Quantitative structure and activity relationship modeling study of corrosion inhibitors: Genetic function approximation and molecular dynamics simulation methods

Abstract

QSAR studies on the inhibition corrosion efficiencies of twenty three organic compounds on steel surface in hydrochloric acid solutions using several physicochemical descriptors and investigation of the adsorption of these compounds on the steel surface by Monte Carlo simulation method were studied. Topological indices as well as several structural descriptors are used in the development of quantitative structure-activity relationships (QSARs) using genetic function approximation statistical analysis method. From our studies it is clear that quantum descriptors are a better choice when predictivity is the main issue. Among the descriptors with major contribution we should point out that lowest unoccupied molecular orbital energy (ELUMO) and molecular volume are important predictive descriptors. Computational studies have been used to find the most stable adsorption sites for tributlyamine inhibitor on steel surface. © 2011 by ESG.