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SEI-forming additives play an important role in lithium-ion batteries, and the key to improving battery functionality is to determine if, how, and when these additives are reduced. Here, we tested a number of computational approaches and methods to determine the best way to predict and describe the properties of the additives. A wide selection of factors were evaluated, including the influences of the solvent and lithium cation as well as the DFT functional and basis set used. An optimized computational methodology was employed to assess the usefulness of different descriptors.   Electronic supplementary material  The online version of this article (doi:10.1007/s00894-016-3180-0) contains supplementary material, which is available to authorized users.

SEI-forming electrolyte additives for lithium-ion batteries: development and benchmarking of computational approaches