AutoEIS: Automated equivalent circuit modeling from electrochemical impedance spectroscopy data using statistical machine learning

Python Submitted 12 December 2023Published 16 May 2025
Review

Editor: @lucydot (all papers)
Reviewers: @dap-biospec (all reviews), @DevT-0 (all reviews), @lucydot (all reviews)

Authors

Mohammad Amin Sadeghi (0000-0002-6756-9117), Runze Zhang (0009-0004-9088-7924), Jason Hattrick-Simpers (0000-0003-2937-3188)

Citation

Sadeghi et al., (2025). AutoEIS: Automated equivalent circuit modeling from electrochemical impedance spectroscopy data using statistical machine learning. Journal of Open Source Software, 10(109), 6256, https://doi.org/10.21105/joss.06256

@article{Sadeghi2025, doi = {10.21105/joss.06256}, url = {https://doi.org/10.21105/joss.06256}, year = {2025}, publisher = {The Open Journal}, volume = {10}, number = {109}, pages = {6256}, author = {Mohammad Amin Sadeghi and Runze Zhang and Jason Hattrick-Simpers}, title = {AutoEIS: Automated equivalent circuit modeling from electrochemical impedance spectroscopy data using statistical machine learning}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  
Tags

python julia electrochemistry materials science electrochemical impedance spectroscopy equivalent circuit model statistical machine learning bayesian inference evolutionary search

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Table of Contents
Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066