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• W2342238862 endingPage "12248" @default.
• W2342238862 startingPage "12238" @default.
• W2342238862 abstract "We used NMR imaging (MRI) combined with data analysis based on inverse modeling of the mass transport problem to determine ionic diffusion coefficients and transference numbers in electrolyte solutions of interest for Li-ion batteries. Sensitivity analyses have shown that accurate estimates of these parameters (as a function of concentration) are critical to the reliability of the predictions provided by models of porous electrodes. The inverse modeling (IM) solution was generated with an extension of the Planck-Nernst model for the transport of ionic species in electrolyte solutions. Concentration-dependent diffusion coefficients and transference numbers were derived using concentration profiles obtained from in situ (19)F MRI measurements. Material properties were reconstructed under minimal assumptions using methods of variational optimization to minimize the least-squares deviation between experimental and simulated concentration values with uncertainty of the reconstructions quantified using a Monte Carlo analysis. The diffusion coefficients obtained by pulsed field gradient NMR (PFG-NMR) fall within the 95% confidence bounds for the diffusion coefficient values obtained by the MRI+IM method. The MRI+IM method also yields the concentration dependence of the Li(+) transference number in agreement with trends obtained by electrochemical methods for similar systems and with predictions of theoretical models for concentrated electrolyte solutions, in marked contrast to the salt concentration dependence of transport numbers determined from PFG-NMR data." @default.
• W2342238862 created "2016-06-24" @default.
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• W2342238862 date "2015-09-03" @default.
• W2342238862 modified "2023-10-16" @default.
• W2342238862 title "Accurate Characterization of Ion Transport Properties in Binary Symmetric Electrolytes Using In Situ NMR Imaging and Inverse Modeling" @default.
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• W2342238862 doi "https://doi.org/10.1021/acs.jpcb.5b04300" @default.
• W2342238862 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26247105" @default.
• W2342238862 hasPublicationYear "2015" @default.
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