Defect Characterization in 4H Silicon Carbide Bulk Crystals and Epilayers

4H silicon carbide (4H-SiC) has been accepted as an optimal semiconductor that can substitute for silicon for fabricating advanced power devices for high temperature, high power, and high frequency applications, owing to its outstanding properties such as wide bandgap, high breakdown electric field, high saturation drift velocity and high thermal conductivity. Developments in advanced growth techniques for both 4H-SiC bulk crystals and epilayers have led to an era of large wafer sizes and relatively low defect densities, and these achievements are partly attributed to extensive and careful studies of different kinds of defects in this material. In turn, high crystal quality provides a unique opportunity to better understand defects behavior and also discover any new types of defects. The central focus of this dissertation is to study the nature of various defects in 4H-SiC, determine their origins, and explain their formation mechanisms and the goal is to enlighten potential strategies to eventually eliminate these defects. Synchrotron x-ray topography, high resolution transmission electron microscopy, chemical etching and computer simulations have been intensively used in the studies. The outcomes can be divided into four parts: (I) Threading c+a dislocations have been recognized from those traditionally considered as threading screw dislocations, and their nucleation, propagation and mutual interactions have been studied; (II)The defect evolution process from threading dislocations with c-component of Burgers vector to stacking faults has been studied. Deflection of threading c+a dislocations was observed to be able to create stacking faults comprising mixtures of Shockley component and Frank component. Moreover, open-core threading screw dislocations, or micropipes, were found to be the source of stacking faults with a peculiar configuration of six-pointed star shape; (III) 2D nucleation mechanisms were provided to explain the formation of stacking faults with 6H structure in the substrate and the formation of so-called V-shaped defects in the epilayer; (IV) A new method has been developed to determine the faults vectors associated with stacking faults in 4H-SiC from their stacking sequences and meanwhile to provide possible pathways to transform the perfect stacking sequence to the faulted one. This technique is also expected to be applicable to all structures comprising corner shared tetrahedra, such as 2H, 3C, 6H, and 15R. | 126 page

Tracing Fasting Glucose Fluxes with Unstressed Catheter Approach in Streptozotocin Induced Diabetic Rats

Objective. Blood glucose concentrations of type 1 diabetic rats are vulnerable, especially to stress and trauma. The present study aimed to investigate the fasting endogenous glucose production and skeletal muscle glucose uptake of Streptozotocin induced type 1 diabetic rats using an unstressed vein and artery implantation of catheters at the tails of the rats as a platform. Research Design and Methods. Streptozotocin (65 mg·kg−1) was administered to induce type 1 diabetic state. The unstressed approach of catheters of vein and artery at the tails of the rats was established before the isotope tracer injection. Dynamic measurement of fasting endogenous glucose production was assessed by continuously infusing stable isotope [6, 6-2H2] glucose, while skeletal muscle glucose uptake by bolus injecting radioactively labeled [1-14C]-2-deoxy-glucose. Results. Streptozotocin induced type 1 diabetic rats displayed polydipsia, polyphagia, and polyuria along with overt hyperglycemia and hypoinsulinemia. They also had enhanced fasting endogenous glucose production and reduced glucose uptake in skeletal muscle compared to nondiabetic rats. Conclusions. The dual catheters implantation at the tails of the rats together with isotope tracers injection is a save time, unstressed, and feasible approach to explore the glucose metabolism in animal models in vivo

Application of the Improved Clustering Algorithm in Operating Room Nursing Recommendation under the Background of Medical Big Data

The nursing work in the operating room has the characteristics of long time, strong technicality, and heavy work, which have an important influence on the quality of the operation. Operating room nursing recommendations based on data mining technology can solve a series of practical problems in clinical nursing and nursing management. This paper selects the clustering algorithm in commonly used data mining technology as the research object and actually analyzes the impact of this algorithm in operating room nursing recommendations. At this stage, there is little research on data mining technology in the field of nursing in China. This paper aims to provide new ideas for the field of nursing research by exploring the actual application in the field of nursing.</jats:p

Grazing Incidence X-ray Topographic Studies of Threading Dislocations in Hydrothermal Grown ZnO Single Crystal Substrates

ABSTRACTZnO single crystal substrates grown by the hydrothermal method have been characterized by grazing incidence X-ray topography using both monochromaticand whitesynchrotron X ray beams.11$\bar 2$4 reflection wasrecorded from the (0001) wafers and the different contrast patterns produced by different threading defects were noted. To uniquely identify the Burgers vectors of these threading dislocation defects, we use raytracingsimulation to compare with observed defect contrast. Our studies showed that threading screw dislocations are not commonly observed.Most threading edge dislocationshavetheBurgers vector of1⁄3[2$\bar 1$$\bar 1$0] or1⁄3[12$\bar 2$10]and a density of 2.88×104/cm2.</jats:p

A Cooperative Optimization Algorithm Inspired by Chaos–Order Transition

The growing complexity of optimization problems in distributed systems (DSs) has motivated computer scientists to strive for efficient approaches. This paper presents a novel cooperative algorithm inspired by chaos–order transition in a chaotic ant swarm (CAS). This work analyzes the basic dynamic characteristics of a DS in light of a networked multiagent system at microlevel and models a mapping from state set to self-organization mechanism set under the guide of system theory at macrolevel. A collaborative optimization algorithm (COA) in DS based on the chaos–order transition of CAS is then devised. To verify the validity of the proposed model and algorithm, we solve a locality-based task allocation in a networked multiagent system that uses COA. Simulations show that our algorithm is feasible and effective compared with previous task allocation approaches, thereby illustrating that our design ideas are correct