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Related Experiment Videos

Resolution optimisation in micellar electrokinetic chromatography using empirical models.

P V van Zomeren1, M J Hilhorst, P M Coenegracht

  • 1Department of Analytical Chemistry and Toxicology, University of Groningen, The Netherlands.

Journal of Chromatography. A
|February 12, 2000
PubMed
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Empirical models effectively optimize resolution in micellar electrokinetic chromatography (MEKC). Modeling effective mobility with average plate numbers offers superior accuracy for predicting separation performance.

Area of Science:

  • Analytical Chemistry
  • Separation Science

Background:

  • Micellar electrokinetic chromatography (MEKC) is a powerful separation technique.
  • Optimizing resolution is crucial for effective MEKC analysis.

Purpose of the Study:

  • To compare empirical modeling approaches for optimizing MEKC resolution.
  • To identify the most suitable modeling strategy for predicting separation characteristics.

Main Methods:

  • Utilized empirical models to predict migration and separation characteristics in MEKC.
  • Compared different empirical approaches, focusing on modeling effective mobility and apparent mobility.
  • Evaluated prediction errors for models of effective mobility, apparent mobility, resolution, and separation factor.

Main Results:

Related Experiment Videos

  • Models of effective mobility combined with average plate numbers showed 2-4 times smaller prediction errors than apparent mobility models.
  • For closely migrating peaks, effective and apparent mobility models yielded approximately half the prediction error compared to resolution and separation factor models.
  • Predictions of the separation factor generally had lower errors than predictions of resolution.

Conclusions:

  • Empirical modeling, particularly using effective mobility, is a viable strategy for optimizing MEKC separation buffers.
  • Despite large prediction errors for closely migrating compounds, this approach aids in achieving optimal buffer compositions.