Global linear solvation energy relationships for retention prediction in reversed-phase liquid chromatography

Abstract

A global linear solvation energy relationship (LSER) that simultaneously models retention in reversed-phase liquid chromatography as a function of both solute LSER descriptors and mobile phase composition has been derived from both the local LSER model and the linear solvent strength theory (LSST). At most only twelve coefficients are required to establish the global LSER model. Many more coefficients would be required if the same data set were modeled using the local LSER model. The global LSER was tested with the retention data obtained in acetonitrile–water, tetrahydrofuran–water, and methanol–water mobile phases each at four or five mobile phase compositions for a large number of highly variegated solutes. Although fewer regression coefficients are used in a global LSER fit than in a series of local LSER fits for the same data, the results show that the goodness-of-fit of the global LSER is as good as that obtained in the local LSERs. The results also show that the residuals of the LSST fits are smaller than those of both the local LSER fits and the global LSER fit and that the residuals of a global LSER fit result mainly from the local LSER model and are not due to the LSST model.