A customized Python module for interactive curve fitting on potentiodynamic scan data

Abstract

A customized Python module for interactive curving fitting in Jupyter Notebook environment right in the browser such as Chrome. It allows users to interactively fit Butler-Volmer equations and its variations to potentiodynamic scan curves. The optimization process is powered by non-linear least squares algorithms from Scipy. It features a user-friendly plotting GUI with Jupyter Notebook widgets. This current release provides options for interactive data range selection, linear/log axis switching, auto-zoomed plotting, and post-IR compensation. The fitted results include corrosion parameters such as corrosion potential, corrosion current, Tafel slopes, polarization resistance, and goodness of fit (R2 score and Chi2 score).

Publication
Zenodo
Gang Li
Gang Li
Sessional Lecturer, R&D

My research focuses on durability of cement-based materials and concrete infrastructures.

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