Adiantum Capillus-Veneris Extract as a Sustainable Inhibitor to Mitigate Corrosion in Acid Solutions: Experimental,...

Area of Science:

• Materials Science
• Electrochemistry
• Green Chemistry

Background:

• Synthetic organic corrosion inhibitors pose environmental risks.
• Green corrosion inhibitors offer sustainable alternatives.
• Adiantum capillus-veneris (ACV) extract is explored for mild steel protection.

Purpose of the Study:

• To evaluate the efficacy of ACV extract as a green corrosion inhibitor for mild steel in hydrochloric acid.
• To optimize ACV concentration and exposure time using machine learning.
• To confirm the corrosion inhibition mechanism and performance.

Main Methods:

• Electrochemical impedance spectroscopy (EIS) and polarization techniques.
• Shallow neural network modeling of EIS data.
• Multiobjective genetic algorithm for optimization.
• Surface analytical techniques for surface characterization.

Main Results:

• ACV extract achieved 88% inhibition efficiency at 800 ppm.
• ACV acted as a mixed-type inhibitor, reducing corrosion current density from 105 to 44 μA/cm².
• Machine learning models accurately predicted corrosion resistance.
• Optimal ACV performance was identified via a Pareto front analysis.

Conclusions:

• ACV extract is a viable and effective green corrosion inhibitor for mild steel.
• Machine learning significantly enhances the optimization and prediction of corrosion inhibitor performance.
• This approach improves the generalization capacity for developing sustainable corrosion solutions.