Simultaneous optimization of mobile phase composition, column nature and length to analyse complex samples using serially coupled columns

Abstract

The combination of the selectivity of different columns serially coupled improves the separation expectancies with regard to the separation offered by each single column. In the reported approaches, either a pre-selected isocratic mobile phase composition or gradient program, giving rise to acceptable retention, is used. In previous work (JCA 1281 (2013) 94), we showed that the approach succeeds with conventional columns, assembled through zero-dead volume couplers. In this work, the simultaneous interpretive optimization of mobile phase composition and column nature and length, based on a limited number of experimental data, is demonstrated. This approach allows an impressive reduction in the number of different column lengths needed without loss of performance. The massive computation needed to develop the approach was cropped by restricting the maximal analysis time, total pressure and combined column length. Guidelines to model peak position and half-widths with low errors are given, which increase the reliability of the optimizations. Pareto plots, expressed as analysis time versus predicted resolution, assisted in the selection of the best separation conditions. Five ACE columns of different selectivity (C18, C18-HL, AQ, CN and Phenyl), available at two or three different lengths, were used to demonstrate the approach. Isocratic experiments with acetonitrile–water in the 10–20% (v/v) range were developed to model each single column, aimed to analyse a mixture of 15 sulphonamides. No single column was able to succeed in the full separation. In contrast, the comprehensive optimization of mobile phase composition, together with column nature and length, allowed baseline resolution of the mixture in approximately 20min.