Biomolecular interactions control the shape of stains from drying droplets of complex fluids

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Hurth, Cedric
Bhardwaj, Ranjeesh
Andalib, Sahar
Frankiewicz, Christophe
Dobos, Andrew
Zenhausern, Frederic
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Attinger, Daniel
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Mechanical Engineering
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When a sessile droplet of a complex fluid dries, a stain forms on the solid surface. The structure and pattern of the stain can be used to detect the presence of a specific chemical compound in the sessile droplet. In the present work, we investigate what parameters of the stain or its formation can be used to characterize the specific interaction between an aqueous dispersion of beads and its receptor immobilized on the surface. We use the biotin-streptavidin system as an experimental model. Clear dissimilarities were observed in the drying sequences on streptavidin-coated substrates of droplets of aqueous solutions containing biotin-coated or streptavidin-coated beads. Fluorescent beads are used in order to visualize the fluid flow field. We show differences in the distribution of the particles on the surface depending on biomolecular interactions between beads and the solid surface. A mechanistic model is proposed to explain the different patterns obtained during drying. The model describes that the beads are left behind the receding wetting line rather than pulled towards the drop center if the biological binding force is comparable to the surface tension of the receding wetting line. Other forces such as the viscous drag, van der Waals forces, and solid–solid friction forces are found negligible. Simple microfluidics experiments are performed to further illustrate the difference in behavior where is adhesion or friction are present between the bead and substrate due to the biological force. The results of the model are in agreement with the experimental observations which provide insight and design capabilities. A better understanding of the effects of the droplet–surface interaction on the drying mechanism is a crucial first step before the identification of drying patterns can be promisingly applied to areas such as immunology and biomarker detection.


NOTICE: this is the author’s version of a work that was accepted for publication in Chemical Engineering Science. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Chemical Engineering Science, [137, (2015)] doi:10.1016/j.ces.2015.06.059

Thu Jan 01 00:00:00 UTC 2015