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    USE OF PATTERNED (SUPER) HYDROPHOBIC SURFACES IN SAMPLE PREPARATION

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    Ph.D. thesis document (4.538Mb)
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    Ghimire, Bidur
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    Abstract
    Digital microfluidics (DMF) is an emerging liquid-handling technology that enables the manipulation of small, discrete droplets (picoliters to microliters) in a precise and reproducible manner. The important applications of DMF involve droplet dispensing, moving, splitting and mixing contents within a droplet. Superhydrophobic (SH) surfaces are used in DMF for facilitating magnetic actuation of droplets and formation of microarrays. A surface is considered superhydrophobic if a water droplet displays both a water contact angle (θCA) >150◦, and a sliding angle (SA) <10◦. SH surfaces provide low frictional forces between a liquid droplet and the surface itself allowing for actuation using minimal force. Magnetic actuation uses an external magnetic field to manipulate droplets containing magnetisable particles (MPs).

    This thesis focuses on the actuation of organic and aqueous droplets on patterned (Super) hydrophobic surfaces. Different commercial coatings used in this study are Ultra-Ever Dry™, Never wet™ and Aculon®. Different surfaces can be patterned to higher surface energy patches called surface energy traps (SETs). Droplets can be pinned to the SETs and dewetted from the SETs. We utilize the contrasting behavior of patterned surfaces to quantitatively determine the ethanol in beer samples. The application of functionalized superparamagnetic particles (PMPs) in combination with magnetic separation techniques has been used for the fractionation of complex proteolytic digest of lysozyme. Droplet kinematic parameters are explored (e.g., volume, size of the SETs, particle concentrations, etc.). Furthermore, we utilize the patterned omniphobic surface Aculon® in combination with the magnetic actuation technique to extract a peptide (bradykinin) from artificial saliva. The fifth chapter of the thesis demonstrates the proof of principle of liquid chromatography (LC) archiving using high-density microarrays (HDMs) platform.
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    http://hdl.handle.net/1974/28644
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    • Department of Chemistry Graduate Theses
    • Queen's Graduate Theses and Dissertations
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