PolCurveFit 1.2.0

library for the analysis of polarization curves

PolCurveFit

A python library to analyse polarization curves, by fitting theoretical curves to input data. Parameters such as the corrosion potential, corrosion rate, Tafel slopes and exchange current densities can be obtained, with three included techniques: Tafel extrapolation: a linear fit to a defined Tafel region Activation control fit: fitting of a theoretical curve describing the anodic and cathodeic activation controlled currents around OCP. Mixed activation-diffusion control fit: fitting of a theoretical curve describing an anodic domain with solely activation controlled currents and a cathodic domain with (mixed) activation and diffusion controlled currents

Installation

pip install PolCurveFit

Documentation

Find the documentation on: https://polcurvefit.readthedocs.io/

Example

Example of how to apply the code

import numpy as np

# An artificial polarization curve
E = np.arange(-1.0, 0.1, 0.01)
I = 0.002 * np.exp(2.3*(E+0.2)/0.08) - 0.002*np.exp(2.3*(-0.2-E)/0.18)/(1+((0.002*np.exp(2.3*(-0.2-E)/0.18))/0.3))

# Instantiate a polarization curve object
from polcurvefit import polcurvefit
Polcurve = polcurvefit(E,I, R= 0, sample_surface=1E-3)

# Apply a fitting technique: 'the activation control fit':
results = Polcurve.active_pol_fit(window=[-0.3,0.1])

# Save the results and visualise the obtained fit
Polcurve.save_to_txt(filename = './output_act')
Polcurve.plotting(output_folder='figures/output_act')

# Apply a fitting technique: 'the mixed activation-diffusion control fit' with a specific weight distribution:
results = Polcurve.mixed_pol_fit(window=[-0.7,0.1], apply_weight_distribution = True, w_ac = 0.07, W = 80)

# Save the results and visualise the obtained fit
Polcurve.save_to_txt(filename = './output_mixed')
Polcurve.plotting(output_folder='figures/output_mixed')