Machine learning and first-principles calculations for the prediction and analysis of superconductivity in Mg–B–N systems
This article explored potential superconducting materials in the Mg–B–N system using machine learning and first-principles calculations. Four stable layered superconductors were discovered at atmospheric pressure.
Authors
- Peng Lin (ORCID: https://orcid.org/0000-0003-2601-0787)
- Tingting Shi (ORCID: https://orcid.org/0000-0002-5686-6706)
- Wenjing Hu (ORCID: https://orcid.org/0000-0003-4375-1341)
- Jia Lin (ORCID: https://orcid.org/0000-0002-0668-6475)
- Liliang Zha
- Shunwei Yao (ORCID: https://orcid.org/0009-0005-6814-9615)
- B. G. Wang (ORCID: https://orcid.org/0000-0003-0710-151X)
- Jing Chen (ORCID: https://orcid.org/0000-0001-6703-2486)
- Xiaolin Liu (ORCID: https://orcid.org/0000-0002-8875-6886)
- Jiajun Jiang
- Yamin Xue
Institutions
- Sun Yat-sen University (CN)
- Jinan University (CN)
- Shanghai University of Electric Power (CN)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5tc00708a
- Citations
- 4
- Primary Topic
- Superconductivity in MgB2 and Alloys
- Type
- article
- Field-Weighted Citation Impact
- 5.03