Developing an oxidation materials ontology for data-driven materials design
Materials data is complex, and managing and storing materials data for use and reuse is a common challenge. An ontology-based data management framework can address these challenges through encoding data attributes and relationships in a flexible way. This presentation discusses the creation of an ontology for alloy oxidation test data and reviews the logic, structure and interoperability of the ontology.
Authors
- Wissam Abdo Saidi (ORCID: https://orcid.org/0000-0001-6714-4832)
- Leebyn Chong (ORCID: https://orcid.org/0000-0003-4881-9210)
- Richard P. Oleksak (ORCID: https://orcid.org/0000-0003-4642-8152)
- Madison Wenzlick (ORCID: https://orcid.org/0000-0003-1375-4218)
- Michael C. Gao (ORCID: https://orcid.org/0000-0002-0515-846X)
- William Trehern (ORCID: https://orcid.org/0000-0002-4921-5331)
Institutions
- National Energy Technology Laboratory (US)
Publication Details
- Published
- 2025-03-27
- DOI
- https://doi.org/10.2172/2553005
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Energy
- National Energy Technology Laboratory