Literature DB >> 15214671

Determination of the pH of binary mobile phases for reversed-phase liquid chromatography.

Martí Rosés1.   

Abstract

The measurement of pH in chromatographic mobile phases has been a constant subject of discussion during many years. The pH of the mobile phase is an important parameter that determines the chromatographic retention of many analytes with acid-base properties. In many instances a proper pH measurement is needed to assure the accuracy of retention-pH relationships or the reproducibility of chromatographic procedures. Three different methods are common in pH measurement of mobile phases: measurement of pH in the aqueous buffer before addition of the organic modifier, measurement of pH in the mobile phase prepared by mixing aqueous buffer and organic modifier after pH calibration with standard solutions prepared in the same mobile phase solvent, and measurement of pH in the mobile phase prepared by mixing aqueous buffer and organic modifier after pH calibration with aqueous standard solutions. This review discusses the different pH measurement and calibration procedures in terms of the theoretical and operational definitions of the different pH scales that can be applied to water-organic solvent mixtures. The advantages and disadvantages of each procedure are also presented through chromatographic examples. Finally, practical recommendations to select the most appropriate pH measurement procedure for particular chromatographic problems are given.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15214671     DOI: 10.1016/j.chroma.2003.12.063

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


  3 in total

1.  An unexpected observation concerning the effect of anionic additives on the retention behavior of basic drugs and peptides in reversed-phase liquid chromatography.

Authors:  Xiaoli Wang; Peter W Carr
Journal:  J Chromatogr A       Date:  2007-03-21       Impact factor: 4.759

2.  Application of a modified linear solvation energy relationship (LSER) model to retention on a butylimidazolium-based column for high performance liquid chromatography.

Authors:  P R Fields; Y Sun; A M Stalcup
Journal:  J Chromatogr A       Date:  2010-12-03       Impact factor: 4.759

3.  Machine Learning for Absolute Quantification of Unidentified Compounds in Non-Targeted LC/HRMS.

Authors:  Emma Palm; Anneli Kruve
Journal:  Molecules       Date:  2022-02-02       Impact factor: 4.411

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.