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Published February 26, 2015 | public
Journal Article Open

Ab Initio Characterization of the Electrochemical Stability and Solvation Properties of Condensed-Phase Ethylene Carbonate and Dimethyl Carbonate Mixtures


A central challenge in the refinement of lithium-ion batteries is to control cathode-induced oxidative decomposition of electrolyte solvents, such as ethylene carbonate (EC) and dimethyl carbonate (DMC). We study the oxidation potentials of neat EC, neat DMC, and 1:1 mixtures of EC and DMC using the newly developed projection-based embedding method, which we demonstrate to be capable of correcting qualitative inaccuracies in the electronic densities and ionization energies obtained from conventional Kohn–Sham density functional theory (DFT) methods. Our wave function-in-DFT embedding approach enables accurate calculation of the vertical ionization energy (IE) of individual molecules at the CCSD(T) level of theory while explicitly accounting for the solvent using a combination of DFT and molecular mechanics interactions. We find that the ensemble-averaged distributions of vertical IEs are consistent with a linear response interpretation of the statistics of the solvent configurations, enabling determination of both the intrinsic oxidation potential of the solvents and the corresponding solvent reorganization energies. Interestingly, we reveal that large contributions to the solvation properties of DMC originate from quadrupolar interactions, resulting in a much larger solvent reorganization energy than that predicted using simple dielectric continuum models. Demonstration that the solvation properties of EC and DMC are governed by fundamentally different intermolecular interactions provides insight into key aspects of lithium-ion batteries, with relevance to electrolyte decomposition processes, solid–electrolyte interphase formation, and the local solvation environment of lithium cations.

Additional Information

© 2015 American Chemical Society. Received: October 30, 2014 Revised: January 07, 2015. Publication Date (Web): January 12, 2015. This work is supported by the Office of Naval Research (ONR) under Grant No. N00014-10-1-0884 and by the U.S. Army Research Laboratory and the U.S. Army Research Office (USARO) under Grant No. W911NF-10-1-0202. Computing resources were provided by the National Energy Research Scientific Computing Center (NERSC) (DE-AC02-05CH11231).

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August 20, 2023
August 20, 2023