Possibilities of retention prediction in fast gradient liquid chromatography. Part 1: Comparison of separation on packed fully porous, nonporous and monolithic columns

. 2013 Feb 22 ; 1278 () : 37-45. [epub] 20130108

Jazyk angličtina Země Nizozemsko Médium print-electronic

Typ dokumentu srovnávací studie, časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid23336942
Odkazy

PubMed 23336942
DOI 10.1016/j.chroma.2012.12.058
PII: S0021-9673(13)00022-8
Knihovny.cz E-zdroje

Due to ever increasing importance of short analysis times in modern HPLC practice, fast gradient elution is becoming widely used both in one-dimensional and two-dimensional separations, especially in the second dimension where the speed of separation is of primary importance. For method development and optimization, prediction of retention in gradient elution from the isocratic data is very important. This is principally possible using the well-established theory of gradient elution, especially for reversed-phase separations. Feasibility of these approaches has been proven in conventional liquid chromatography and commercial prediction software is available for this purpose. However, fast gradient chromatography employing short columns and gradient times in between 1 and 2 min or even less, impose additional stringent demands on the accuracy of prediction, due to rapid changes in mobile phase composition and increased role of extra-column contributions and instrumental dwell volume on the retention. In the present work, possibilities of prediction of the gradient elution times from the isocratic data measured only at two mobile phase concentrations were investigated in fast chromatography of alkylbenzenes, phenylurea and triazine pesticides on five columns differing in lengths: two monolithic ones and three packed with particles of different size. In the second dimension, gradient times are strongly restricted by the short cycle frequency. The effects of the flow-rate on the elution times, on the accuracy of their prediction and on peak capacity were studied under time constraint conditions. Gradient theory can be useful for the optimization of fast gradients.

Citace poskytuje Crossref.org

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...