Predefined attention-focused mechanism using center-environment features: a machine learning study of alloying effects on the stability of Nb <sub>5</sub> Si <sub>3</sub> alloys
Machine learning prediction of substitution energies of Nb 5 Si 3 using the Center-Environment (CE) features with the environment atoms defined by the Atomic Environment Type (AET).
Authors
- Quan Qian (ORCID: https://orcid.org/0000-0003-0051-7440)
- Yuchao Tang (ORCID: https://orcid.org/0000-0002-4404-9952)
- Bin Xiao (ORCID: https://orcid.org/0000-0003-1174-2491)
- Shuizhou Chen
- Yi Liu (ORCID: https://orcid.org/0009-0008-3024-5806)
Institutions
- Shanghai University (CN)
- Shanghai University of Engineering Science (CN)
- Chinese Academy of Sciences (CN)
- Shanghai Institute of Microsystem and Information Technology (CN)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00079c
- Citations
- 3
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 1.55
Funders
- National Natural Science Foundation of China