Researchers used EIS to study the corrosion of copper in a chloride-containing environment, mimicking seawater. By analyzing the Nyquist plots obtained at different immersion times, they identified the formation of a Cu₂O layer and elucidated the dissolution-deposition process involved in the corrosion. Equivalent circuit models were developed to represent the different stages of corrosion, providing insights into the charge transfer processes and the influence of the oxide layer's resistance and capacitance. The study even extended to comparing the anisotropic corrosion behavior of different copper crystal orientations (Cu(100) vs. Cu(111)), revealing how the atomic arrangement on the surface affects the initial adsorption of corrosive ions and subsequent corrosion kinetics.

🧠Example

https://gist.github.com/viadean/afcf85dfbc289bec8c4360481a35e303

Highlights of the Script:

1. Equivalent Circuit Model:
   • The Randles circuit is used as an example, which consists of a resistor ($R_s$) in series with a parallel combination of ($R_{ct}$) and ($C_{dl}$).
2. Curve Fitting:
   • The scipy.optimize.curve_fit function optimizes the model parameters to fit the experimental data.
3. Visualization:
   • Nyquist and Bode plots are generated to compare experimental data with the fitted model.
4. Interpretation:
   • Extracted parameters ($R_{ct}$, $C_{dl}$, $R_s$) provide insights into the corrosion mechanism.

Applications in Copper Corrosion Studies:

• Chloride Effect: Analyze how chloride ions influence charge transfer resistance and double-layer capacitance.
• Inhibitor Efficiency: Evaluate the effectiveness of corrosion inhibitors in chloride environments.
• Mechanistic Insights: Investigate diffusion-controlled processes or adsorption phenomena.