Integrated Density Functional Theory and QSAR Modelling of Selected Imidazole Derivatives for Corrosion Inhibition of Mild Steel in Acidic Medium

Background: Organic nitrogen-containing heterocycles can inhibit corrosion through their interactions with metal surfaces, but computational descriptors alone do not establish the performance of proposed inhibitors. Aim: This study integrated density functional theory (DFT) and quantitative structure–activity relationship (QSAR) modelling to examine the corrosion-inhibition behaviour of selected imidazole derivatives for mild steel in an acidic medium. Methods: A literature-derived dataset of 21 compounds was assembled. Molecular geometries and electronic descriptors were calculated using Spartan at the B3LYP/6-31G** level in an aqueous computational environment. Molecular descriptors generated using PaDEL were screened through a genetic-algorithm procedure, and a three-descriptor multiple linear regression model was developed using AATSC0p, TDB10s and E1m. Seventeen compounds were used for model development and four for external validation. Results: Compound 11 had the highest reported inhibition efficiency (98.5%), a HOMO–LUMO energy gap of 3.70 eV and a softness of 0.54 eV⁻¹. The QSAR model yielded R² = 0.9161, adjusted R² = 0.8968, Q²LOO = 0.8685, Q²F1 = 0.8199, Q²F2 = 0.8195 and a concordance correlation coefficient of 0.8803. Compound 17 was identified as a response outlier. Four analogues of compound 15 were proposed and assessed computationally within the stated applicability domain. Conclusion: This combined approach offers a framework for molecular prioritisation, but predictions for the designed analogues require numerical reconciliation, followed by experimental assessment.