Faculty Advisor or Committee Member

Susan Zhou, Advisor

Faculty Advisor or Committee Member

Cosme Furlong-Vazquez, Committee Member

Faculty Advisor or Committee Member

Nickolas Kazantzis, Committee Member

Identifier

etd-052012-230237

Abstract

Magnetic nanoparticle (MNP) combined with biomolecules in a microfluidic system can be efficiently used in various applications such as mixing, pre-concentration, separation and detection. They can be either integrated for point-of care applications or used individually in the area of bio-defense, drug delivery, medical diagnostics, and pharmaceutical development. The interaction of magnetic fields with magnetic nanoparticles in microfluidic flows will allow simplifying the complexity of the present generation separation and detection systems. The ability to understand the dynamics of these interactions is a prerequisite for designing and developing more efficient systems. Therefore, in this work proof-of-concept experiments are combined with advanced numerical simulation to design, develop and optimize the magnetic microfluidic systems for mixing, separation and detection. Different strategies to combine magnetism with microfluidic technology are explored; a time-dependent magnetic actuation is used for efficiently mixing low volume of samples whereas tangential microfluidic channels were fabricated to demonstrate a simple low cost magnetic switching for continuous separation of biomolecules. A simple low cost generic microfluidic platform is developed using assembly of readily available permanent magnets and electromagnets. Microfluidic channels were fabricated at much lower cost and with a faster construction time using our in-house developed micromolding technique that does not require a clean room. Residence-time distribution (RTD) analysis obtained using dynamic light scattering data from samples was successfully used for the first time in microfluidic system to characterize the performance. Both advanced multiphysics finite element models and proof of concept experimentation demonstrates that MNPs when tagged with biomolecules can be easily manipulated within the microchannel. They can be precisely captured, separated or detected with high efficiency and ease of operation. Presence of MNPs together with time-dependent magnetic actuation also helps in mixing as well as tagging biomolecules on chip, which is useful for point-of-care applications. The advanced mathematical model that takes into account mass and momentum transport, convection & diffusion, magnetic body forces acting on magnetic nanoparticles further demonstrates that the performance of microfluidic surface-based bio-assay can be increased by incorporating the idea of magnetic actuation. The numerical simulations were helpful in testing and optimizing key design parameters and demonstrated that fluid flow rate, magnetic field strength, and magnetic nanoparticle size had dramatic impact on the performance of microfluidic systems studied. This work will also emphasize the importance of considering magnetic nanoparticles interactions for a complete design of magnetic nanoparticle-based Lab-on-a-chip system where all the laboratory unit operations can be easily integrated. The strategy demonstrated in this work will not only be easy to implement but also allows for versatile biochip design rules and provides a simple approach to integrate external elements for enhancing mixing, separation and detection of biomolecules. The vast applications of this novel concept studied in this work demonstrate its potential of to be applied to other kinds of on-chip immunoassays in future. We think that the possibility of integrating magnetism with microfluidic-based bioassay on a disposable chip is a very promising and versatile approach for point-of care diagnostics especially in resource-limited settings.

Publisher

Worcester Polytechnic Institute

Degree Name

PhD

Department

Chemical Engineering

Project Type

Dissertation

Date Accepted

2012-05-20

Accessibility

Unrestricted

Subjects

Microfluidics, Lab-on-a-chip, Mathematical Modeling, Nanoparticles, Magnetism

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