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Abstract Hybrid perovskites are interesting optoelectronic materials. The perovskite ABX₃structure offers a vast compositional space, and we have identified over 300 perovskite ions. This flexibility enables tuneable properties and has significantly contributed to the success of perovskite optoelectronics. However, this diversity also leads to confusion, ambiguity, and inconsistencies causing challenges for data mining and machine learning applications. To address this issue, we propose guidelines and a JSON schema to standardize the reporting of perovskite compositions. The schema adheres to IUPAC recommendations and is designed to make data both human- and machine-readable. It captures key descriptors such as perovskite composition, molecular formula, SMILES representation, IUPAC name, and CAS number for each ion. To facilitate adoption, we have developed utilities to automatically generate comprehensive and standardized perovskite descriptions from standard ion abbreviations and stoichiometric coefficients. Additionally, we provide a curated database of all identified perovskite ions with associated descriptive data. 

Abstract Emerging photovoltaics (PVs) focus on a variety of applications complementing large scale electricity generation. Organic, dye‐sensitized, and some perovskite solar cells are considered in building integration, greenhouses, wearable, and indoor applications, thereby motivating research on flexible, transparent, semitransparent, and multi‐junction PVs. Nevertheless, it can be very time consuming to find or develop an up‐to‐date overview of the state‐of‐the‐art performance for these systems and applications. Two important resources for recording research cells efficiencies are the National Renewable Energy Laboratory chart and the efficiency tables compiled biannually by Martin Green and colleagues. Both publications provide an effective coverage over the established technologies, bridging research and industry. An alternative approach is proposed here summarizing the best reports in the diverse research subjects for emerging PVs. Best performance parameters are provided as a function of the photovoltaic bandgap energy for each technology and application, and are put into perspective using, e.g., the Shockley–Queisser limit. In all cases, the reported data correspond to published and/or properly described certified results, with enough details provided for prospective data reproduction. Additionally, the stability test energy yield is included as an analysis parameter among state‐of‐the‐art emerging PVs.