Theoritical evaluation of Citrus Aurantium leaf extract as green inhibitor for chemical and biological corrosion of mild steel in acidic solution: Statistical, molecular dynamics, docking, and quantum mechanics study

Citrus Aurantium extract consists of many compounds such as Alpha terpineol (AT), Linalool (LI), Linalyl acetate (LA), and Monoterpene hydrocarbons (MH) that suggested as corrosion inhibitors in the ground and protonated states. The current study included treatment of the corrosion process caused by the aggressive ions and/or Acidithiobacillus ferrooxidans bacteria (A. ferrooxidans) through Density Function Theory (DFT). The autodock process was carried out by the Molecular Graphic Laboratory (MGL) and Discovery Studio Visualizer (DSV) software. The bond length, angles, and dihedral were measured to present the adsorption sites of molecules. Also, the HOMO, LUMO, dipole moment, energy gap, and more parameters were used to compare the efficiency of the inhibitors. Total Electron Density (TED) and Electrostatic Surface Potential (ESP) were used to show the sites of adsorption according to electron density. Fukui function used to present the ability of atoms to donate and receipt electrons. Binding energy (Eb) was used to test the inhibition ability of A. ferrooxidans by docking calculations. DFT showed that the order of corrosion inhibition was MH > LI > LA > AT, while bio-corrosion inhibition of A. ferrooxidans was AT > MH > LA > LI. Statistical analysis was used to correlate quantum chemical parameters with inhibition efficiency. A significant model was obtained with a 0.98 correlation coefficient. The calculated inhibition efficiency was compared with the experimental one. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This study utilized Density Function Theory (DFT) to investigate the corrosion inhibition effect of Citrus Aurantium extract on metal corrosion, and through molecular docking and correlation analysis of quantum chemical parameters, the study identified the order of inhibition effects of different compounds on metal and microbial corrosion and established an effective model with a 0.98 correlation coefficient.