TY  - JOUR
AU  - Narayanan Krishnamoorthy, Anand
AU  - Wölke, Christian
AU  - Diddens, Diddo
AU  - Maiti, Moumita
AU  - Mabrouk, Youssef
AU  - Yan, Peng
AU  - Grünebaum, Mariano
AU  - Winter, Martin
AU  - Heuer, Andreas
AU  - Cekic-Laskovic, Isidora
TI  - Data‐Driven Analysis of High‐Throughput Experiments on Liquid Battery Electrolyte Formulations: Unraveling the Impact of Composition on Conductivity**
JO  - Chemistry methods
VL  - 2
IS  - 9
SN  - 2628-9725
CY  - Weinheim (Germany)
PB  - Wiley-VCH
M1  - FZJ-2023-05463
SP  - e202200008
PY  - 2022
AB  - 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.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:001054525700004
DO  - DOI:10.1002/cmtd.202200008
UR  - https://juser.fz-juelich.de/record/1019516
ER  -