Abstract
New developments and publications on alkali metal solid-state batteries are being published at a high rate, with the total number of publications now in the thousands, but the search and analysis of the data in these publications is still largely done using key words and through careful reading of the article and the supporting information. The challenges of efficiently searching and extracting data from thousands of publications in a field are also present in other fields, such as perovskite solar cells, for which a large (>15,000) set of cell data has been entered into a database that continues to be updated.1 A database for alkali metal (e.g., based on Na+ and Li+ conduction) solid-state cells that could be easily searched and that facilitated advanced forms of data analysis could accelerate research progress, and is consistent with efforts such as definition of the “Principles of the Battery Data Genome” and the BIG-MAP project.2 In this talk, we describe our approach to creating an ontology and database for lab-scale solid-state cells, along with results to date. Key areas for the ontology include component material identities, material properties, component properties (e.g., active material loading, mass fractions, thicknesses), processing conditions for materials and the cell itself (e.g., ball milling time, sintering time), and both performance (e.g., rate capability) and degradation (e.g., cycle life). Results based on several hundred solid state cells in our database are presented in terms of histogram plots, violin plots, correlation plots, and other representations. We also describe our efforts to integrate our ontology and tool with broader efforts in the field, and to make it broadly useful to battery researchers.1. Nature Energy, volume 7, pages 107–115 (2022) and https://www.perovskitedatabase.com/2. Joule 6, 2253–2271, October 19, 2022 and https://www.big-map.eu/dissemination/battinfo
Published Version
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