PhD Dissertation: Arzu Özbey
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Arzu Özbey
Mechatronics Engineering, PhD Dissertation, 2017


Thesis Jury

Prof. Dr. Ali Koşar (Thesis Advisor),

Prof. İ. Kürşat Şendur, Assoc. Prof. İ. Burç Mısırlıoğlu, Asist. Prof. Yegan Erdem (Bilkent University), Asist. Prof. Timm Krüger (University of Edinburgh)



Date & Time: July 31th, 2017 – 13:00 PM

Place: SUNUM G111

Keywords: Inertial Microfluidics, Particle Focusing, Curvilinear Microchannel




Inertial microfluidics has become one of the emerging topics due to potential applications such as particle separation, particle enrichment, rapid detection and diagnosis of circulating tumor cells (CTCs). To realize its integration to such applications, underlying physics should be well understood. This dissertation focuses on particle dynamics in curvilinear channels with different curvature angles (280°, 230° and 180°), where advantages of hydrodynamic forces are exploited as well as cancer cell line focusing in curvilinear channels with curvature angle of 280°. The cruciality of the 3D particle position with respect to inertial forces and Dean drag force is presented by examining the focusing behavior of 20 µm (large), 15 µm (medium) and 10 µm (small) fluorescent polystyrene microparticles, Jurkat, MDA and K562 cell lines for a wide range of flow rates (400-2700 µL/min) and corresponding channel Reynolds numbers (30-205). Migration of the particles and cells in lateral and vertical directions and their equilibrium positions are investigated in detail. In the framework of this studys findings, it can be concluded that an increase in curvature angle results in a better separation efficiency. Additionally, two different regions are described: transition region, where the inner wall becomes the outer wall and vice versa, and outlet region. Based on particles bypassing movement, designing outlets in transition region results in a better separation efficiency. This fundamental approach gives insight into the underlying physics of particle dynamics and offers continuous, high throughput, label-free and parallelizable size-based particle and cell separation.