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| Home > Publications database > Data‐Driven Analysis of High‐Throughput Experiments on Liquid Battery Electrolyte Formulations: Unraveling the Impact of Composition on Conductivity** |
| Home > Publications database > Data‐Driven Analysis of High‐Throughput Experiments on Liquid Battery Electrolyte Formulations: Unraveling the Impact of Composition on Conductivity** |
| Journal Article | FZJ-2023-05463 |
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2022
Wiley-VCH
Weinheim (Germany)
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Please use a persistent id in citations: doi:10.1002/cmtd.202200008 doi:10.34734/FZJ-2023-05463
Abstract: A specially designed high-throughput experimentation facility,used for the highly effective exploration of electrolyte formulationsin composition space for diverse battery chemistries andtargeted applications, is presented. It follows a high-throughputformulation-characterization-optimization chain based on a setof previously established electrolyte-related requirements. Here,the facility is used to acquire large dataset of ionic conductivitiesof non-aqueous battery electrolytes in the conducting saltsolvent/co-solvent-additive composition space. The measuredtemperature dependence is mapped on three generalizedArrhenius parameters, including deviations from simple activateddynamics. This reduced dataset is thereafter analyzed bya scalable data-driven workflow, based on linear and Gaussianprocess regression, providing detailed information about thecompositional dependence of the conductivity. Completeinsensitivity to the addition of electrolyte additives for otherwiseconstant molar composition is observed. Quantitativedependencies, for example, on the temperature-dependentconducting salt content for optimum conductivity are providedand discussed in light of physical properties such as viscosityand ion association effects.
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