An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

TLDR

Large datasets are ubiquitous, yet research fields rarely benefit from them due to inconsistent formatting, undocumented storage, or improper dissemination. The study extracts all meaningful device data from peer‑reviewed metal‑halide perovskite solar cell papers and makes it available in a database, while developing open‑source procedures for data analysis. Data from over 42,400 devices with up to 100 parameters each were compiled into an open‑source database, graphics, and analysis tools that are publicly available and will continue to evolve. The resulting database and tools enable extensive field‑wide data capture, interactive exploration, and graphical representation, and can be applied to many materials science, engineering, and bioscience fields.

Abstract

Abstract Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences.