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Issue 16, 2019
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Flow-assisted droplet assembly in a 3D microfluidic channel

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Abstract

Self-assembly of soft matter, such as droplets or colloids, has become a promising scheme to engineer novel materials, model living matter, and explore non-equilibrium statistical mechanics. In this article, we present detailed numerical simulations of few non-Brownian droplets in various flow conditions, specifically, focusing on their self-assembly within a short distance in a three-dimensional (3D) microfluidic channel, cf. [Shen et al., Adv. Sci., 2016, 3(6), 1600012]. Contrary to quasi two-dimensional (q2D) systems, where dipolar interaction is the key mechanism for droplet rearrangement, droplets in 3D confinement produce much less disturbance to the underlying flow, thus experiencing weaker dipolar interactions. Using confined simple shear and Poiseuille flows as reference flows, we show that the droplet dynamics is mostly affected by the shear-induced cross-stream migration, which favors chain structures if the droplets are under an attractive depletion force. For more compact clusters, such as three droplets in a triangular shape, our results suggest that an inhomogeneous cross-sectional inflow profile is further required. Overall, the accelerated self-assembly of a small-size droplet cluster results from the combined effects of strong depletion forces, confinement-mediated shear alignments, and fine-tuned inflow conditions. The deterministic nature of the flow-assisted self-assembly implies the possibility of large throughputs, though calibration of all different effects to directly produce large droplet crystals is generally difficult.

Graphical abstract: Flow-assisted droplet assembly in a 3D microfluidic channel

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Publication details

The article was received on 07 Dec 2018, accepted on 28 Mar 2019 and first published on 01 Apr 2019


Article type: Paper
DOI: 10.1039/C8SM02479K
Citation: Soft Matter, 2019,15, 3451-3460
  • Open access: Creative Commons BY-NC license
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    Flow-assisted droplet assembly in a 3D microfluidic channel

    Z. Ge, O. Tammisola and L. Brandt, Soft Matter, 2019, 15, 3451
    DOI: 10.1039/C8SM02479K

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