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A Dual Column pH Switchable Water Stationary Phase System for Separation Control in Supercritical Fluid Chromatography.

  • Published In: Journal of Separation Science, 2024, v. 47, n. 21. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nai, Emmanuel A.; Thurbide, Kevin B. 3 of 3

Abstract

A dual column system comprised of a pH switchable water stationary phase column and a conventional non‐polar capillary column is introduced for use in Supercritical Fluid Chromatography (SFC). By removing or adding NH4OH to the system hydration source, the water stationary phase pH can be rapidly switched between acidic (measured at pH∼3) and basic (measured at pH∼9) in seconds, while the operating character of the conventional column is unchanged. This switch modulates the velocity of ionizable analytes about 20‐fold in the system, whereas non‐ionizable analytes are not affected. In this way, the retention time of acids and/or bases can be reproducibly altered (<1% RSD; n = 3) in SFC separations. As a result, analyte selectivity and resolution can be readily controlled during analyses. For example, a selectivity reversal (alpha from 0.4 to 1.6) and a resolution increase (from 0 to 13) are demonstrated. Rapid stationary phase pH switching also allows multiple acids, bases, and/or neutral analytes to be determined simultaneously. Applications demonstrate that this method can greatly simplify complex mixture analysis in SFC by helping to separate target analytes from interfering matrix components. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Separation Science. 2024/11, Vol. 47, Issue 21, p1
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2024
  • ISSN:1615-9306
  • DOI:10.1002/jssc.70008
  • Accession Number:180902453
  • Copyright Statement:Copyright of Journal of Separation Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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