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Experimental Exploration, RSM Modeling, and DFT/MD Simulations of the Anticorrosion Performance of Naturally Occurring Amygdalin and Raffinose for Aluminum in NaOH Solution

Research Authors
Arafat Toghan, Ahmed Fawzy, Abbas I. Alakhras, Nada Alqarni, Magdi E. A. Zaki, Moustafa M. S. Sanad, Ahmed A. Farag
Research Abstract

This paper underlined how the naturally occurring amygdalin (Amy) and raffinose (Raf) can inhibit the corrosion of aluminum in 0.1 M sodium hydroxide utilizing various tools at fixed temperatures. The obtained outcomes designated that the rate of corrosion of Al was set to rise with the rising alkali. The evaluated greater values of inhibition efficiencies (%IEs) of Amy and Raf (reaching 89% and 92%, respectively, at doses of 500 ppm) indicated that such compounds were efficient inhibitors against aluminum corrosion. Such %IE values depended on the concentrations and the structures of the inhibitors. The examined compounds played as mixed-kind inhibitors with a trivial cathodic priority. At similar concentrations, the average %IE values of raffinose were discovered to be faintly greater than those of amygdalin. The %IE values were reduced with the rising temperature. The acquired high values of %IEs were understood to be a result of the effective adsorption of the molecules of the examined compounds on the aluminum surface and the construction of a defensive film, and this adsorption was in agreement with the Langmuir adsorption isotherm. The thermodynamic and kinetic parameters were evaluated and debated. The kinetics of inhibition by the tested compounds were also investigated. The mechanisms of Al corrosion and its inhibition were discussed. The results acquired from the three utilized tools with respect to the values of %IEs were set to be in a good agreement with each other, confirming the validity of the obtained results of the existing study. Computational studies for the interactions between Amy and Raf molecules at the Al (1 1 1) surface were found to be consistent with the experimental results. The quadratic model of response surface methodology (RSM) modeling was used to expertly evaluate the relationships between the input parameters and the expected response (output)

Research Date
Research Journal
Coatings
Research Member
Research Publisher
MDPI
Research Rank
2
Research Vol
13
Research Year
2023
Research Pages
1-24