Predictive Modeling and Adsorption Behavior, Kinetics, and Thermodynamic Studies of <i>Anthocleista grandiflora </i>Leaf Extract for Corrosion Inhibition of Carbon Steel in Seawater

Abstract

This study investigates the corrosion inhibition performance of Anthocleista grandiflora leaf (AGL) extract on carbon steel in seawater, considering the effects of temperature, immersion time, and inhibitor concentration. Predictive modeling, adsorption behavior, and the kinetics and thermodynamics of the inhibition process were examined. The weight loss technique,characterization techniques combined with response surface methodology (RSM), revealed that the AGL extract follows the Langmuir adsorption model, exhibiting physical adsorption with ΔG values between −16.24 to −15.49kJ/mol, indicating spontaneous and endothermic inhibition. The thermodynamic parameters entropy (−198.87 to −52.58 J/mol), enthalpy (20.42 to 53.42 kJ/mol), and activation energy (13.68 to 56.32 kJ/mol further support this. The corrosion reaction follows first-order kinetics, with the half-life decreasing as the rate constant and extract concentration increase.The SEM images revealed that the AGL extract formed a protective surface layer on the mild steel, effectively preventing pitting. This protective effect became more pronounced as the concentration of the extract increased. RSM optimization identified optimal conditions for maximum inhibition efficiency (98.70%) and corrosion rate (0.058 mm/y) at 800 ppm, 303 K, and 45 days, with a prediction accuracy of 95%, making it suitable for application in the oil and gas industry.