A simple approach for retention prediction in the pH-gradient reversed-phase liquid chromatography.

A simple approach for retention modeling of solutes under pH-gradient conditions at various organic contents in the mobile phase is proposed. This approach is based on a retention model arising from the evaluation of the retention data of a set of 17 OPA derivatives of amino acids obtained in two series of 22 pH-gradient runs performed between a given initial and final pH value (between 2.8 and 10.7 or 3.2 and 9.0) with different gradient duration and with different organic modifier content in the eluent. The derived model is a fifth-parameter equation easily manageable through a linear least-squares fitting. It requires only 6 initial pH-gradient experiments, allows a very satisfactory prediction for various pH-changes of the same kind with those used in the fitting procedure and seems to be very promising in separation optimization under pH-gradient conditions. The pH-gradient method appears to be especially suitable and effective for separation of amino acid derivatives whereas the application of pH-gradients from 3.2 to 9.0 proved to be beneficial.