galpynostatic.datasets submodule

The galpynostatic.dataset module loads the data required for the fits.

These datasets have been obtained using a continuum computational physics model for different geometries [5]. They result from a cut-off of multiple galvanostatic profiles at a given cell potential, with respect to equilibrium, with different combinations of the internal unitless parameters \(\Xi\) and \(\ell\) covering a wide range of possible values of the experimental descriptors involved.

References

[5]

E. M. Gavilán-Arriazu, D. E. Barraco, D., 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.i” ChemPhysChem 24, no. 6 (2023): e202200665.

galpynostatic.datasets.load_dataset(geometry='spherical')

Galvanostatic map for a cut-off potential of 150 mV.

Parameters:

geometry (str, default="spherical") – The geometry of the electrode. It can be “spherical”, “cylindrical” or “planar”.

Returns:

The geometry dataset as a pandas.DataFrame.

Return type:

pandas.DataFrame

Raises:

ValueError – If the geometry is not “spherical”, “cylindrical” or “planar”.