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Background. Alcohol-use is an identifiable and preventable risk factor among women seeking to become pregnant. Maternal alcohol-use during pregnancy may be related to congenital cardiac defects, one of the leading types of birth defects. Methods. This study used data from the Pregnancy Risk Assessment Monitoring Surveillance (PRAMS), an ongoing national study administered in selected participating states. Alcohol use and other risk factors were obtained from the PRAMS survey linked to birth defects data from birth certificates in 9 participating states over a ten year period (1996-2005). In this study cases included infants born with a congenital cardiac defect as indicated on the birth certificate. Cases were compared to two control groups. One control group consisted of infants with no indication of a congenital abnormality on their birth certificate. A second control group consisted of infants born with Down's syndrome indicated on their birth certificate. Odds ratios for congenital cardiac defects were computed for maternal alcohol use, frequent drinking, binge drinking and continued drinking through logistic regression. Results. Differences were found in the odds of congenital cardiac defects among mothers who reported binge drinking on more than once occasion in the 3 months prior to pregnancy. Maternal binge drinking on multiple occasions was found to be a risk factor for congenital cardiac defects (OR 2.99; CI 1.19-7.51) when nonaffected controls were used as a reference group. Significant interaction between binge drinking and smoking in the 3 months prior to pregnancy was noted with both control groups. Conclusion. Binge drinking in early pregnancy may be a risk factor for congenital cardiac defects, particularly when combined with smoking. / Public Health

The research performed aims to develop a deeper understanding and prediction of behaviour of complex chemical and physical systems using density functional theory (DFT) modelling complemented by experimental techniques. We focus on phenomena relevant to practical applications of semiconducting materials. Semiconductor nanowires, produced by the vapor-liquid-solid method are being considered for applications in photo sensors, field effect transistors, light emitting diodes (LEDs) and energy harvesting devices. In particular, semiconductor nanowire based photovoltaic devices show potential for lower cost due to less material utilization and greater energy conversion efficiency arising from enhanced photovoltage or photocurrent due to hot carrier or multiexciton phenomena enhanced light absorption, compared to conventional thin film devices. Further, freedom from lattice matching requirements due to strain accommodation at the nanowire surfaces enable compatibility with a wide variety of substrates including Silicon. Thus understanding and improving the optoelectronic properties of nanowires is of great interest. In the first paper, we study the effect of planar defects on optoelectronic properties of nanowire based semiconductor devices. Specifically, we were interested in investing the origin of various features observed in the photoluminisence (PL) spectrum of GaP nanowire using density functional modelling, which are not well understood. In the second paper, we work to model bonding characteristics during a chemical synthesis. We focus on the synthesis of nanoparticles for supercapacitor application. In the past decade, comprehensive research has been emphasized on manganese oxides for electrochemical supercapacitor (ECS) applications. Mn3O4 has gained significant interest due to its compatibility with capping agents and the unique spinel structure allows for potential modifications with other cations. Many metal oxide synthesis techniques are based on aqueous processing. The synthesized particles are usually dried and redispersed in organic solvents to incorporate water-insoluble additives such as binders to fabricate films and devices. However, during the drying step nano-structures are highly susceptible to agglomeration, which can be attributed to the condensation reactions occurring between particles and reduction in surface energy. Poor electrolyte access due to agglomeration and low intrinsic conductivity of Mn3O4 are detrimental to the performance of Mn 3O4 electrode especially at high active mass loadings. Numerous attempts have focused on controlling size and morphology of Mn3O4 nanostructures using capping agents, which have strong adhesion to particles surface to inhibit agglomeration. Catechol containing molecules have been used for dispersion of metallic nanoparticles and fabrication of composite thin films, resulted in narrow size distribution of nanoparticles and strong adhesion to substrates. Despite the experimental results showing good adsorption of catechol group to metal atoms, the mechanism is unclear since it is highly influenced by synthesis parameters. We use Infrared spectroscopy in conjugation with density functional modelling to understand the binding mechanism of 3,4 dihydroxy benzaldehyde onto Mn3O4 surface. / Thesis / Master of Applied Science (MASc)

As complementary metal-oxide semiconductor (CMOS) technology faces more and more severe physical barriers down the path of continuously feature size scaling, innovative nano-scale devices and other post-CMOS technologies have been developed to enhance future circuit design and computation. These nanotechnologies have shown promising potentials to achieve magnitude improvement in performance and integration density. The substitution of CMOS transistors with nano-devices is expected to not only continue along the exponential projection of Moore's Law, but also raise significant challenges and opportunities, especially in the field of electronic design automation. The major obstacles that the designers are experiencing with emerging nanotechnology design include: i) the existing computer-aided design (CAD) approaches in the context of conventional CMOS Boolean design cannot be directly employed in the nanoelectronic design process, because the intrinsic electrical characteristics of many nano-devices are not best suited for Boolean implementations but demonstrate strong capability for implementing non-conventional logic such as threshold logic and reversible logic; ii) due to the density and size factors of nano-devices, the defect rate of nanoelectronic system is much higher than conventional CMOS systems, therefore existing design paradigms cannot guarantee design quality and lead to even worse result in high failure ratio. Motivated by the compelling potentials and design challenges of emerging post-CMOS technologies, this dissertation work focuses on fundamental design methodologies to effectively and efficiently achieve high quality nanoscale design. A novel programmable logic element (PLE) is first proposed to explore the versatile functionalities of threshold gates (TGs) and multi-threshold threshold gates (MTTGs). This PLE structure can realize all three- or four-variable logic functions through configuring binary control bits. This is the first single threshold logic structure that provides complete Boolean logic implementation. Based on the PLEs, a reconfigurable architecture is constructed to offer dynamic reconfigurability with little or no reconfiguration overhead, due to the intrinsic self-latching property of nanopipelining. Our reconfiguration data generation algorithm can further reduce the reconfiguration cost. To fully take advantage of such threshold logic design using emerging nanotechnologies, we also developed a combinational equivalence checking (CEC) framework for threshold logic design. Based on the features of threshold logic gates and circuits, different techniques of formulating a given threshold logic in conjunctive normal form (CNF) are introduced to facilitate efficient SAT-based verification. Evaluated with mainstream benchmarks, our hybrid algorithm, which takes into account both input symmetry and input weight order of threshold gates, can efficiently generate CNF formulas in terms of both SAT solving time and CNF generating time. Then the reversible logic synthesis problem is considered as we focus on efficient synthesis heuristics which can provide high quality synthesis results within a reasonable computation time. We have developed a weighted directed graph model for function representation and complexity measurement. An atomic transformation is constructed to associate the function complexity variation with reversible gates. The efficiency of our heuristic lies in maximally decreasing the function complexity during synthesis steps as well as the capability to climb out of local optimums. Thereafter, swarm intelligence, one of the machine learning techniques is employed in the space searching for reversible logic synthesis, which achieves further performance improvement. To tackle the high defect-rate during the emerging nanotechnology manufacturing process, we have developed a novel defect-aware logic mapping framework for nanowire-based PLA architecture via Boolean satisfiability (SAT). The PLA defects of various types are formulated as covering and closure constraints. The defect-aware logic mapping is then solved efficiently by using available SAT solvers. This approach can generate valid logic mapping with a defect rate as high as 20%. The proposed method is universally suitable for various nanoscale PLAs, including AND/OR, NOR/NOR structures, etc. In summary, this work provides some initial attempts to address two major problems confronting future nanoelectronic system designs: the development of electronic design automation tools and the reliability issues. However, there are still a lot of challenging open questions remain in this emerging and promising area. We hope our work can lay down stepstones on nano-scale circuit design optimization through exploiting the distinctive characteristics of emerging nanotechnologies. / Ph. D.

In comparison with Si-based converters, the emerging Medium Voltage (MV) SiC-based converters can achieve higher blocking voltage capability, lower on-resistance, faster switching speed with less switching related losses and run under higher temperature. Thus, theoretically, it can achieve much higher power density, which becomes very promising for future power transmission and distribution. However, in order to achieve the desired high power density, insulation system of the MV SiC-based converter must be compact. Therefore, challenges for the insulation system gradually appeared, as the insulation size becomes smaller and the Electric field (E-field) intensity significantly increases. Under such high E-field intensity, it is necessary and important to eliminate Partial Discharge (PD) for such power converters, since the converter system is vulnerable to PDs. Developing an insulation design, assessment and online monitoring method to help reach a compact and PD free insulation system for MV SiC-based converters is a goal of this work. General insulation design and assessment guidelines based on experimental PD investigation and physics-based model –Experimental PD investigation is completed for internal void discharge, surface discharge, and point discharge representative coupons under square excitations. Based on the data and the existing knowledge about PD mechanisms, widely accepted PD models are selected. Using these physics-based models, simulation results can demonstrate the major features observed in the experiments. With the experimental data and valid PD models, several general insulation design and assessment guidelines are proposed, which could be further applied during converter prototypes development. Partial Discharge elimination methodology and design examples – By using the laminated bus as the design example, internal void evaluation and analysis method is demonstrated. Then, targeting the internal PD-free design with reasonable insulation thickness, several insulation improvement methods are applied and experimentally verified by using representative coupons. After understanding the possible ways for evaluating and eliminating internal voids, a PCB-based planar bus is designed and fabricated, which shows great insulation improvement after experimental verification. In order to eliminate PDs in the air and shrink the insulation distance, three ways for managing E-field distribution in air are demonstrated by three examples. First, by using the interconnections among the power modules, Rogowski-based current-sensing board, and the laminated bus as an example, E-field distribution can be estimated by Finite Element Analysis (FEA) and its management can be achieved by geometrical modifications. Second, for the one-turn inductor, a methodology is demonstrated that builds a coaxial insulation structure with proper termination technology in order to squeeze air out of the insulation system. Finally, E-field shielding technology is applied along the heatsink edges in order to make the E-field distribution uniform and to shrink the insulation distance between the heatsink and the cooling system. After improving the insulation, this work shrinks the converter unit size by around 50% while maintaining its PD-free status under normal operation conditions. Besides the significant increase in power density and weight reduction, the entire converter system has less ringing and better current-sharing performance due to reductions of the parasitic inductance. Partial Discharge online monitoring via acoustic and photon detection methods –Targeting the online monitoring and even localization of surface discharge for power converter applications, two novel types of sensors have been proposed and fabricated. In order to verify the concepts, one example with experimental results has been given for each type of sensor. The experimental data demonstrates that such sensors can be placed inside the converter and online monitoring can be realized for surface or corona discharges by capturing either the acoustic signal or the photons that are generated by discharge events. / Doctor of Philosophy / A unproper designed insulation system can take more than 50% volume of Medium Voltage (MV) SiC-based converters and have significant internal or external Partial Discharge (PD), which can not only accelerate the insulation aging but also risk to multiple aspects of the converter system. Therefore, developing an insulation design, assessment and online monitoring method to help reach a compact and PD free insulation system for MV SiC-based converters is a goal of this work. Experimental PD investigation is completed for internal void discharge, surface discharge, and point discharge representative coupons under square excitations. Several general insulation design and assessment guidelines are proposed based on the experimental PD investigation and physics-based explanations, which are further applied during converter prototypes development. Then, PD elimination methodology is developed and demonstrated by design examples. By using the laminated bus as an example, internal void evaluation and analysis method is demonstrated. Then, targeting the internal PD-free design with reasonable insulation thickness, several insulation improvement methods are applied and experimentally verified by using representative coupons. In order to eliminate PDs in air and shrink the insulation distance, three ways for managing E-field distribution in air are demonstrated by three examples. First, by using the interconnections among the power modules, Rogowski-based current-sensing board, and the laminated bus as an example, E-field distribution can be estimated by Finite Element Analysis (FEA) and its management can be achieved by geometrical modifications. Second, for the one-turn inductor, a coaxial insulation structure with proper termination technology in order to squeeze air out of the insulation system is demonstrated. Finally, E-field shielding technology is applied along the heatsink edges in order to make the E-field distribution uniform and to shrink the insulation distance between the heatsink and the cooling system. After improving the insulation, this work shrinks the converter unit size by around 50% while maintaining its PD-free status under normal operation conditions. Besides the significant increase in power density and weight reduction, the entire converter system has less ringing and better current-sharing performance due to reductions of the parasitic inductance. Targeting the PD online monitoring for power converter applications, two novel types of sensors have been proposed and fabricated. In order to verify the concepts, one example with experimental results has been given for each type of sensor. The experimental data demonstrates that such sensors can be placed inside the converter and online monitoring can be realized for surface or corona discharges by capturing either the acoustic signal or the photons that are generated by discharge events.

Early detection of rail defects is necessary for preventing derailments and costly damage to the train and railway infrastructure. A rail surface flaw can quickly propagate from a small fracture to a broken rail after only a few train cars have passed over it. Rail defect detection is typically performed by using an instrumented car or a separate railway monitoring vehicle. Rail surface irregularities can be measured using accelerometers mounted to the bogie side frames or wheel axles. Typical signal processing algorithms for detecting defects within a vertical acceleration signal use a simple thresholding routine that considers only the amplitude of the signal. As a result, rail surface defects that produce low amplitude acceleration signatures may not be detected, and special track components that produce high amplitude acceleration signatures may be flagged as defects. The focus of this research is to develop an intelligent signal processing algorithm capable of detecting and classifying various rail surface irregularities, including defects and special track components. Three algorithms are proposed and validated using data collected from an instrumented freight car. For the first two algorithms, one uses a windowed Fourier Transform while the other uses the Wavelet Transform for feature extraction. Both of these algorithms use an artificial neural network for feature classification. The third algorithm uses the Wavelet Transform to perform a regularity analysis on the signal. The algorithms are validated with the collected data and shown to out-perform the threshold-based algorithm for the same data set. Proper training of the defect detection algorithm requires a large data set consisting of operating conditions and physical parameters. To generate this training data, a dynamic wheel-rail interaction model was developed that relates defect geometry to the side frame vertical acceleration signature. The model was generated by using combined systems dynamic modeling, and the system was solved with a developed combined lumped and distributed parameter system numerical approximation. The broken rail model was validated with real data collected from an instrumented freight car. The model was then used to train and validate the defect detection methodologies for various train and rail physical parameters and operating conditions. / Ph. D.

Optical three dimensional (3D) mapping routines are used in inspection robots to detect faults by creating 3D reconstructions of environments. To detect surface faults, sub millimeter depth resolution is required to determine minute differences caused by coating loss and pitting. Sensors that can detect these small depth differences cannot quickly create contextual maps of large environments. To solve the 3D mapping problem, a sensor fused approach is proposed that can gather contextual information about large environments with one depth sensor and a SLAM routine; while local surface defects can be measured with an actuated optical profilometer. The depth sensor uses a modified Kinect Fusion to create a contextual map of the environment. A custom actuated optical profilometer is created and then calibrated. The two systems are then registered to each other to place local surface scans from the profilometer into a scene context created by Kinect Fusion. The resulting system can create a contextual map of large scale features (0.4 m) with less than 10% error while the optical profilometer can create surface reconstructions with sub millimeter resolution. The combination of the two allows for the detection and quantification of surface faults with the profilometer placed in a contextual reconstruction. / Master of Science

Cerium oxide nanoparticles have the unique ability to accept and donate electrons, making them powerful antioxidants. Their redox nature is due to oxygen defects in the lattice structure, which are more abundant at the nanoscale. Reactive oxygen species (ROS) are pro-oxidants whose presence is increased during periods of inflammation in the body. ROS damage tissues and cellular function by stripping electrons from proteins, lipids, and DNA. We investigated the ability of nanoceria to quench ROS in vitro and in vivo, and examined the biodistribution and biocompatibility of nanoceria in murine models. Nanoceria was internalized in vitro by macrophages, is non-toxic at the concentrations we investigated, and proteins, mRNA, and oxidative markers of ROS were abated with nanoceria pretreatment in immune stimulated cells as measured by western blot, real time RT PCR, and Greiss assay respectively. In vivo, nanoceria was deposited in the spleen and liver, with trace amounts in the lungs and kidneys as determined by ICP-MS. Using IVIS in vivo imaging, it appeared that nanoceria deposition occurred in lymph tissue. Histology grades show no overt pathology associated with nanoceria deposition, although white blood cell (WBC) counts were generally elevated with nanoceria treatment. Nanoceria suspect particles were seen in lysosomes from kidney samples of IV injected mice in HRTEM images. Lastly, IV nanoceria treatment appears to reduce markers of oxidative stress in mice treated with carbon tetrachloride (CCl4) to induce ROS production. Taken together, our data suggest that nanoceria treatment has the potential to reduce oxidative stress. / Master of Science