Impedance Spectroscopy for Electroceramics and Electrochemical System

Authors: Subrata Karmakar

arXiv: 2406.15467v2 - DOI (physics.app-ph)

Abstract: This tutorial review focuses on the basic theoretical backgrounds, their working principles, and implementation of impedance spectroscopy in both electroceramics and electrochemical research and technological applications. Various contributions to the impedance, admittance, dielectric, and conductivity characteristics of electroceramic materials can be disentangled and independently characterized with the help of impedance spectroscopy as a function of frequency and temperature. In polycrystalline materials, the impedance, charge transport/ conduction mechanism, and the macroscopic dielectric properties i.e., dielectric constant and loss are typically composed of many contributions, including the bulk or grain resistance/capacitance, grain boundary, and sample-electrode interface effect. Similarly, electrochemical impedance spectroscopy (EIS) endeavors to the charging kinetics, diffusion, and mechanical impact of various electrochemical systems widely used in energy storage (i.e., supercapacitor, battery), corrosion resistance, chemical and bio-sensing, diagnostics, etc. in electrolytes as a function of frequency. The understanding of various contributions in the EIS spectra i.e., kinetic control, mass control, and diffusion control is essential for their practical implications. It is demonstrated that electrochemical and electroceramics impedance spectroscopy is an effective method to explain and simulate such behavior. Deconvolute these contributions to obtain a detailed understanding of the functionality of polycrystalline electroceramic materials. This short review aims to endow the expertise of senior researchers in many fields where both EIS (electrochemical and ceramics) are involved, as well as to provide the necessary background information for junior researchers working in these fields.

Submitted to arXiv on 15 Jun. 2024

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.