Literature DB >> 25441348

Use of individual retention modeling for gradient optimization in hydrophilic interaction chromatography: separation of nucleobases and nucleosides.

Eva Tyteca1, Davy Guillarme2, Gert Desmet3.   

Abstract

In this study, the separation of twelve nucleobases and nucleosides was optimized via chromatogram simulation (i.e., prediction of individual retention times and estimation of the peak widths) with the use of an empirical (reversed-phase) non-linear model proposed by Neue and Kuss. Retention time prediction errors of less than 2% were observed for all compounds on different stationary phases. As a single HILIC column could not resolve all peaks, the modeling was extended to coupled-column systems (with different stationary phase chemistries) to increase the separation efficiency and selectivity. The analytical expressions for the gradient retention factor on a coupled column system were derived and accurate retention time predictions were obtained (<2% prediction errors in general). The optimized gradient (predicted by the optimization software) included coupling of an amide and an pentahydroxy functionalized silica stationary phases with a gradient profile from 95 to 85%ACN in 6 min and resulted in almost baseline separation of the twelve nucleobases and nucleosides in less than 7 min. The final separation was obtained in less than 4h of instrument time (including equilibration times) and was fully obtained via computer-based optimization. As such, this study provides an example of a case where individual retention modeling can be used as a way to optimize the gradient conditions in the HILIC mode using a non-linear model such as the Neue and Kuss model.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Computer-assisted method development; HILIC; Individual retention modeling; Nucleobases; Nucleosides

Mesh:

Substances:

Year:  2014        PMID: 25441348     DOI: 10.1016/j.chroma.2014.09.065

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  3 in total

1.  Accurate prediction of retention in hydrophilic interaction chromatography by back calculation of high pressure liquid chromatography gradient profiles.

Authors:  Nu Wang; Paul G Boswell
Journal:  J Chromatogr A       Date:  2017-08-26       Impact factor: 4.759

Review 2.  Optimizing separations in online comprehensive two-dimensional liquid chromatography.

Authors:  Bob W J Pirok; Andrea F G Gargano; Peter J Schoenmakers
Journal:  J Sep Sci       Date:  2017-11-23       Impact factor: 3.645

Review 3.  Recent applications of retention modelling in liquid chromatography.

Authors:  Mimi J den Uijl; Peter J Schoenmakers; Bob W J Pirok; Maarten R van Bommel
Journal:  J Sep Sci       Date:  2020-11-03       Impact factor: 3.645

  3 in total

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