Machine-learning assisted screening of MXene-supported single-atom catalysts for oxygen reduction
SACs supported on Ti 2 NO 2 MXene and its derivatives with defective surfaces (O or Ti vacancies) are screened for excellent ORR electrocatalytic activity using first-principles calculations and key descriptors are identified by machine learning.
Authors
- Zhishan Su (ORCID: https://orcid.org/0000-0001-5168-3823)
- Dianyong Tang (ORCID: https://orcid.org/0000-0001-9389-870X)
- Changwei Hu (ORCID: https://orcid.org/0000-0002-4094-6605)
- Yan Zhang (ORCID: https://orcid.org/0000-0002-0839-2331)
Institutions
- Sichuan University (CN)
- Chongqing University of Arts and Sciences (CN)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ta04542h
- Citations
- 4
- Primary Topic
- MXene and MAX Phase Materials
- Type
- article
- Field-Weighted Citation Impact
- 2.07