Predictive qspr analysis of corrosion inhibitors for super 13% cr steel in hydrochloric acid

An experimental and theoretical study on the inhibition corrosion efficiencies of twenty three compounds in hydrochloric acid (15% w/v) on 13% Cr modified stainless steel (martensitic) has been carried out. This inhibitor set includes amines, thiourea derivatives and acetylenic alcohols. Experimental weight losses at 60 degrees C were correlated with group and quantum AMI descriptors obtained from QSPR analysis. Such data, for a large set of molecules, offer a unique opportunity for searching for correlations between inhibition corrosion efficiency and molecular properties. Calculations based on three different statistical methodologies were carried out. The first method, using calibration procedures, employs an ordinary least squares (OLS) methodology with a simple descriptor selection based on R-2 values. From this procedure, we obtained a model, Y-15, having a R-2 value of 0,979 and a Q(2) value of 0.786. The second method employs a descriptor selection based on the second-order cross-validation OLS procedure (SOCV-OLS). In this process, the variables are chosen according to their ability to predict molecular inhibition efficiencies. The best model obtained using this methodology, Q(5), had R-2 and Q(2) values of 0.859 and 0.785, respectively. The third method, based on regular partial least squares (PLS), resulted in R-2 and Q(2) values of 0.859 and 0.754, respectively. All calculations were carried out for the weight isoesteric Langmuir adsorption function (WILA function), ln(theta M/(1-theta)) or ln K-ads. A careful comparison between the calibration and the cross-validation descriptor selection indicated that they had very few descriptors in common. This article presents some key equations and the most relevant descriptors. We are unaware of any similar QSPR study on super 13% Cr stainless steel in the literature.