Machine learning-driven breakthroughs in water electrolysis and supercapacitors
ML has revolutionized the field of materials science by expediting discovery and optimization procedures. ML algorithms monitor enormous datasets, thereby predicting novel nanomaterials with tailored properties for breakthroughs in nanotechnology.
Authors
- Fuming Lai (ORCID: https://orcid.org/0000-0002-8393-9034)
- Qinfang Zhang (ORCID: https://orcid.org/0000-0003-3233-3400)
- Hao Huang (ORCID: https://orcid.org/0000-0002-1824-8835)
- Jue Wang (ORCID: https://orcid.org/0000-0001-8297-8827)
- Xiaoqing Wang (ORCID: https://orcid.org/0000-0001-9317-9983)
- Diab Khalafallah (ORCID: https://orcid.org/0000-0002-9445-581X)
Institutions
- Chuzhou University (CN)
- Jinhua Academy of Agricultural Sciences (CN)
- Yancheng Institute of Technology (CN)
- Aswan University (EG)
Publication Details
- Journal
- Materials Chemistry Frontiers
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5qm00326a
- Citations
- 9
- Primary Topic
- Fuel Cells and Related Materials
- Type
- article
- Field-Weighted Citation Impact
- 6.57