Towards longevity in solid oxide electrolysis cells: multi-scale modeling and machine learning for degradation diagnosis and mitigation
The degradation of SOECs is influenced by coupling across multiple scales. It is necessary to consider establishing a full-chain research framework that integrates multiscale numerical simulations with artificial intelligence methods.
Authors
- Ganlu Fan
- Tom Wu (ORCID: https://orcid.org/0000-0003-0845-4827)
- Xinhai Xu (ORCID: https://orcid.org/0000-0002-5170-2868)
- Ligang Wang (ORCID: https://orcid.org/0000-0003-4327-1903)
- Hanming Chen (ORCID: https://orcid.org/0000-0001-5707-6928)
Institutions
- North China Electric Power University (CN)
- Harbin Institute of Technology (CN)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ta03711e
- Citations
- 3
- Primary Topic
- Advancements in Solid Oxide Fuel Cells
- Type
- article
- Field-Weighted Citation Impact
- 1.55