ArticlePatterns (New York, N.Y.)2023
Guiding maps of solvents for lithium-sulfur batteries via a computational data-driven approach.
Article in Patterns (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Practical realization of lithium-sulfur batteries requires designing optimal electrolytes with controlled dissolution of polysulfides, high ionic conductivity, and low viscosity. Computational chemistry techniques enable tuning atomistic interactions to discover electrolytes with targeted properties. Here, we introduce ComBat (Computational Database for Lithium-Sulfur Batteries), a public database of ∼2,000 quantum-chemical and molecular dynamics properties for lithium-sulfur electrolytes composed of solvents spanning 16 chemical classes. We discuss the microscopic origins of polysulfide clustering and the diffusion mechanism of electrolyte components. Our findings reveal that polysulfide solubility cannot be determined by a single solvent property like dielectric constant. Rather, observed trends result from the synergistic effect of multiple factors, including solvent C/O ratio, fluorination degree, and steric hindrance effects. We propose binding energy as a proxy for Li
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