4.7 Article

Sample dispersion in isotachophoresis

Journal

JOURNAL OF FLUID MECHANICS
Volume 679, Issue -, Pages 455-475

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/jfm.2011.139

Keywords

MHD and electrohydrodynamics; microfluidics

Funding

  1. DARPA [N66001-10-1-4003, N660001-09-C-2082]
  2. Stanford School of Engineering
  3. Office of Technology Licensing Stanford Graduate Fellowship
  4. Fulbright Fellowship

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We present an analytical, numerical and experimental study of advective dispersion in isotachophoresis (ITP). We analyse the dynamics of the concentration field of a focused analyte in peak mode ITP. The analyte distribution is subject to electromigration, diffusion and advective dispersion. Advective dispersion results from strong internal pressure gradients caused by non-uniform electro-osmotic flow (EOF). Analyte dispersion strongly affects the sensitivity and resolution of ITP-based assays. We perform axisymmetric time-dependent numerical simulations of fluid flow, diffusion and electromigration. We find that analyte properties contribute greatly to dispersion in ITP. Analytes with mobility values near those of the trailing (TE) or leading electrolyte (LE) show greater penetration into the TE or LE, respectively. Local pressure gradients in the TE and LE then locally disperse these zones of analyte penetration. Based on these observations, we develop a one-dimensional analytical model of the focused sample zone. We treat the LE, TE and LE-TE interface regions separately and, in each, assume a local Taylor-Aris-type effective dispersion coefficient. We also performed well-controlled experiments in circular capillaries, which we use to validate our simulations and analytical model. Our model allows for fast and accurate prediction of the area-averaged sample distribution based on known parameters including species mobilities, EO mobility, applied current density and channel dimensions. This model elucidates the fundamental mechanisms underlying analyte advective dispersion in ITP and can be used to optimize detector placement in detection-based assays.

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