Example of Data-driven Superconducting Wire Research
The data-driven research has progressed in recent years. Particularly in the field of superconducting materials, there has been active research into the search for new materials, especially by materials informatics (MI). On the other hand, in a superconducting material that has three critical points, the critical current density of the three critical points changes greatly depending on the material manufacturing process. The critical current density properties greatly depend on the material structure, and there are many parameters to obtain the appropriate mictrostructures for various applications. Therefore, these data will be useful to a wide range of users, including materials researchers and even superconducting wire suppliers and a field of application. In this commentary, we provided an overview of data collection, storage, and use, and then presented the progress of some ongoing research and discussed future development possibilities.
Authors
- Masayoshi Inoue (ORCID: https://orcid.org/0000-0002-5323-0454)
- A. Matsumoto (ORCID: https://orcid.org/0000-0002-6388-2130)
- Shigeyuki Matsunami
- Shinya Kawashima (ORCID: https://orcid.org/0000-0001-5282-4720)
- Hiroshi Narazaki
Institutions
- Fukuoka Institute of Technology (JP)
- National Institute for Materials Science (JP)
Publication Details
- Journal
- IEEJ Transactions on Fundamentals and Materials
- Published
- 2024-08-31
- DOI
- https://doi.org/10.1541/ieejfms.144.366
- Citations
- 1
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.12