Purification of complex samples: Implementation of a modular and reconfigurable droplet-based microfluidic platform with cascaded deterministic lateral displacement separation modules

Eloise Pariset, Catherine Pudda, François Boizot, Nicolas Verplanck, Frédéric Revol-Cavalier, Jean Berthier, Aurélie Thuaire and Vincent Agache

PLOS ONE, 2018, vol. 13, issue 5, 1-18

Abstract: Particle separation in microfluidic devices is a common problematic for sample preparation in biology. Deterministic lateral displacement (DLD) is efficiently implemented as a size-based fractionation technique to separate two populations of particles around a specific size. However, real biological samples contain components of many different sizes and a single DLD separation step is not sufficient to purify these complex samples. When connecting several DLD modules in series, pressure balancing at the DLD outlets of each step becomes critical to ensure an optimal separation efficiency. A generic microfluidic platform is presented in this paper to optimize pressure balancing, when DLD separation is connected either to another DLD module or to a different microfluidic function. This is made possible by generating droplets at T-junctions connected to the DLD outlets. Droplets act as pressure controllers, which perform at the same time the encapsulation of DLD sorted particles and the balance of output pressures. The optimized pressures to apply on DLD modules and on T-junctions are determined by a general model that ensures the equilibrium of the entire platform. The proposed separation platform is completely modular and reconfigurable since the same predictive model applies to any cascaded DLD modules of the droplet-based cartridge.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0197629

DOI: 10.1371/journal.pone.0197629

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