Exploring the feasibility of new eco-friendly heterocyclic compounds for establishing efficient corrosion protection for N80 steel in a simulated oil well acidizing environment: From molecular-level prediction to experimental validation

Abstract

Corrosion inhibitors are an effective and low-cost option to relieve strong acid-induced corrosion during acidizing oil wells. In this work, a computational study was conducted to assess the interaction of newly synthesized eco-friendly compounds namely, (R, E)-N′-(4-(dimethylamino)benzylidene)− 2-(4-isobutylphenyl) propanehydrazide (DBIP) and (R,E)− 2-(4-isobutylphenyl)-N′-(4-nitrobenzylidene) propanehydrazide (INBP) with the steel surface. Theoretical prediction of compounds’ affinity to the steel surface and interaction mechanisms were elucidated at the molecular level using first-principles density-functional tight-binding (DFTB), quantum chemical descriptors (QCDs), Fukui functions (FFs) and molecular dynamics (MD) simulations. Then, the corrosion inhibition performance of selected compounds for N80 steel in 15 wt% HCl solution was investigated using weight loss (WL), electrochemical impedance spectroscopy (EIS), potentiodynamic polarization curves (PPCs) methods, and field emission scanning electron microscopy (FESEM). A theoretical investigation by DFTB modeling and Partial Density of States (PDOSs) showed the formation of several covalent bonds between inhibitor molecules and Fe(110) surface. Experimental studies revealed an increased inhibition efficiency of both inhibitors DBIP and INBP with increasing concentrations reaching a higher efficiency of 99% at 5 × 10−3 mol/L of DBIP. The PPCs data confirmed the mixed-type nature of inhibition. The adsorption obeyed the Langmuir isotherm model, following a mixed physical and chemical interaction mode. The surface morphology analysis by FESEM showed a protected N80 steel surface in the presence of inhibitors compared to its highly corroded surface in blank solutions. The present results open an interesting approach for developing a highly efficient corrosion inhibitor formulation for oil well acidizing based on low-cost computational prediction. © 2022 Elsevier B.V.