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Bridging Multiscale Characterization Technologies and Digital Modeling to Evaluate Lithium Battery Full Lifecycle (Adv. Energy Mater. 33/2022).
- Source :
-
Advanced Energy Materials . Sep2022, Vol. 12 Issue 33, p1-1. 1p. - Publication Year :
- 2022
-
Abstract
- Characterization, digital twins, machine learning, simulation Bridging Multiscale Characterization Technologies and Digital Modeling to Evaluate Lithium Battery Full Lifecycle (Adv. Keywords: characterization; digital twins; machine learning; simulation EN characterization digital twins machine learning simulation 1 1 1 09/05/22 20220901 NES 220901 B Lithium Batteries b In article number 2200889, Kai Yang, Shichun Yang and co-workers demonstrate the potential of cyber hierarchy and interactional network framework (CHAIN) to bridge multi-scale characterization and modeling technologies to evaluate lithium battery overall lifecycle. [Extracted from the article]
Details
- Language :
- English
- ISSN :
- 16146832
- Volume :
- 12
- Issue :
- 33
- Database :
- Academic Search Index
- Journal :
- Advanced Energy Materials
- Publication Type :
- Academic Journal
- Accession number :
- 158867972
- Full Text :
- https://doi.org/10.1002/aenm.202270144