Robust interpretation of electrochemical impedance spectra using numerical complex analysis
Authors
Jithin D. George
Willa Brenneis
Vinod K. Sangwan
Dilara Meli
Heather Kurtz
Jeffrey Richards
Lincoln J. Lauhon
Jonathan Rivnay
Mark C. Hersam
Jeffrey Lopez
Maria K. Y. Chan
Valerie Taylor
Abstract
Electrochemical Impedance Spectroscopy (EIS) is a non-invasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition, and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can ascertain the presence of inductors and constant phase elements (non-ideal capacitors) in circuit models and enable us to answer questions about the identifiability and uniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.
