Knowledge-driven design of fluorinated ether electrolytes via a multi-model approach

Nav Nidhi Rajput,Rasha Atwi,Daniel Gribble, Dan Thien Nguyen, Minyung Song, Agrim Babbar,Vijayakumar Murugesan,Vilas Pol

crossref(2024)

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摘要
Abstract Fluorinated ether solvents (FLS) can enhance the cycle life of Li-S batteries by mitigating the polysulfide shuttle effect. However, developing fluorinated electrolytes with reduced polysulfide solubility and uncompromised transport properties is underexplored. We integrate high-throughput density functional theory, molecular simulations, machine learning, and experimental analyses to explore ~1,000 FLS to be used as co-solvent with 1,3-dioxolane. Only 14 FLS in our library have been previously reported in Li-S literature. Through a rigorous screening process, we identify and test two new solvents which demonstrate reduced polysulfide solubility. One solvent exhibits electrochemical performance on par with the widely used 1,1,2,2-tetrafluoro-3-(1,1,2,2-tetrafluoroethoxy)propane (TTE) solvent, yet with superior electrolyte viscosity and ionic conductivity. Interpretable machine learning models indicate fluorination degree, steric effects on ether oxygen, and fluorine proximity to ether oxygen are crucial in dictating oxidation reactions and polysulfide solubility. This work not only introduces new promising co-solvents for Li-S batteries but also provides a framework for knowledge-driven electrolyte design.
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