Prediction of inhibition performance of some benzimidazole derivatives against steel corrosion through QSAR and molecular dynamic simulation

The corrosion inhibition performance of benzimidazole derivatives against steel corrosion has been investigated by the quantum chemical calculation, QSAR analysis, and molecular dynamics (MD) simulation methods. Density functional theory (B3LYP/6- 31G*) quantum chemical parameters such as energy of the highest occupied molecular orbital (E-HOMO), the energy of the lowest unoccupied molecular orbital (E-LUMO), energy band gap ΔE, Dipole Moment, electrophilicity index (ω), chemical softness (σ), chemical hardness (η) and fraction of electron transfer from the inhibitors molecule to the metallic surface (ΔN) have been calculated and well discussed. A linear quantitative structure-activity relationship (QSAR) model was built by multiple linear regression (MLR) method between the computed descriptors and the experimental corrosion inhibition efficiencies. The prediction of corrosion efficiencies of these inhibitors nicely matched the experimental measurements. The validation parameters are the squared correlation coefficients (R²) of 0.942, adjusted squared correlation coefficients (R² adj) value of 0.908, cross-validation coefficients (Q² cv) value of 0.795 and the external validations (R² test) of 0.983 respectively. These indicate that the generated models were excellent for verifying with internal and external validation parameters. Molecular dynamics (MD) simulation was also applied to search the best adsorption configuration of inhibitor over Fe (1 1 0) surface. It was found that adsorption of the inhibitor molecules on the steel surface mainly occurred by a chemical adsorption phenomenon. Thus, Quantum chemical studies, QSAR analysis along with MD simulation may be a very powerful tool for the rational designing of several promising corrosion inhibitors.