Structure-driven retention model for optimization of ternary solvent systems in reversed-phase liquid chromatography

Abstract

A new approach is presented fro the prediction of retention in reversed-phase liquid chromatography using ternary mobile phase compositions. The solvation parameter model is used to create the system constants that characterize the properties of the mobile and stationary phases in terms of the relative ease of cavity formation, and differences in dispersion, lone pair electron, dipole-type, and hydrogen-bond association interactions for all solvent compasitions employed. A statistical mixture-design approach provides system surfaces and models for the variation of individual system constants as a function of ternary solvent composition. The models for the system surfaces allow the retention factor to be predicted as a function of mobile phase composition for any compound whose descriptor values are known, or can be obtained from estimation rules or determined by experiment. The method is validated using a large literature data base for the retention factor of up to 46 varied aromatic solutes in 72 methonolacetonitrile-water and methonol-tetrahydrofuran-water mobile phase compositions.