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Invited Article

Sorting and separation of microparticles by surface properties using liquid crystal-enabled electro-osmosis

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 1936-1943 | Received 30 Mar 2018, Published online: 14 Jun 2018
 

ABSTRACT

Sorting and separation of microparticles is a challenging problem of interdisciplinary nature. Existing technologies can differentiate microparticles by their bulk properties, such as size, density, electric polarisability, etc. The next level of challenge is to separate particles that show identical bulk properties and differ only in subtle surface features, such as functionalisation with ligands. In this work, we propose a technique to sort and separate particles and fluid droplets that differ in surface properties. As a dispersive medium, we use a nematic liquid crystal (LC) rather than an isotropic fluid, which allows us to amplify the difference in surface properties through distinct perturbations of LC order around the dispersed particles. The particles are placed in an LC cell with spatially distorted molecular orientation subject to an alternating current electric field. The gradients of the molecular orientation perform two functions. First, elastic interactions between these pre-imposed gradients and distortions around the particles separate the particles with different surface properties in space. Second, these pre-imposed patterns create electro-osmotic flows powered by the electric field that transport the sorted particles to different locations thus separating them. The demonstrated unique sorting and separation capability opens opportunities in lab-on-a-chip, cell sorting and bio-sensing applications.

GRAPHICAL ABSTRACT

Supplementary material

Supplemental data for this article can be accessed here.

Acknowledgement

This work was supported by NSF grants DMR-1507637, DMS-1729509 and CMMI-1436565.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by NSF grants DMR-1507637, DMS-1729509 and CMMI-1436565.

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