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Boosting Rechargeable Batteries R&D by Multiscale Modeling: Myth or Reality?
Alejandro A Franco1,2,3,4, Alexis Rucci1,2, Daniel Brandell3,5
1Laboratoire de Réactivité et Chimie des Solides (LRCS), CNRS UMR 7314 , Université de Picardie Jules Verne , Hub de l'Energie, 15 Rue Baudelocque , 80039 Amiens Cedex 1 , France.
Chemical Reviews
|March 13, 2019
Summary
This review explores multiscale modeling for designing rechargeable battery cells. It covers methods, outcomes, and challenges to advance battery technology.
Area of Science:
- Materials Science
- Chemical Engineering
- Computational Science
Background:
- Rechargeable battery design requires advanced modeling techniques.
- Optimizing battery performance necessitates understanding processes across multiple length and time scales.
Purpose of the Study:
- To review multiscale modeling concepts, approaches, tools, and outcomes for rechargeable battery cells.
- To demystify different multiscale modeling strategies and their methodological aspects.
- To compare modeling outcomes with other strategies and experimental data.
Main Methods:
- Discussion of various multiscale modeling approaches.
- Analysis of methodological aspects of these models.
- Comparative analysis of modeling results against experimental data and alternative methods.
Main Results:
- Overview of current multiscale modeling capabilities in battery design.
- Identification of strengths and limitations of different modeling strategies.
- Validation of modeling approaches through comparison with experimental results.
Conclusions:
- Multiscale modeling is crucial for current and future rechargeable battery development.
- Methodological clarity and validation are key for effective multiscale modeling.
- Future research should focus on addressing remaining challenges and exploring new developments in the field.
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