A Computational Model for Predicting Fully-Coupled Particle-Fluid Dynamics and Self-Assembly for Magnetic Particle Applications
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Magnetic particles are increasingly used in microfluidic systems to selectively separate and sort biomaterial from a specimen for a broad range of biomedical and clinical diagnostic applications. To date, most theoretical studies of such systems have been based on one-way particle fluid coupling wherein the fluid flow influences particle motion, but the flow is assumed to be constant, independent of particle motion. Relatively few groups have taken into account more rigorous two-way particle-fluid coupling wherein momentum is transferred from the particles to the fluid, thereby altering the flow. In this thesis we introduce a unique computational model that can be used to predict magnetophoretic phenomena in a broad range of microfluidic systems. The novel features of this model are its capability and versatility. With regards to capability, the model predicts particle transport, manipulation and aggregation taking into account fully-coupled particle-fluid interactions and magnetic dipole-dipole forces that induce self-assembly of the particles. The particle-fluid coupling involves two-way momentum transfer between the fluid and the particles wherein the fluid flow impacts particle motion, which, in turn, alters the flow field in a self-consistent fashion. This is in contrast to the vast majority of work in this field, which is usually based on one-way coupling wherein the fluid flow impacts particle motion, but not vice versa. Also, few groups have modeled dipole-dipole interactions in microfluidic systems, which give rise to self-assembly and aggregation, effects that can be especially important in particle separation applications. With regards to versatility, we have implemented the model by integrating custom-developed algorithms into a state-of-the-art commercial computational fluid dynamic (CFD) program, FLOW-3D from flowscience (www.flow3d.com). The advantage of using FLOW-3D is that it is capable of modeling general microfluidic applications, i.e. arbitrary geometries, real-world boundary conditions, a wide range of fluid properties (e.g. temperature and strain dependent viscosity), conjugate heat transfer, and multiphase and free-surface analysis etc. We leverage this capability to enable the broadest range of applications for our custom magnetic analysis. We demonstrate the versatility and capability of the model via application to microfluidic-based sorting, separation and micromixing systems. The thesis is organized as follows. The first chapter is an introduction towards magnetic particles in which covers particle properties, functions and recent research on magnetic particles. Chapter 2 contains a brief review of fundamental principles of magnetism. This is followed by a discussion of the preparation and properties of magnetic nanoparticles in Chapter 3. We introduce the computational model in Chapter 4 and apply it to continuous flow sorting, bioseparation and micromixing systems in Chapters 5, 6 and 7 respectively.