Computational Investigation of Corrosion Inhibition Properties of Hydrazine and Its Derived Molecules for Mild Steel

Abstract

Corrosion of mild steel has gained a lot of attention by many industries and academia. This study was aimed to find the corrosion inhibition properties of hydrazine and its 11 derived molecules for mild steel using computational method, namely, the density functional theory with Beck 3‐parameter Lee Yang and Parr functional along with the 6‐311++G (d, p) basis set using simple quantum chemical parameters. The main quantum chemical parameters were energies of highest occupied and lowest unoccupied molecular orbitals and their energy gap, dipole moment, hardness, softness, electrophilicity index, the fractions of electrons transmitted, the change energy back‐donation, electron‐donating power, electron‐accepting power, molecular electrostatic potential, and Fukui function as well as polarizability. The results indicated that hydrazine derivatives have good anticorrosion nature which is consistent with the experimental findings. Out of the 12 target inhibitor molecules, N′‐(3‐nitrobenzylidene) hydrazine carbodithioic acid (NBHCA) and N′‐(4‐dimethylaminobenzylidene) hydrazine carbodithioic acid (DABHCA) are the most effective inhibitors. According to the value of the quantum chemical parameters, E HOMO , Δ E gap , Χ, η , σ , ε , Δ N , α , and ΔE b-d DABHCA showed the top effective anticorrosion inhibitor, and by the value of the quantum chemical parameters, E LUMO , TE, ω − , and ω + NBHCA showed an effective anticorrosion inhibitor. The quantum chemical parameter data showed that NBHCA and DABHCA are nearly equivalent in their values, which is consistent with experimental values. Furthermore, a multiple‐linear regression equation was proposed as a quantitative structural activity relationship model to relate the calculated molecular descriptors of hydrazine derivatives to their experimental inhibition efficiencies obtained from literature. As a result, this model showed an excellent accuracy with an R ‐squared of 0.924 and this uses to predict inhibition efficiencies of another molecules.