In this work we uncover a novel effect between concentration dependent ion pair formation and anion stability at reducing potentials, e.g., at the metal anode. Through comprehensive calculations using both first-principles as well as well-benchmarked classical molecular dynamics over a matrix of electrolytes, covering solvents and salt anions with a broad range in chemistry, we elucidate systematic correlations between molecular level interactions and composite electrolyte properties, such as electrochemical stability, solvation structure, and dynamics. We find that Mg electrolytes are highly prone to ion pair formation, even at modest concentrations, for a wide range of solvents with different dielectric constants, which have implications for dynamics as well as charge transfer. Specifically, we observe that, at Mg metal potentials, the ion pair undergoes partial reduction at the Mg cation center (Mg(2+) → Mg(+)), which competes with the charge transfer mechanism and can activate the anion to render it susceptible to decomposition. Specifically, TFSI(-) exhibits a significant bond weakening while paired with the transient, partially reduced Mg(+). In contrast, BH4(-) and BF4(-) are shown to be chemically stable in a reduced ion pair configuration. Furthermore, we observe that higher order glymes as well as DMSO improve the solubility of Mg salts, but only the longer glyme chains reduce the dynamics of the ions in solution. This information provides critical design metrics for future electrolytes as it elucidates a close connection between bulk solvation and cathodic stability as well as the dynamics of the salt.
Computational screening techniques have been found to be an effective alternative to the trial and error of experimentation for discovery of new materials. With increased interest in development of advanced electrical energy storage systems, it is essential to find new electrolytes that function effectively. This Perspective reviews various methods for screening electrolytes and then describes a hierarchical computational scheme to screen multiple properties of advanced electrical energy storage electrolytes using high-throughput quantum chemical calculations. The approach effectively down-selects a large pool of candidates based on successive property evaluation. As an example, results of screening are presented for redox potentials, solvation energies, and structural changes of ∼1400 organic molecules for nonaqueous redox flow batteries. Importantly, on the basis of high-throughput screening, in silico design of suitable candidate molecules for synthesis and electrochemical testing can be achieved. We anticipate that the computational approach described in this Perspective coupled with experimentation will have a significant role to play in the discovery of materials for future energy needs.
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