Operando Optical Microscopy of Battery Materials for Transport Coefficients

Diffusion coefficients of electrode materials are often determined using galvanostatic (GITT) or potentiostatic intermittent titration technique (PITT), electrochemical impedance spectroscopy (EIS) or cyclic voltammetry (CV). However, these methods require special care, as each of their formal derivations use quite restrictive assumptions. As an alternative, an operando optical microscopy method is proposed for studying lithium transport. Two material systems are presented namely, Li4Ti5O12 (LTO) and LiMn2O4 (LMO). In both cases, a huge concentration-dependent Li kinetics can be observed. Moreover, phase propagation in the initial stages follows a linear growth rather than the conventional assumed parabolic growth. This is characterized by a "barrier coefficient" which restricts the phase transformation behavior. For the case of LTO this barrier coefficient seems to be size dependent. This is due to the fact that the fast kinetics in Li-poor spinel phase hinders the nucleation of the Li-rich rock-salt phase. For the case of LMO, the method had been extended due to the presence of multiple phases in the solubility range of 1≥x≥0 LixMn2O4. Therefore, no monotonic dependence of optical intensity was recorded by the microscope on lithium concentration. For this purpose, a python code is developed that determines concentration profiles from RGB images using support vector regression (SVR), a flexible machine-learning tool. To evaluate the diffusion coefficient, an inverse Boltzmann-Matano concept is applied. Representing the diffusion coefficient with generalized Redlich-Kister polynomials, concentration profiles are predicted and fit to the measured data.