Microfluidic fabrication of advanced microcapsules for use in self-healing materials

The proposed work aims to facilitate the development of a microfluidic platform for the production of advanced microcapsules containing active agents which can be the functional constituents of self-healing composites. The creation of such microcapsules is enabled by the unique flow characteristics within microchannels including precise control over shear and interfacial forces for droplet creation and manipulation as well as the ability to form a solid shell either chemically or via the addition of thermal or irradiative energy. Microchannel design and a study of the fluid dynamics and mechanisms for shell creation are undertaken in order to establish a fabrication approach capable of producing healing-agent-containing microcapsules. An in-depth study of the process parameters has been undertaken in order to elucidate the advantages of this production technique including precise control of size (i.e., monodispersity) and surface morphology of the microcapsules. This project also aims to aid the optimization of the mechanical properties as well as healing performance of self-healing composites by studying the effects of the advantageous properties of the as-produced microcapsules. Scale-up of the microfluidic fabrication using parallel devices on a single chip as well as on-chip microcapsule production and shape control will also be investigated. It will be demonstrated that microfluidic fabrication is a versatile approach for the efficient creation of functional microcapsules allowing for superior design of self-healing composites.

Integration of room temperature single electron transistor with CMOS subsystem

The single electron transistor (SET) is a charge-based device that may complement the dominant metal-oxide-semiconductor field effect transistor (MOSFET) technology. As the cost of scaling MOSFET to smaller dimensions are rising and the the basic functionality of MOSFET is encountering numerous challenges at dimensions smaller than 10nm, the SET has shown the potential to become the next generation device which operates based on the tunneling of electrons. Since the electron transfer mechanism of a SET device is based on the non-dissipative electron tunneling effect, the power consumption of a SET device is extremely low, estimated to be on the order of 10^-18J. The objectives of this research are to demonstrate technologies that would enable the mass produce of SET devices that are operational at room temperature and to integrate these devices on top of an active complementary-MOSFET (CMOS) substrate. To achieve these goals, two fabrication techniques are considered in this work. The Focus Ion Beam (FIB) technique is used to fabricate the islands and the tunnel junctions of the SET device. A Ultra-Violet (UV) light based Nano-Imprint Lithography (NIL) call Step-and-Flash- Imprint Lithography (SFIL) is used to fabricate the interconnections of the SET devices. Combining these two techniques, a full array of SET devices are fabricated on a planar substrate. Test and characterization of the SET devices has shown consistent Coulomb blockade effect, an important single electron characteristic. To realize a room temperature operational SET device that function as a logic device to work along CMOS, it is important to know the device behavior at different temperatures. Based on the theory developed for a single island SET device, a thermal analysis is carried out on the multi-island SET device and the observation of changes in Coulomb blockade effect is presented. The results show that the multi-island SET device operation highly depends on temperature. The important parameters that determine the SET operation is the effective capacitance Ceff and tunneling resistance Rt . These two parameters lead to the tunneling rate of an electron in the SET device, Γ. To obtain an accurate model for SET operation, the effects of the deviation in dimensions, the trap states in the insulation, and the background charge effect have to be taken into consideration. The theoretical and experimental evidence for these non-ideal effects are presented in this work.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

EFFECTS OF ION LIMITING CONDITIONS ON THE BEHAVIOR OF MICROFLUIDIC DEVICES

Finite numbers of ions are present in microfluidic devices. This leads to ion limiting effects in microfluidic channels and electrode surfaces. These effects include electrode surface changes and ion concentration gradient formation across microfluidic channels, and can influence microfluidic device behavior. A literature survey on the use of electrochemical analysis techniques in micro- and nanofluidic devices was carried out, which puts into perspective the importance of electrode surface changes with regards to analytical microfluidic applications. Surface changes in Pt wire electrodes under various physiological buffer and electric field conditions were investigated using cyclic voltammetry (CV), SEM-EDS and XPS. Effects of surface changes on electrochemical analysis performance of Pt wire and thin film electrodes were investigated. Electrode surfaces were subjected to varying phosphate buffer and electric field conditions, and their CV performance was monitored. Electrode surfaces were also studied with SEM-EDS. Two studies of ion concentration gradient formation in microfluidic channels were conducted. In the first, concentration gradients of H+ and OH- ions generated on electrode surfaces were found to cause significant pH decreases in certain buffer and electric field conditions, which was also found to play a key role in iDEP manipulation of proteins. The role of electrode surface reactions in this case shows the importance of understanding electrode surface changes in microfluidic devices. In the second study of ion concentration gradient formation, Cl- ion concentration gradient formation was attempted to be quantified upon electric field application across a KCl solution. Electrokinetic transport of the Cl- indicating fluorophore MQAE contributed significantly to the fluorescence microscopy signals collected, complicating Cl- quantification as a function of position and time. It was shown that a dielectric coating on electrode surfaces is effective at preventing MQAE electrokinetic transport.

On-chip Non-reciprocal Optical Devices Based on Quantum Inspired Photonic Lattices

We propose integrated optical structures that can be used as isolators and polarization splitters based on engineered photonic lattices. Starting from optical waveguide arrays that mimic Fock space (quantum state with a well-defined particle number) representation of a non-interacting two-site Bose Hubbard Hamiltonian, we show that introducing magneto-optic nonreciprocity to these structures leads to a superior optical isolation performance. In the forward propagation direction, an input TM polarized beam experiences a perfect state transfer between the input and output waveguide channels while surface Bloch oscillations block the backward transmission between the same ports. Our analysis indicates a large isolation ratio of 75 dB after a propagation distance of 8mm inside seven coupled waveguides. Moreover, we demonstrate that, a judicious choice of the nonreciprocity in this same geometry can lead to perfect polarization splitting.