1st Edition

An Introduction to Electrochemical Impedance Spectroscopy

    262 Pages 126 B/W Illustrations
    by CRC Press

    262 Pages 126 B/W Illustrations
    by CRC Press

    This book covers the fundamental aspects and the application of electrochemical impedance spectroscopy (EIS), with emphasis on a step-by-step procedure for mechanistic analysis of data. It enables the reader to learn the EIS technique, correctly acquire data from a system of interest, and effectively interpret the same. Detailed illustrations of how to validate the impedance spectra, use equivalent circuit analysis, and identify the reaction mechanism from the impedance spectra are given, supported by derivations and examples. MATLAB® programs for generating EIS data under various conditions are provided along with free online video lectures to enable easier learning.


    • Covers experimental details and nuances, data validation method, and two types of analysis – using circuit analogy and mechanistic analysis
    • Details observations such as inductive loops and negative resistances
    • Includes a dedicated chapter on an emerging technique (Nonlinear EIS), including code in the supplementary material illustrating simulations
    • Discusses diffusion, constant phase element, porous electrodes, and films
    • Contains exercise problems, MATLAB codes, PPT slide, and illustrative examples


    This book is aimed at senior undergraduates and advanced graduates in chemical engineering, analytical chemistry, electrochemistry, and spectroscopy.

    Chapter 1 Introduction

    Chapter 2 Experimental Aspects

    Chapter 3 Data Validation

    Chapter 4 Data Analysis ・ Equivalent Electrical Circuits

    Chapter 5 Mechanistic Analysis

    Chapter 6 EIS ・ Other Physical Phenomena

    Chapter 7 Applications ・ A Few Examples

    Chapter 8 Nonlinear EIS


    Dr. Ramanathan Srinivasan obtained his B.Tech. in Chemical Engineering from A.C. Tech, Anna University in 1993. He completed his Masters. (Chem. Engg.) in 1996 and Ph.D (Chem. Engg.) in 2000 from Clarkson University, and joined PDF Solutions, USA as Senior Consulting Engineer. He joined IIT Madras as faculty in 2003 and is currently working as Professor in the Department of Chemical Engineering, IIT Madras. His main field of specialization is in the application of electrochemical impedance spectroscopy to obtain mechanistic information of electrochemical reactions. His research group has extended the traditional analysis of metal dissolution from Tafel extrapolation to a more realistic, multi-step reaction mechanistic analysis and has developed a framework to analyze EIS data to unravel the detailed mechanism. One of the unique advantages of this method is that it enables one to estimate the surface coverage of oxidized species at various conditions using in situ measurements in challenging environments, such as acidic fluoride media. He has developed a few freely downloadable software tools to simulate electrochemical responses of reacting systems. He has delivered several invited talks on corrosion and electrochemical techniques, in various national symposiums and conferences and in workshops organized by NACE, India. He was awarded Shri. S. K. Seshadri Memorial Mascot Award 2019, by the Electrochemical Society of India in recognition of his contributions in the area of corrosion and electrochemistry. He has created a freely available 30 h video lectures on electrochemical impedance spectroscopy under the auspices of NPTEL. Dr. Fathima Fasmin obtained her Bachelors of Technology degree in Chemical Engineering from Thangal Kunju Musaliar College of Engineering, Kerala in 2005. She completed her Ph.D (Chemical Engineering) in 2016 from Indian Institute of Technology Madras, and joined Qatar Environment & Energy Research Institute, Qatar as postdoctoral researcher. Currently, she is Assistant Professor in the Department of Chemical Engineering, National Institute of Technology, Calicut. She pursues research in areas such as corrosion, fuel cells and batteries; particularly in understanding EIS and nonlinear EIS data using physics-based models.