Curated materials data of hybrid perovskites: approaches and potential usage

Over the past decade, hybrid perovskite research has evolved to a point where the literature contains an enormous volume of chemical and physical information. However, many essential material design challenges remain open for researchers to address. The dispersed nature of the large, rapidly growing body of hybrid perovskite materials data poses a barrier to systematic discovery efforts, which can be solved by materials property databases, either by high-throughput or by systematic, accurate human-curated efforts. This opinioned review article discusses the necessity, challenges, and requirements of building such data libraries. In light of using machine learning (ML) and related tools to solve specific problems, the importance of information related to different material attributes and properties is also highlighted.

Automated summary

In the past decade, research on hybrid perovskites has made significant progress, but there are still material design challenges to be addressed. The dispersed nature of the data requires the establishment of material property databases for systematic research. Additionally, the importance of information related to different material attributes and properties is emphasized when using machine learning tools to solve problems.