Abstract: Lithium–sulfur (Li–S) batteries are considered as promising candidates for next-generation energy storage devices due to their ultrahigh theoretical gravimetric energy density, cost-effectiveness, and environmental friendliness. However, the application of Li–S batteries remains challenging, mainly due to a lack of understanding of the complex chemical reactions and associated equilibria occurring in a working Li–S system. In this review, the typical applications of computational chemistry in Li–S battery studies, correlating to characterization techniques, such as X-ray diffraction, infra-red & Raman spectra, X-ray absorption spectroscopy, binding energy, and nuclear magnetic resonance, are reviewed. In particular, high-accuracy calculations and large-scale models, materials genome, and machine-learning approaches are expected to further advance computational design for the development of Li–S batteries and related fields.

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DOI: 10.1016/j.mattod.2018.04.007