Artificial Intelligence Empowers Solid-State Batteries for Material Screening and Performance Evaluation
Highlights The latest advancements in the application of machine learning (ML) for the screening of solid-state battery materials are reviewed. The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. Future challenges and perspec...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-06-01
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| Series: | Nano-Micro Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40820-025-01797-y |
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| Summary: | Highlights The latest advancements in the application of machine learning (ML) for the screening of solid-state battery materials are reviewed. The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. Future challenges and perspectives of artificial intelligence in solid-state battery are discussed. |
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| ISSN: | 2311-6706 2150-5551 |