Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy
Abstract Electrochemical Impedance Spectroscopy (EIS) is a crucial technique for assessing corrosion of metallic materials. The analysis of EIS hinges on the selection of an appropriate equivalent circuit model (ECM) that accurately characterizes the system under study. In this work, we systematical...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | npj Materials Degradation |
| Online Access: | https://doi.org/10.1038/s41529-024-00537-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850064599574904832 |
|---|---|
| author | Runze Zhang Debashish Sur Kangming Li Julia Witt Robert Black Alexander Whittingham John R. Scully Jason Hattrick-Simpers |
| author_facet | Runze Zhang Debashish Sur Kangming Li Julia Witt Robert Black Alexander Whittingham John R. Scully Jason Hattrick-Simpers |
| author_sort | Runze Zhang |
| collection | DOAJ |
| description | Abstract Electrochemical Impedance Spectroscopy (EIS) is a crucial technique for assessing corrosion of metallic materials. The analysis of EIS hinges on the selection of an appropriate equivalent circuit model (ECM) that accurately characterizes the system under study. In this work, we systematically examined the applicability of three commonly used ECMs across several typical material degradation scenarios. By applying Bayesian Inference to simulated corrosion EIS data, we assessed the suitability of these ECMs under different corrosion conditions and identified regions where the EIS data lacks sufficient information to statistically substantiate the ECM structure. Additionally, we posit that the traditional approach to EIS analysis, which often requires measurements to very low frequencies, might not be always necessary to correctly model the appropriate ECM. Our study assesses the impact of omitting data from low to medium-frequency ranges on inference results and reveals that a significant portion of low-frequency measurements can be excluded without substantially compromising the accuracy of extracting system parameters. Further, we propose simple checks to the posterior distributions of the ECM components and posterior predictions, which can be used to quantitatively evaluate the suitability of a particular ECM and the minimum frequency required to be measured. This framework points to a pathway for expediting EIS acquisition by intelligently reducing low-frequency data collection and permitting on-the-fly EIS measurements. |
| format | Article |
| id | doaj-art-7664c7498ea949ee99eba800956e87f9 |
| institution | DOAJ |
| issn | 2397-2106 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Materials Degradation |
| spelling | doaj-art-7664c7498ea949ee99eba800956e87f92025-08-20T02:49:16ZengNature Portfolionpj Materials Degradation2397-21062024-11-01811710.1038/s41529-024-00537-8Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopyRunze Zhang0Debashish Sur1Kangming Li2Julia Witt3Robert Black4Alexander Whittingham5John R. Scully6Jason Hattrick-Simpers7Department of Material Science and Engineering, University of TorontoCenter for Electrochemical Science and Engineering, University of VirginiaDepartment of Material Science and Engineering, University of TorontoDivision of Material and Surface Technologies, Federal Institute of Materials Research and Testing (BAM)Clean Energy Innovation Research Centre (CEI), National Research Council CanadaClean Energy Innovation Research Centre (CEI), National Research Council CanadaCenter for Electrochemical Science and Engineering, University of VirginiaDepartment of Material Science and Engineering, University of TorontoAbstract Electrochemical Impedance Spectroscopy (EIS) is a crucial technique for assessing corrosion of metallic materials. The analysis of EIS hinges on the selection of an appropriate equivalent circuit model (ECM) that accurately characterizes the system under study. In this work, we systematically examined the applicability of three commonly used ECMs across several typical material degradation scenarios. By applying Bayesian Inference to simulated corrosion EIS data, we assessed the suitability of these ECMs under different corrosion conditions and identified regions where the EIS data lacks sufficient information to statistically substantiate the ECM structure. Additionally, we posit that the traditional approach to EIS analysis, which often requires measurements to very low frequencies, might not be always necessary to correctly model the appropriate ECM. Our study assesses the impact of omitting data from low to medium-frequency ranges on inference results and reveals that a significant portion of low-frequency measurements can be excluded without substantially compromising the accuracy of extracting system parameters. Further, we propose simple checks to the posterior distributions of the ECM components and posterior predictions, which can be used to quantitatively evaluate the suitability of a particular ECM and the minimum frequency required to be measured. This framework points to a pathway for expediting EIS acquisition by intelligently reducing low-frequency data collection and permitting on-the-fly EIS measurements.https://doi.org/10.1038/s41529-024-00537-8 |
| spellingShingle | Runze Zhang Debashish Sur Kangming Li Julia Witt Robert Black Alexander Whittingham John R. Scully Jason Hattrick-Simpers Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy npj Materials Degradation |
| title | Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy |
| title_full | Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy |
| title_fullStr | Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy |
| title_full_unstemmed | Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy |
| title_short | Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy |
| title_sort | bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy |
| url | https://doi.org/10.1038/s41529-024-00537-8 |
| work_keys_str_mv | AT runzezhang bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT debashishsur bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT kangmingli bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT juliawitt bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT robertblack bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT alexanderwhittingham bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT johnrscully bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy AT jasonhattricksimpers bayesianassessmentofcommonlyusedequivalentcircuitmodelsforcorrosionanalysisinelectrochemicalimpedancespectroscopy |