galpynostatic 0.0.1

A physics-based heuristic model to predict the optimal electrode particle size for a fast-charging of lithium-ion batteries.

galpynostatic

galpynostatic is a Python package with a physics-based heuristic model to predict the optimal electrode particle size for a fast-charging of lithium-ion batteries.

Requirements

You need Python 3.8+ to run galpynostatic. All other dependencies, which are the usual ones of the scientific computing stack (matplotlib, NumPy, pandas, scikit-learn and SciPy), are installed automatically.

Installation

You can install the most recent stable release of galpynostatic with pip

python -m pip install -U pip
python -m pip install -U galpynostatic

Usage

To learn how to use galpynostatic you can start by following the tutorials and then read the API.

Also, you can read the Jupyter Notebook pipeline in the paper folder to reproduce the results of the published article.

License

galpynostatic is under MIT License.

Citation

If you use galpynostatic in a scientific publication, we would appreciate it if you could cite the following article:

F. Fernandez, E. M. Gavilán-Arriazu, D. E. Barraco, A. Visintin, Y. Ein-Eli, E. P. M. Leiva. "Towards a fast-charging of LIBs electrode materials: a heuristic model based on galvanostatic simulations" (2023). TODO

BibTeX entry:

@article{fernandez2023towards,
  title={Towards a fast-charging of LIBs electrode materials: a heuristic model based on galvanostatic simulations},
  author={Fernandez, Francisco and Gavilán, Maximiliano and Barraco, Daniel and Visintín, Aldo and Ein-Eli, Yair and Leiva, Ezequiel},
  year={2023}
}

Contact

You can contact me if you have any questions at [e-mail]