Pushing the boundaries of lithium battery research with atomistic modelling on different scales

Lucy M. Morgan, Michael P. Mercer, Arihant Bhandari, Chao Peng, Mazharul M. Islam, Hui Yang, Julian Holland, Samuel W. Coles, Ryan Sharpe, Aron Walsh, Benjamin J. Morgan, Denis Kramer, M. Saiful Islam, Harry E. Hoster, Jacqueline Sophie Edge, Chris Kriton Skylaris

Research output: Contribution to journalReview articlepeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Article number012002
JournalProgress in Energy
Volume4
Issue number1
DOIs
Publication statusPublished - 2022 Jan

Bibliographical note

Publisher Copyright:
© 2021 The Author(s). Published by IOP Publishing Ltd

All Science Journal Classification (ASJC) codes

  • Energy(all)

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