Perspectives on accurately analyzing cyclic voltammograms for surface- and diffusion-controlled contributions

Abstract

As electrochemical energy storage continues to gain importance, researchers have been exploring novel materials and electrode designs to enhance performance. While these innovations have significantly improved the performance of energy storage devices, the specific mechanisms responsible for their success remain unclear. One powerful tool for gaining insights into how modifications to the electrode can enhance cell performance is cyclic voltammetry (CV). However, interpreting CV data can be challenging, and simple analytical relations are often inadequate for accurate assessment. Moreover, different analytical methods can yield conflicting results, leading to confusion within the research community and hindering progress in the field. To address these challenges, our study aims to investigate the contributions of surface and diffusion-controlled processes to charge storage in supercapacitor applications. We will employ conventional methods to examine how these processes can lead to the misinterpretation of CV data and identify the advantages and limitations of different analytical approaches. Our research underscores the importance of developing models that faithfully replicate the system of interest to gain insights into charge storage mechanisms. By identifying these key factors, our findings could pave the way for the development of more efficient and effective energy storage technologies.

Keywords

• Cyclic voltammetry
• Modeling
• Surface-controlled process
• Diffusion-controlled process
• Charge storage mechanisms
• Supercapacitors