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    Characterization of a passive diffusion microdevice for assays of chemotaxis and morphogenesis

    Chakraborty, Ipshita
    : https://etd.library.vanderbilt.edu/etd-07262007-224841
    http://hdl.handle.net/1803/13606
    : 2015-08-14

    Abstract

    BIOMEDICAL ENGINEERING CHARACTERIZATION OF A PASSIVE DIFFUSION DEVICE FOR ASSAYS OF CHEMOTAXIS AND MORPHOGENESIS IPSHITA CHAKRABORTY Thesis under the direction of Professor John Wikswo Cell migration plays an important role in a wide variety of physiological phenomena, such as cancer, wound healing, and embryonic development. Microfluidic devices have become a highly useful platform for studying how cell migration influences these processes. An effort initiated in 2005 at the Vanderbilt Institute for Integrative Biosystems Research and Education (VIIBRE) has resulted in the development and fabrication of a class of multi-chambered implantable cell trap devices that can be used to examine the combinatorial effects of the gradients of diffusive substances. We have developed a Computational Flow Dynamics (CFD) model of one of these devices to visualize its function and derive information regarding significant parameters, such as concentration at different points in space at varying time points, flux entering the device chamber, and the gradient of substances entering the device at different time points. An important feature of this device is a narrow restriction channel that limits the amount of substance entering the device chamber. In this thesis, we present a set of studies conducted with the CFD model on the effect of the width of this channel on the diffusion rate in the device chamber. This thesis also investigates how CFD packages like Fluent and GAMBIT calculate small numbers such as those derived in microscale flows and the extent to which a microfluidic device can be approximated with a CFD model. Our results indicate that Fluent is a valuable tool for modeling these kinds of microfluidic devices; however, phenomena such as numerical diffusion and contour algorithms influence the final data values obtained, and future work on this model should be aimed at a more detailed study of these effects and further ways to circumvent them. Approved________________________________ Date______________
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