Modeling Retention in Liquid Chromatography by using the Solvation Parameter Model

GOTTA, J.; CASTELLS, C. B.; RETA, M. R.

Budapest

Simposio; 36th. Internacional Symposium on HPLC and Related Techniques (HPLC2011); 2011

HPLC Symposium

The prediction capability of the solvation parameter model (SP) in reverse phase chromatography (RPLC) at different methanol-water mobile phase compositions (40-70 % MeOH) and temperatures (30-70 °C) was investigated. By using a carefully selected set of solutes, the ?training set?, linear solvation energy relationships (LSER) were established by using multiple linear regression equations between the logarithm of the retention factor, log k, and different solute parameters of polarity, polarizability, acidity, basicity and molar volume. The solute parameters for which no information was obtained from the literature were calculated by a commercial software. The chemical interpretation of the LSER coefficients and its variation with mobile phase composition, φ, and the temperature, T, were in agreement with previous results and chemical intuition. These coefficients were used to create a general and simple retention model able to predict retention in RPLC, where only the solute parameters for the studied analytes, the mobile phase composition and the temperature are the input parameters. To check for the validity of the model, a different set of solutes of very diverse chemical nature, the ?test set?, was used. Retention for these compounds was measured at two different set of experimental conditions (Temperature and mobile phase composition) not used for the training set (65% Methanol, 40°C and 45% Methanol, 60°C). For the mentioned test set, very good retention predictions with low average standard deviations were obtained. The model also performed very well for solutes with descriptors very out of the ranges used for the training set.