D7.5 Update to D7.2 (metastudy based on the perovskite database) taking into account latest data

D7.5 Update to D7.2 (metastudy based on the perovskite database) taking into account latest data

One of the main focuses of this task was the broader adoption of FAIR (Findable, Accessible, Interoperable, and Reusable) data principles in the perovskite PV community. A central achievement of has been the establishment of the Perovskite Database, an open-access platform that compiles metadata and performance metrics from over 16,000 publications. This initiative has provided the research community with a valuable resource for analyzing trends, identifying gaps, and fostering collaboration. However, challenges such as the time-intensive nature of manual data extraction, inconsistent reporting practices, and limited community contributions to the database have highlighted the need for more automated and standardized approaches. Emerging tools, such as large language models (LLMs), have shown promise in addressing these challenges by automating data extraction from scientific literature. Based on the database several metastudies were carried out the essence of a few from within the project we highlight in this report.
In this context, we also emphasize the importance of standardized testing protocols, such as ISOS procedures, to ensure the reliability and comparability of aging and stability data. Metadata studies conducted on the Perovskite Database revealed critical insights into device performance, stability, and material optimization, underscoring the need for comprehensive and high-quality datasets to support machine learning (ML) applications and further innovation. In collaboration with the FAIRmat initiative, we developed research data management platforms, based on NOMAD (Oasis), to facilitate the secure and efficient sharing of (experimental) data. These platforms enable researchers to adhere to FAIR principles while maintaining control over sensitive information. The adoption of these tools by research institutions worldwide marks a significant step toward creating a unified and collaborative data-sharing ecosystem for perovskite PV research.
We conclude with actionable recommendations to improve data quality, promote standardized testing, and encourage the adoption of research data management platforms. These efforts aim to accelerate the development and commercialization of perovskite PV technology, ensuring its long-term stability, scalability, and efficiency.