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" High Throughput Passive Inertial Separation of Viscoelastic Droplets in Microchannels "
Karimi, Armin
Di Carlo, Dino; Chiou, Pei-Yu
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Latin Dissertation
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English
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| Record Number
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905725
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TL0b39v9rs
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| Main Entry
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Karimi, Armin
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High Throughput Passive Inertial Separation of Viscoelastic Droplets in Microchannels\ Karimi, ArminDi Carlo, Dino; Chiou, Pei-Yu
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UCLA
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2018
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2018
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| Abstract
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Droplet microfluidics offers a unique liquid-handling capability for various applications, such as single cell analysis and sorting, chemical synthesis and development of biochemical assays, diagnostics, drug screening, DNA sequencing and directed evolution. Producing highly monodisperse pico-liter to nano-liter droplets enables quantitative control of solute concentration, while compartmentalizing samples into droplets provides a precise chemical and bio-chemical environment. Small volume and high concentration of encapsulated samples allows for rapid processing and analysis of the thousands to millions of cells that must be screened to find a heterogenous population of interest. Being able to effectively sort droplets is in high demand. A limiting factor for active sorting of droplets is the real time sensing and control mechanism that they require. The control components of active systems lead to a complex and expensive sorting device. On the other hand, passive methods of droplet sorting which operate based on intrinsic properties of droplets, are especially important to reduce the complexity and cost. Many biological reactions that occur inside droplets can alter droplet properties, such as viscosity, interfacial tension and viscoelasticity. In this study we focus on non-Newtonian fluids which exhibit viscoelastic properties. A need to passively sort droplets based on intrinsic properties, in an inertial flow regime, is of an immense importance. Viscoelastic solutions possess unique properties such as shear rate dependence viscosity, and relaxation time. We developed an integrated microfluidics platform to generate, incubate, and sort droplet based on viscoelastic properties on-chip. One approach to achieve this is by tuning the timescale of flow compare to relaxation time of viscoelastic droplets, where we engineered our platform to pre-deformed droplet, and the droplet retains its deformed shape within the relaxation time. This results in a significant enhancement in viscoelastic-based droplet sorting. Viscoelastic solutions possess unique properties such as shear rate dependence viscosity, and relaxation time, which is an inherent property of a viscoelastic solutions. In this work we have developed an integrated microfluidics platform to generate, incubate and sort viscoelastic droplets of interest without the need for active sensing components..
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Di Carlo, Dino; Chiou, Pei-Yu
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UCLA
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