Computer-Assisted Modeling, Prediction, and Multifactor Optimization in Micellar Electrokinetic Chromatography of Ionizable Compounds

Abstract

Previously, the use of phenomenological models to describe the migration behavior of acidic solutes in micellar electrokinetic chromatography (MEKC) was reported. In this paper, the phenomenological approach is further extended by including both acidic and basic solutes and simultaneously taking two important experimental factors (pH and micelle concentration) into consideration. In addition, a general method is described to model the migration behavior of ionizable (both acidic and basic) solutes in MEKC with anionic and cationic micelles. The practical implication of the phenomenological approaches is that they will provide quantitative relationships between solute migration and experimental factors such that the migration behavior can be predicted on the basis of a few initial experiments and that physicochemical parameters of solutes can also be estimated from model fitting. Through computer-assisted modeling, migration behavior of several acidic and basic solutes over a pH-micelle concentration factor space was successfully predicted on the basis of only five experiments. Furthermore, this phenomenological approach was used to predict the separation of a group of aromatic amines in MEKC with anionic micelles, which resulted in a successful separation of 18 aromatic amines in less than 15 min.