Computational Investigation of Corrosion Inhibition Efficiency of Novel Benzimidazole Derivatives on Mild Steel Surfaces

Abstract

Corrosion of mild steel in aggressive media remains a major industrial challenge, particularly in acid pickling and petrochemical environments. In this work, computational approaches were used to evaluate the inhibition efficiency of newly designed benzimidazole derivatives against iron corrosion. Density functional theory (DFT) calculations were employed to analyze electronic parameters such as HOMO-LUMO energy gap, dipole moment, and Mulliken charges, while Monte Carlo simulations assessed adsorption behavior on Fe (110) surfaces. Results indicated that the designed molecules exhibited strong electron-donating ability through nitrogen and aromatic groups, promoting stable chemisorption on the metal surface. The adsorption energies ranged from −165 to −192 kJ/mol, demonstrating spontaneous and robust interactions. Molecular dynamics simulations confirmed the formation of a compact protective layer, minimizing surface corrosion. Correlation between inhibition efficiencies and quantum chemical descriptors revealed that lower HOMO-LUMO gaps and higher dipole moments corresponded to better inhibition potential. These theoretical insights provide a cost-effective pre-screening method for designing efficient corrosion inhibitors, reducing the reliance on extensive experimental trials. This study contributes to the rational design of green, non-toxic, and high-performance corrosion inhibitors for industrial applications.