Possibility of predicting separations in supercritical fluid chromatography with the solvation parameter model

In order to obtain a selection of optimal chromatographic columns for the separation of chlorotriazine pesticides in packed column supercritical fluid chromatography (pSFC), a multi-criteria approach is applied. For this purpose, prediction of the separations is carried out, based on quantitative structure–retention relationships, then Derringer's desirability function is proposed to determine the stationary phase that will result in the most desirable separation. The best SFC separation obtained was then optimized using a mobile phase gradient. Besides, the accuracy of the solvation parameter model as SFC retention predictive model is assessed.