nleis 0.2

A NLEIS toolbox for impedance.py that provides RC level nonlinear equivalent circuit modeling (nECM) and analysis

nleis.py

Second-harmonic nonlinear electrochemical impedance spectroscopy (2nd-NLEIS), a special form of nonlinear electrochemical impedance spectroscopy (NLEIS), is emerging as a powerful complementary technique to traditional electrochemical impedance spectroscopy (EIS). It retains the experimental simplicity of EIS while providing additional physical insights. However, its adoption and application have been limited by the lack of open-source, user-friendly software.

nleis.py aims to address this gap by providing a Python toolbox that is designed to work with and extend the capabilities of impedance.py. Key features include:

• Nonlinear equivalent circuit modeling (nECM)
• Simultaneous analysis of EIS and 2nd-NLEIS data

This repository contains the most recent version of nleis.py. As of today, nleis.py supports the latest version of impedance.py (v1.7.1).

Installation

The nleis.py is avaliable in a standalone version now. You can install it directly with pip.

pip install nleis

See Getting started with nleis.py for instructions on how to get most of this toolbox.

In the near future, you will be able to access all the funcationality for nleis.py from impedance.py.

Dependencies

nleis.py requires the same dependencies as impedance.py puls the latest version of impedance.py:

• Python (>=3.8)
• SciPy (>=1.0)
• NumPy (>=1.14)
• Matplotlib (>=3.0)
• Altair (>=3.0)
• impedance(>=1.7.1)
• pandas (>= 2.0.2)

Examples and Documentation

The detailed documentation can be found at nleispy.readthedocs.io.

Contributing to nleis.py

The nleis.py project welcomes all kinds of contributions, including bug fixes, feature requests, code reviews, new features, examples, documentation improvements, and community engagement. For any changes involving the repository, please refer to the detailed guidance in the CONTRIBUTING.md. If you encounter any issues or have suggestions, feel free to submit an issue to let us know.

We are also excited to see contributions that expand the capabilities of nleis.py. Potential future features include:

• EIS and 2nd-NLEIS data processing from the time domain
• Data validation for 2nd-NLEIS

Citing nleis.py

If you use nleis.py in your work, please consider citing our JOSS paper as:

@article{Ji2025,
  doi = {10.21105/joss.07424},
  url = {https://doi.org/10.21105/joss.07424},
  year = {2025}, publisher = {The Open Journal},
  volume = {10},
  number = {105},
  pages = {7424},
  author = {Yuefan Ji and Matthew D. Murbach and Daniel T. Schwartz},
  title = {nleis.py: A Nonlinear Electrochemical Impedance Analysis Toolbox},
  journal = {Journal of Open Source Software}
}

Credits

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This work adopted and built the nleis.py based on impedance.py (Murbach, M., Gerwe, B., Dawson-Elli, N., & Tsui, L. (2020). impedance.py: A Python package for electrochemical impedance analysis. Journal of Open Source Software, 5. https://doi.org/10.21105/joss.02349)

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Contributors :battery:

Yuefan Ji 🎨 💻 📖 ⚠️ 👀

Matt Murbach 💻 👀

Dan Schwartz 📖 👀

Jake Anderson 💻 👀