Computational Evaluation of Ionic Liquids as Sustainable Corrosion Inhibitors for Copper

Corrosion of copper and other metals poses a persistent challenge in industrial and engineering applications, causing significant economic losses and safety risks to workers, equipment, and the immediate environment. Conventional corrosion inhibitors, including organic coatings, often raise environmental and human health concerns, motivating the search for safer and more sustainable alternatives. Ionic liquids (ILs) have emerged as promising candidates owing to their low toxicity, favourable adsorption characteristics, and high thermal stability. This study employs computational methods to evaluate the corrosion inhibition potential of selected ILs on copper surfaces using the PM6 semi-empirical quantum molecular simulation method, chosen for its improved parameterization of d-orbital interactions, making it well-suited for copper–IL systems. Two key quantum chemical descriptors were employed: the energy gap (e-GAP), which assesses chemical stability and resistance to charge transfer, and the interaction energy gap (IEG), which evaluates adsorption tendency and electron-transfer capacity between the inhibitor and the copper surface. These descriptors were computed for each IL and benchmarked against styrene, a representative paint component used as a reference inhibitor. Findings reveal that several investigated ILs exhibit lower IEG values than styrene, indicating stronger adsorption potential. Notably, 1-pentylpyridazinium bromide (PPB) displayed the lowest IEG of 5.59 eV compared to styrene's 6.61 eV, alongside the lowest LUMO energy among all compounds studied, underscoring its superior electron-accepting ability and adsorption affinity for the copper surface. These results demonstrate that the selected ILs, particularly PPB, outperform styrene as corrosion inhibitors under the modelled conditions, making them potentially effective and environmentally friendly alternatives for copper protection in industrial applications. While this study is computational in scope, the findings provide a molecular-level foundation that may guide future experimental validation efforts by other researchers.