4.6 Article

The advantage of mixed-mode separation in the first dimension of comprehensive two-dimensional liquid-chromatography

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1358, 期 -, 页码 128-135

出版社

ELSEVIER
DOI: 10.1016/j.chroma.2014.06.086

关键词

Comprehensive two-dimensional liquid chromatography; Mixed mode; Peak-distribution area; Chinese Herbal Medicine; White wine

资金

  1. China Scholarship Council (CSC)
  2. German Academic Exchange Service (DAAD)

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Comprehensive two-dimension liquid chromatography (LC x LC) has exhibited its powerful ability to separate complex samples. However, the use of a single chromatographic mode in 1st dimension has been limited to the separation of components by their individual characteristics, such as hydrophobicity, ionic properties etc. The use of mixed-mode stationary phases has revealed opportunities to combine different retention mechanisms. In this respect, stationary phases featuring both RP-like hydrophobic and ion-exchange interactive sites promise great versatility in retaining both polar and more apolar ionic and non-ionic compounds. We have therefore developed an LC x LC system based on mixed-mode (strong anion exchange and reversed phase) in the first dimension and a C18 phase in the second dimension. The system has been evaluated with standard compounds and applied for the separation of white wine and Chinese Herbal Medicine (CHM). The mixed-mode system SAX-PFP x C18 results in a better separation than a single mode system such as SAX x C18 or PFP x C18. Although little improvement in orthogonality (0.91 instead 0.86) is achieved with SAX x C18, the mixed-mode SAX-PFP x C18 gives a much larger effective peak distribution area in the analysis of e. g. white wine. But the analysis of aqueous extracts of CHM (Hdyotis diffusa and Scutellaria barbata) with SAX-PFP x RP leads to a very long analysis time because of strong hydrophobic interactions with the PFP column. Thus, the system was changed by using a cyano phase instead of a PFP phase. The improved SAX-CN x C18 system shows a better peak distribution and more importantly a reasonable analysis time. (C) 2014 Published by Elsevier B.V.

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