Corrosion inhibition of Q235A steel in acid medium using isatin derivatives: a QSAR study

Abstract

Quantitative Structure-Activity Relationship (QSAR) study was performed on 10 isatin derivatives which were reportedly used as corrosion inhibitors. Dragon software was used to calculate the molecular descriptors. Partial least square (PLS) method was used to run the regression analysis between the descriptors and the corrosion inhibition efficiencies (IE) of the inhibitors. A predictive QSAR model was developed with a correlation coefficient (r2 cal) of 0.9676. The model validity was assessed through internal and external validation. The results show that cross-validation regression coefficient (r2 cv) and prediction regression coefficient (r2 pred) are 0.8163 and 0.9189, respectively. The model was used to predict the IE for ten isatin derivatives. The results confirm a good stability and predictive ability of the model. Dragon-based descriptors provide a very good description of the corrosion inhibition properties of the inhibitors. The results of the QSAR study were found to be consistent with the experimental data.