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Genetic function approximation (GFA) algorithm was used to model the quantitative structure–activity relationship (QSAR) among corrosion inhibition efficiency, friction coefficient and oil film strength of the thiadiazole derivatives as corrosion inhibitor and antiwear and friction-reducing agent. Corrosion inhibition efficiency, friction coefficient and oil film strength of these compounds on the steel surface contained in the emulsion were studied by weight loss test and a fourball friction and wear test. The results show that quantum descriptors are a better choice for predicting the corrosion inhibition efficiency, friction coefficient and oil film strength of lubricants. For the thiadiazole derivatives, friction coefficient of the lubricants is inversely proportional to their inhibition efficiency and oil film strength.

QSAR Models for the Prediction of the Relationship Among Corrosion Inhibition Efficiency, Friction Coefficient and Oil Film Strength of Lubricants