A review on the distribution of relaxation times analysis: A powerful tool for process identification of electrochemical systems

The Distribution of Relaxation Times (DRT) analysis gained considerable attention for its ability to reveal detailed information about complex electrochemical processes without requiring a priori knowledge. This review provides a comprehensive insight into different methods of the DRT analysis, their mathematical bases, and the latest approaches to acquiring and analyzing frequency and time domain data. The analysis is based on the deconvolution of frequency domain data into a distribution function of gains at (pre-specified) relaxation times in the time domain, which improves the spectral resolution and separability of electrochemical processes. It provides valuable information about different electrochemical processes on different time scales, making it particularly useful for the characterization of both materials and electrochemical systems. The DRT analysis can be applied to arbitrary spectra containing electromagnetic effects, resistive–capacitive processes, and solid-state diffusion. To enhance process identification, a post-processing step involving peak analysis with Gaussian or RQ-distribution peaks is presented and the assignment of peak patterns induced by distributed processes like solid-state diffusion is discussed. In addition, a step-by-step workflow for the DRT analysis is provided to guide researchers from data acquisition and validation techniques to calculation and interpretation of the distribution function.