SUBJECT: Ph.D. Dissertation Defense
BY: Fatima Ezahra Chrit
TIME: Wednesday, May 3, 2023, 11:00 a.m.
PLACE: MRDC Building, 3515
TITLE: Modeling and simulation of cells and particles in microfluidic channels
COMMITTEE: Dr. Alexander Alexeev, Chair (ME)
Dr. Spencer Bryngelson (CSE)
Dr. Todd Sulchek (ME)
Dr. David Hu (ME)
Dr. Xiangchun Xuan (ME)
Dr. Damir B. Khismatullin (BMED)


Suspensions of biological and synthetic particles are common both in nature and in numerous engineering applications in biomedical technology, food and chemical industry, and environmental pollution monitoring. Separation and sorting of cells and particles in heterogeneous populations are critical tasks often required in diverse applications. In this work, we investigate the isolation and sensing of cells and particles via their mechanical and surface properties using label-free and passive approaches. We consider microfluidic channels decorated with periodic diagonal ridges hanging from the top of the channel as a framework for continuous label-free cell separation. First, we examine the stiffness-based isolation of viable cells from heterogeneous samples and probe the effect of flow rate, ridge angle, and ridge gap on cells motion in the device. Then, we numerically investigate how the use of power-law fluids can enhance sorting via a size-based inertial migration as well as a stiffness-based sorting in ridged microchannels. Furthermore, we examine cell adhesion-based sorting in the microfluidic device and elucidate the important role of stiffness in enhancing this type of sorting. Design parameters such as ridge angle and gap size significantly affect cells motion in the device and thus should be optimized for best sorting efficiency. Our numerical simulations are conducted using the lattice Boltzmann method (LBM). In general, fluid flow simulations use our most powerful computational resources. Given that quantum computers provide an opportunity to speedup traditional computations, we explore quantum algorithms with application to partial differential equations. For that, we study a quantum LBM algorithm that revises a quantum lattice gas automata and we validate it by simulating the diffusion and Burgers' equations on different quantum simulators. Overall, the results of this work have applications in viability monitoring and measuring adhesion cells signature to enable downstream purification and analysis and improve current cell processing workflows.