HyStor: an experimental database of hydrogen storage properties for various metal alloy classes
Title | HyStor: an experimental database of hydrogen storage properties for various metal alloy classes |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Wilson, N, Verma, A, Maharana, PRanjan, Sahoo, ABhusan, Joshi, K |
Journal | International Journal of Hydrogen Energy |
Volume | 90 |
Pagination | 460-469 |
Date Published | NOV |
Type of Article | Article |
ISSN | 0360-3199 |
Keywords | Databases, machine learning, Metal hydrides, Solid-state hydrogen storage |
Abstract | In this work, we introduce the HyStor database, consisting of 1282 metal alloys along with their maximum hydrogen storage capacity (H2wt%) at a given absorption temperature. The curated HydPark database consist of 831 entries. We sourced compositions from research articles and various patent documents, resulting in addition of 451 compositions to the HydPark database. The addition is reflected in the data across all existing classes of alloys. Further, low entropy alloys (LEA), medium entropy alloys (MEA) and high entropy alloys (HEA) have been newly included classes. This has broadened the scope of the database to encompass the latest materials of interest for hydrogen storage. HyStor contains representation of 54 elements, with a temperature range of 200-800 K, and H2wt% ranging from 0.1 to 7.19. We conducted thorough checks for duplicate entries, erroneous data, and conflicting compositions within the database to ensure data quality. Furthermore, we conducted multiple tests to identify potential outlier compositions. The data curation and updation reflects into slight improved error metrics of the HYST model, reducing the Mean Absolute Error (MAE) from 0.31 to 0.29 and increasing the R2 score from 0.77 to 0.79. |
DOI | 10.1016/j.ijhydene.2024.09.390 |
Type of Journal (Indian or Foreign) | Foreign |
Impact Factor (IF) | 7.2 |
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