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Title: Characterization of surface–solute interactions by diffusioosmosis
The accurate measurement of wall zeta potentials and solute–surface interaction length scales for electrolyte and non-electrolyte solutes, respectively, is critical to the design of many biomedical and microfluidic applications. We present a novel microfluidic approach using diffusioosmosis for measuring either the zeta potentials or the characteristic interaction length scales for surfaces exposed to, respectively, electrolyte or non-electrolyte solutes. When flows containing different solute concentrations merge in a junction, local solute concentration gradients can drive diffusioosmotic flow due to electrokinetic, steric, and other interactions between the solute molecules and solid surfaces. We demonstrate a microfluidic system consisting of a long, narrow pore connecting two large side channels in which solute concentration gradients drive diffusioosmosis within the pore, resulting in predictable fluid velocity/pressure and solute profiles. Furthermore, we present analytical results and a methodology to determine the zeta potential or interaction length scale for the pore surfaces based on the solute concentrations in the main side channels, the flow rate in the pore, and the pressure drop across the pore. We apply this method to the experimental data of Lee et al. to predict the zeta potentials of their system, and we use 3D numerical simulations to validate the theory and show that end effects caused by the junctions are negligible for a wide range of parameters. Because the dynamics in the proposed system are driven by diffusioosmosis, this technique does not suffer from certain disadvantages associated with the use of sensitive electronics in traditional zeta potential measurement approaches such as streaming potential, streaming current, or electroosmosis. To the best of our knowledge this is the first flow-based approach to characterize surface/solute interactions with non-electrolyte solutes.  more » « less
Award ID(s):
1702693
NSF-PAR ID:
10093277
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Soft Matter
Volume:
15
Issue:
7
ISSN:
1744-683X
Page Range / eLocation ID:
1582 to 1596
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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