Pushing the boundaries of lithium battery research with atomistic modelling on different scales
Publication date
2021-12-07
Document type
Research article
Author
Morgan, Lucy
Mercer, Michael
Bhandari, Arihant
Peng, Chao
Islam, Mazharul M.
Yang, Hui
Holland, Julian Oliver
Coles, Samuel William
Sharpe, Ryan
Walsh, Aron
Morgan, Benjamin J.
Islam, Saiful M.
Hoster, Harry
Edge, Jacqueline Sophie
Skylaris, Chris-Kriton
Organisational unit
Publisher
Institute of Physics Publishing (IOP)
Series or journal
Progress in Energy
ISSN
Periodical volume
4
Periodical issue
1
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Abstract
Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.
Version
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