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


An illustration of anistropic harmonic lithium vibration in LiFePO4

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.  An example is that 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, Professor Saiful Islam and collaborators 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.  

In this paper, published in Progress in Energy, atomistic modelling is linked to experimental data and higher scale models such as continuum and control models.  The paper also includes a critical discussion on the outlook of these materials and the main challenges for future battery research.