Carboxylic acids: prediction of retention data from chromatographic and electrophoretic behaviours

A review of the main results reached in the prediction of retention data of carboxylic acids, inferred by their chromatographic and electrophoretic behaviour, is presented. Attention has been focused on the main separation methods used in carboxylic acids analysis, that is ion-exclusion, anion-exchange, reversed-phase (RP) liquid chromatography and capillary electrophoresis. Papers proposing mechanistic models as well as chemometric and multilayer feed-forward neural network analysis of ion chromatography (IC) and RP chromatographic retention data were reviewed. Principal component analysis, PCA, sequential simplex method and simultaneous modelling of response surfaces through simple nonlinear models (not related to equilibria involved in retention) have been considered. Computer simulations for the prediction of retention data have also been discussed. A quick overlook on the prediction of capacity factors of analytes by less common determination methods such as thin-layer, gas chromatography and supercritical fluid chromatography has also been done.