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Retention modelling in hydrophilic interaction chromatography.

Melvin R Euerby1,2, Jennifer Hulse3, Patrik Petersson4

  • 1Hichrom Ltd, 1 The Markham Centre, Station Road, Theale, Reading Berkshire, RG7 4PE, UK. meuerby@hichrom.com.

Analytical and Bioanalytical Chemistry
|November 14, 2015
PubMed
Summary

This study evaluates hydrophilic interaction chromatography (HILIC) retention models for various analytes and parameters. HILIC retention modeling accuracy is comparable to reversed-phase chromatography (RPC), but gradient and isocratic predictions are not interchangeable.

Keywords:
Design of experimentsHydrophilic interaction chromatographyInfluence of operating parametersMethod development strategyRetention and peak width modellingRetention behaviour

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Area of Science:

  • Analytical Chemistry
  • Chromatography

Background:

  • Hydrophilic interaction chromatography (HILIC) is a key separation technique.
  • Accurate retention prediction is crucial for method development in HILIC.

Purpose of the Study:

  • To evaluate existing and new empirical HILIC retention models.
  • To assess the impact of HILIC operating parameters on analyte retention and selectivity.
  • To determine the reliability of HILIC retention modeling for isocratic and gradient separations.

Main Methods:

  • Analyzed retention behavior of diverse analytes on various HILIC stationary phases.
  • Investigated HILIC operating parameters: MeCN content, buffer concentration, pH, and temperature.
  • Assessed empirical retention models using ACD/LC simulator software.
  • Applied statistical approaches to rank parameter importance for retention and selectivity.

Main Results:

  • HILIC retention modeling accuracy is comparable to reversed-phase chromatography (RPC).
  • Organic content and stationary phase type are most critical for retention; stationary phase and pH are key for selectivity.
  • Gradient and isocratic HILIC retention predictions are not reliably interchangeable.

Conclusions:

  • Established the applicability of HILIC retention modeling in 1D and 2D separations.
  • Provided a framework for optimizing HILIC methods through parameter ranking.
  • Highlighted limitations in predicting isocratic from gradient conditions and vice versa.