Abstract
Electrochemical impedance spectroscopy (EIS) is an important electrochemical technique that is used to detect changes and ongoing processes in a given material. The main challenge of EIS is interpreting the collected measurements, which can be performed in several ways. This article focuses on the electrical equivalent circuit (EEC) approach and uses grammatical evolution to automatically construct an EEC that produces an AC response that corresponds to one obtained by the measured electrochemical process(es). For fitting purposes, synthetic measurements and data from measurements in a realistic environment were used. In order to be able to faithfully fit realistic data from measurements, a new circuit element (ZARC) had to be implemented and integrated into the SPICE simulator, which was used for evaluating EECs. Not only is the presented approach able to automatically (i.e., with almost no user input) produce a more than satisfactory EEC for each of the datasets, but it also can also generate completely new EEC configurations. These new configurations may help researchers to find some new, previously overlooked ongoing electrochemical processes.
Highlights
The results of an Electrochemical impedance spectroscopy (EIS) study offer a large amount of additional data such as the distribution of relaxation times (DRT) [3,4,5] and the distribution of diffusion times (DDT) [6,7], which can be used to gain deeper insights into ongoing electrochemical processes
We present the results of running the grammatical evolution algorithm in trying to approximate the data provided in the previous section
Grammatical evolution was used as an automatic method for creating a matching
Summary
Electrochemical impedance spectroscopy (EIS) [1] is an important electrochemical technique that is used to detect changes and ongoing processes in a given material. It can be applied in fields such as solid oxide fuel cell (SOFC) development, monitoring protective coatings properties, measuring the effectiveness of electrodes and more. The results of an EIS study offer a large amount of additional data such as the distribution of relaxation times (DRT) [3,4,5] and the distribution of diffusion times (DDT) [6,7], which can be used to gain deeper insights into ongoing electrochemical processes. The EEC application is custom in EIS study [8,9], and there are modern articles on how to improve and modify EEC analysis [10,11,12,13,14,15] EEC analysis
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