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Updated: Mar 7, 2026

Adapting Taylor Dispersion to Measure the Dispersion Coefficient of Electrolyte Solutions via an Accessible Microfluidic Setup
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Large deviations in Taylor dispersion.

Marcel Kahlen1, Andreas Engel1, Christian Van den Broeck1

  • 1Universität Oldenburg, Institut für Physik, 26111 Oldenburg, Germany Hasselt University, Faculty of Sciences, B-3590 Diepenbeek, Belgium.

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|February 18, 2017
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Summary
This summary is machine-generated.

We linked Taylor dispersion to empirical distribution theory. This provides a more precise, long-time description of Taylor dispersion using large deviations theory.

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Area of Science:

  • Fluid dynamics
  • Statistical physics
  • Probability theory

Background:

  • Taylor dispersion describes solute spreading in fluid flow.
  • Existing models may lack precision in long-time regimes.
  • Empirical distributions offer a framework for data analysis.

Purpose of the Study:

  • To connect Taylor dispersion with empirical distribution theory.
  • To develop a more accurate long-time description of Taylor dispersion.
  • To apply large deviations theory for enhanced precision.

Main Methods:

  • Establishing a theoretical link between Taylor dispersion and empirical distributions.
  • Utilizing the theory of large deviations.
  • Deriving a new mathematical description for the long-time behavior.

Main Results:

  • A novel connection between Taylor dispersion and empirical distribution theory is established.
  • A more precise mathematical description for the long-time regime of Taylor dispersion is derived.
  • The application of large deviations theory enhances the accuracy of the dispersion model.

Conclusions:

  • The integration of empirical distribution theory offers a powerful new perspective on Taylor dispersion.
  • The derived model provides superior accuracy for predicting long-term solute spreading.
  • This work advances the theoretical understanding and predictive capabilities of Taylor dispersion phenomena.