COMPUTATIONAL DESIGN OF DIBENZO[a,c]QUINOXALINO(2,3-I) PHENAZINE AS ECO-FRIENDLY CORROSION INHIBITORS: A DFT AND MONTE CARLO SIMULATIONS STUDIES
Keywords:
Corrosion inhibition, Dibenzo[a,c]quinoxalino(2,3-i)phenazine, Density Functional Theory (DFT), Monte Carlo simulationsAbstract
Corrosion of mild steel in acidic environments remains a critical challenge for industrial infrastructure, driving the need for sustainable, high-performance inhibitors. This study investigates the corrosion-inhibition potential of dibenzo[a,c]quinoxalino(2,3-i)phenazine (DQP), a nitrogen-rich heterocyclic compound, using computational approaches. Density Functional Theory (DFT) and Monte Carlo (MC) simulations were employed to elucidate molecular geometry, electronic properties, and adsorption mechanisms on Fe(110) surfaces. The optimized planar DQP structure exhibits a conjugated π-system with a narrow HOMO-LUMO energy gap (2.48 eV), low chemical hardness (1.24 eV), and high softness (0.806 eV⁻¹), indicative of strong electron-donating and accepting capabilities. Fukui function analysis identified nitrogen atoms and adjacent carbons as nucleophilic sites, facilitating multidentate coordination with iron surfaces. Molecular electrostatic potential maps further localized electron-rich regions over nitrogen atoms, corroborating their role in chemisorption. MC simulations revealed thermodynamically stable adsorption of DQP on Fe(110), with a parallel orientation maximizing π-orbital interactions and surface coverage. The negative back-donation energy (-1.11 eV) and low adsorption energy (-50.41 kJ/mol) highlight efficient charge transfer and robust interfacial stability. Electronic absorption spectra highlighted intramolecular charge transfer transitions (419.78–515.48 nm), reinforcing DQP’s capacity to passivate metal surfaces. The dual functionality of DQP (electron donation via heteroatoms and electron acceptance through back-donation) alongside its planar adsorption geometry, positions it as a potent eco-friendly inhibitor. These findings provide a computational framework for rational design of corrosion inhibitors, emphasizing molecular engineering to balance efficacy, stability, and environmental compatibility.
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