Please use this identifier to cite or link to this item: https://repository.seku.ac.ke/handle/123456789/8296
Title: Synergistic corrosion inhibition of 304 stainless steel in 1 M HCl by methanolic Acacia mearnsii bark extract and KI: Thermodynamic, kinetic, and thermal analysis
Authors: Mungwari, Chakanaka P.
Obadele, Babatunde A.
King'ondu, Cecil K.
Keywords: thermodynamics
kinetics
synergistic
adsorption
methanolic acacia mearnsii bark extract
Issue Date: Oct-2025
Publisher: Elsevier
Citation: Chemical thermodynamics and thermal analysis, volume 20, 100233, 2025
Abstract: This study evaluates the thermodynamic behavior and adsorption mechanism of methanolic Acacia mearnsii bark extract (MAMBE) as a green corrosion inhibitor for stainless steel (SS304) in synergy with KI in 1 M HCl solution. Using weight loss measurements, thermodynamic calculations, and adsorption studies, the study assesses both the individual and combined effectiveness of MAMBE and potassium iodide (KI). MAMBE alone achieved a maximum inhibition efficiency of 62.2 % at 1.2 g/L, which dramatically increased to 98.2% when supplemented with 0.3 g/L KI, indicating a strong synergistic effect (s > 1). Thermodynamic parameters, including activation energy (Ea), enthalpy change (ΔH°), entropy change (ΔS°), and Gibbs free energy change (ΔG°), were analyzed to understand the nature of adsorption and spontaneity. MAMBE and KI alone showed Ea values below 80 kJ/mol with positive ΔH°, indicating endothermic adsorption. The MAMBE and KI combination presented a higher Ea of 105 kJ/mol, suggesting a more robust corrosion barrier. The ΔG° values (-6.653 to −21.765 kJ/mol) confirmed spontaneous, predominantly physical adsorption. Adsorption followed the Langmuir isotherm model, and thermogravimetric analysis revealed MAMBE's thermal stability up to 110°C, highlighting its excellent thermal resistance and potential as an effective eco-friendly corrosion inhibitor.
Description: https://doi.org/10.1016/j.ctta.2025.100233
URI: https://www.sciencedirect.com/science/article/pii/S2667312625000732
https://repository.seku.ac.ke/handle/123456789/8296
Appears in Collections:School of Science and Computing (JA)

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