Design and Implementation of Position-Encoded Microfluidic Microsphere-Trap Arrays

Microarray devices are useful for detecting and analyzing biological targets, such as DNAs, mRNAs, proteins, etc. Applications of microarrays range from fundamental research to clinical diagnostics and drug discovery. In this dissertation, we consider a microsphere array device with predetermined positions of the microspheres. The microspheres are conjugate on their surfaces with molecular probes to capture the targets, and the targets are identified by the microspheres\u27 positions. We implement the microsphere arrays by employing microfluidic technology and a hydrodynamic trapping mechanism. We call our device microfluidic microsphere-trap arrays. To fully realize the potential of the device in biomedical applications, we utilize statistical performance analysis, mathematical optimization, and finite element fluid dynamics simulations to optimize device design, fabrication, and implementation. Our device is promising as a cost-effective and point-of-care lab-on-a-chip system. We first analyze the statistical performance of position-encoded microsphere arrays in imaging biological targets at different signal-to-noise ratio (SNR) levels. We compute the Ziv-Zakai bound (ZZB) on the errors in estimating the unknown parameters, including the target concentrations. Through numerical examples, we find the SNR level below which the ZZB provides a more accurate prediction of the error than the posterior Cramer-Rao bound (PCRB) does. We further apply the ZZB to select the optimal design parameters, such as the distance between the microspheres, and to investigate the effects of the experimental variables such as the microscope point-spread function. We implement the arrays by using microfluidic technology and hydrodynamic trapping. We design a novel geometric structure for the device, and develop a comprehensive and robust framework to optimize its geometric parameters that maximize the microsphere arrays\u27 packing density. We also simultaneously optimize multiple criteria, such as high microsphere trapping efficiency and low fluidic and imaging errors. Microsphere-trapping experiments performed using the optimized device and an un-optimized device demonstrate easy control of the microspheres\u27 transportation and manipulation in the optimized device. They also show that the optimized device greatly outperforms the un-optimized one. We extend our optimization framework to build a device that enables simultaneous, efficient, and accurate screening of multiple targets in a single microfluidic channel, by immobilizing different-sized microspheres at different regions. Different biomolecules captured on the surfaces of the different-sized microspheres can thus be detected simultaneously by the microspheres\u27 positions. We employ finite element fluid dynamics simulations to investigate hydrodynamic trapping of microspheres, and to study the effects of the geometric parameters and critical fluid velocity. The accuracy of the time-dependent simulations is validated by experimental results. The simulations guide the device design and experimental operation. The guidelines on the simulation set-up and the openly available model will help researchers apply the simulation to similar microfluidic systems that may accommodate a variety of structured particles