galpynostatic 0.4.0

A Python package with physics-based models to predict optimal conditions for fast-charging lithium-ion batteries.

galpynostatic

galpynostatic is a Python package with physics-based models to predict optimal conditions for fast-charging lithium-ion batteries.

Requirements

You need Python 3.9+ 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 latest stable release of galpynostatic with pip

python -m pip install --upgrade pip
python -m pip install --upgrade galpynostatic

Usage

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

License

galpynostatic is licensed under the MIT License.

Citations

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 and E. P. M. Leiva. "Towards a fast-charging of LIBs electrode materials: a heuristic model based on galvanostatic simulations." Electrochimica Acta 464 (2023): 142951.

For the theoretical framework and the universal map datasets (galpynostatic.datasets submodule) refer to:

E. M. Gavilán‐Arriazu, D. E. Barraco, Y. Ein‐Eli and E. P. M. Leiva. "Galvanostatic Fast Charging of Alkali‐Ion Battery Materials at the Single‐Particle Level: A Map‐Driven Diagnosis". ChemPhysChem, 24.6 (2023): e202200665.

BibTeX entries can be found in the CITATIONS.bib file.

Contact

If you have any questions, you can contact me at [e-mail]