HADB: A materials-property database for hard-coating alloys
نویسندگان
چکیده
Data-driven approaches are becoming increasingly valuable for modern science, and they making their way into industrial research development (R&D). Supervised machine learning of statistical models can utilize databases materials parameters to speed up the exploration candidate experimental synthesis characterization. In this paper we introduce HADB database, which contains properties industrially relevant chemically disordered hard-coating alloys, focusing on thermodynamic, elastic mechanical properties. We present technical implementations database infrastructure including support browse, query, retrieval, API access through OPTIMADE make data findable, accessible, interoperable, reusable (FAIR). Finally, demonstrate usefulness by training a graph-based (ML) model predict alloys. The ML is shown bulk shear moduli out out-of-sample alloys with less than 6 GPa mean average error.
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ژورنال
عنوان ژورنال: Thin Solid Films
سال: 2023
ISSN: ['1879-2731', '0040-6090']
DOI: https://doi.org/10.1016/j.tsf.2022.139627