Using Molecular Dynamics Simulations and Genetic Function Approximation to Model Corrosion Inhibition of Iron in Chloride Solutions

摘要

Density functional theory (DFT) calculations have been used to investigate the minimum energystructures of asparagine molecules on iron (Fe) (111) surface. Adsorption of the asparagine moleculeon a Fe (111) surface has been studied computationally to generate adsorption configurations and touse the force field method to obtain a ranking of the energies for each generated configuration, therebyindicating the preferred adsorption sites. In this article Monte Carlo simulation has been used to findlow energy adsorption sites on both adsorbate (asparagines) substrate (Fe 111) systems as thetemperature of the system is gradually decreased. The results indicated that asparagine could adsorb ona Fe surface through the nitrogen/oxygen atoms with the lone pair of electrons in its molecule.TheQuantitative Structure Activity Relationship (QSAR) method is becoming more desirable forpredicting corrosion inhibition properties. The inhibition efficiency of organic compounds isdependent on many basic molecular descriptors, such as dipole moments, molecular surface area,molecular volume, electronic parameters as EHOMO (highest occupied molecular orbital energy); ELUMO(lowest unoccupied molecular orbital energy); and energy gap (ELUMO - EHOMO). A Genetic FunctionApproximation (GFA) method was used to run the regression analysis and establish correlationsbetween different types of descriptors and the measured corrosion inhibition efficiencies of 28 aminoacids and their related compounds. Similarly, a QSAR equation was developed and used to predict thecorrosion inhibition efficiencies of 28 amino acids and their related compounds. The prediction ofcorrosion efficiencies of these compounds nicely matched the experimental measurements.