Sergey A. Krachkovskiy

Visualization of Steady-State Ionic Concentration Profiles Formed in Electrolytes during Li-Ion Battery Operation and Determination of Mass-Transport Properties by in Situ Magnetic Resonance Imaging

Accurate modeling of Li-ion batteries performance, particularly during the transient conditions experienced in automotive applications, requires knowledge of electrolyte transport properties (ionic conductivity κ, salt diffusivity D, and lithium ion transference number t(+)) over a wide range of salt concentrations and temperatures. While specific conductivity data can be easily obtained with modern computerized instrumentation, this is not the case for D and t(+). A combination of NMR and MRI techniques was used to solve the problem. The main advantage of such an approach over classical electrochemical methods is its ability to provide spatially resolved details regarding the chemical and dynamic features of charged species in solution, hence the ability to present a more accurate characterization of processes in an electrolyte under operational conditions. We demonstrate herein data on ion transport properties (D and t(+)) of concentrated LiPF6 solutions in a binary ethylene carbonate (EC)-dimethyl carbonate (DMC) 1:1 v/v solvent mixture, obtained by the proposed technique. The buildup of steady-state (time-invariant) ion concentration profiles during galvanostatic experiments with graphite-lithium metal cells containing the electrolyte was monitored by pure phase-encoding single point imaging MRI. We then derived the salt diffusivity and Li(+) transference number over the salt concentration range 0.78-1.27 M from a pseudo-3D combined PFG-NMR and MRI technique. The results obtained with our novel methodology agree with those obtained by electrochemical methods, but in contrast to them, the concentration dependences of salt diffusivity and Li(+) transference number were obtained simultaneously within the single in situ experiment.

Accurate Characterization of Ion Transport Properties in Binary Symmetric Electrolytes Using In Situ NMR Imaging and Inverse Modeling

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.