Computational Screening of Aromatic and Heterocyclic Compounds as Corrosion Inhibitor Candidates: A DFT and Monte Carlo Simulation Study

In this study, the corrosion inhibition potential of a series of aromatic and heterocyclic organic compounds was systematically investigated using Density Functional Theory (DFT) and Monte Carlo (MC) simulations. The electronic structures of carbazole, thiophene, azobenzene, coumarin, quinoline, pyridine, resorcinol, benzaldehyde, 4‐nitroaniline, anthracene, Phenothiazine, aniline, hydroquinone, and fluorene were optimized, and their quantum chemical parameters were evaluated. The calculated HOMO and LUMO energies, energy gap (ΔE), dipole moment, electronegativity, global hardness, softness, and electrophilicity index were employed to assess the reactivity and corrosion inhibition capability of the investigated molecules. The results indicate that compounds possessing higher HOMO energies and lower energy gaps exhibit enhanced electron‐donating ability and stronger interaction with the metal surface, favoring effective corrosion protection. Among the studied compounds, quinoline, anthracene, and fluorene demonstrated particularly favorable electronic characteristics for corrosion inhibition. Furthermore, Monte Carlo simulations on the Fe(110) surface revealed strong and stable adsorption behavior for Phenothiazine, azobenzene, and coumarin, as evidenced by their highly negative adsorption energies. The enhanced adsorption performance is attributed to the presence of heteroatoms and extended π‐conjugated systems, which facilitate strong interactions with the metal surface. The combined DFT and MC results provide valuable insight into the structure–activity relationship governing corrosion inhibition and demonstrate the effectiveness of computational approaches for the screening and design of organic corrosion inhibitors.