Corrosion of metal and alloy is a critical phenomenon that has a big impact on safety and economic growth. It has been considered as one of the most pressing issues facing global industry. Numerous chemical compounds are commonly utilized to prevent this undesirable issue. Among them rhodanine and its derivatives serve as anti-corrosion agents, protecting metals such as iron. Currently, computational techniques have been employed to design several new corrosion inhibitors. Designing of novel inhibitors using Density functional theory (DFT) and Molecular dynamics (MD) simulation is a smart strategy. Our goal is to theoretically design a potential rhodanine-based corrosion inhibitor via varying the alkyl chain lengths -methyl (Me); ethyl (Et) and n -propyl (Pr) groups of amine group of the experimentally reported rhodanine derivative. The substituents NMe 2 , NEt 2 , and NPr 2 at N-4 position were screened, and the outcomes were compared with the reported molecule. Different global reactivity descriptors were computed at DFT/B3LYP/6-31++g (d,p) theoretical level to predict the impact of alkyl chain length on corrosion inhibition efficiency. Molecular electrostatic potential (MEP) surface analysis was also carried out. In addition to that, the interactions between designed molecules with the single Fe atom were taken in account. Moreover, molecular dynamics simulation was used to evaluate the adsorption behavior and binding pattern of the inhibitors on the Fe (110) metal surface. A correlation analysis was conducted between the parameters based on MD simulation and DFT. This comprehensive computational investigation demonstrates that the Pr-alkyl chain produces the best inhibitor.
Dey et al. (Sat,) studied this question.