Microstructure-informed performance boost in solid oxide fuel cells through multiphysical modeling and machine learning

作者：Li Duan, Zilin Yan, Zehua Pan, Zheng Zhong · 发表于：Journal of Materials Chemistry A · 年份：2025 · DOI：10.1039/d5ta03421c · 被引用次数：7 · 研究领域：Advancements in Solid Oxide Fuel Cells、Machine Learning in Materials Science

Machine learning co-optimizes SOFC macro-microstructures, boosting power density by 29% while controlling failure risk.