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QSPR prediction analysis of corrosion inhibitors in hydrochloric acid on 22%-Cr stainless steel

Corrosion inhibitors have been widely used to prevent corrosion on stimulation operations on petroleum wells. Detailed experimental and theoretical investigation of twenty three different compounds including amines, thiourea derivatives, and acetylenic alcohols were carried out to estimate their inhibition corrosion efficiency on 22% Cr stainless steel (austenitic-ferritic, duplex) in hydrochloric acid (15% m/v) solutions. The obtained data were theoretically interpreted with respect to prediction, regression analysis (OLS), principal analysis component (PCA) and partial regression analysis (PLS) employing quantum and group contribution descriptors. In our study we found advantage in the use of the weight isoesteric Langmuir adsorption function (WILA), ln(thetaM/(1-theta)) or lnKads. Excellent correlations were obtained for most models and few equations, results, calibration and validation plots were discussed in the text. The content of the present work represents a first step toward an efficient estimation of the inhibition corrosion efficiency (ICE) of arbitrary inhibitors towards several metals, alloys and steel types.

corrosion inhibitor; regression analysis; QSPR (Quantitative Structure Properties Relationship); interfaces


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