This talk will discuss electrochemical impedance spectroscopy (EIS) tracking of aqueous alkaline Zn-MnO2 cells cycled at 20% depth of discharge (DOD) based on cathode capacity. Shallow cycled alkaline batteries have previously been reported as cost effective and safe options for large-scale electrical storage. Periodically collected EIS data was used to fit a full battery model based on Voigt elements, and fitted parameters were tracked over time. These were used as a real-time diagnostic to assess performance and predict future performance in advance of any degradation of the cell voltage.The cell model was based on individual electrode models developed previously by Donne and co-workers for γ-MnO2 and Hampson and McNeil for Zn. Two prismatic cell builds were compared using electrodes fabricated by two different commercial sources with identical compositions. Both cell performance and EIS response were distinctly different between the electrode sources. The model provided an acceptable fit of the experimental data in both cases, as shown in Figure 1. The parameters of the model corresponded to physical phenomena, allowing an analysis of the performance difference despite the fact that all electrode fabrication variables could not be known unless provided by the commercial sources.The combined anode and cathode interfacial models were incorporated into a transmission line porous electrode, shown in Figure 2. Each anode + cathode fit involved a combined 15 parameters, which was the minimum number of parameters that would fit data for all cells in all states of charge. Performance analysis was accomplished by comparing a) the individual parameters, b) lumped parameters such as the RC time constants and RLC Q factors, and c) features of the cycling potential such as the discharge end voltage (DEV). Use of a reference electrode with EIS has been shown to be highly dependent on electrode placement. Battery EIS also faces a challenge in that electrodes may have similar capacity, while ideally the counter electrode should be non-limiting. We will address these factors and discuss steps taken to obtain repeatable data free of inductive loops caused by capacitive coupling with current collectors and electrode tabs.
Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds
