationships and overcoming bottlenecks in the development of emerging PV technologies. This review introduces the key technologies involved in MGE and overviews the accelerating role of MGE in the field of organic and perovskite PVs.