Control of Large-size SiC Growth Process Using Modeling tool

Large size bulk silicon carbide (SiC) crystals are commonly grown by the physical vapor transport (PVT) method. The PVT growth of SiC crystals involves sublimation and condensation, chemical reactions, stoichiometry, mass transport, induced thermal stress, as well as defect and micropipes generation and propagation. The quality and polytype of as-grown SiC crystals are related to the temperature distribution inside the growth chamber during the growth process, it is critical to predict the temperature distribution from the measured temperatures outside the crucible by pyrometers. A radio-frequency induction-heating furnace was used for the growth of large-size SiC crystals by the PVT method in the present study. Modeling and simulation have been used to develop the SiC growth process and to improve the SiC crystal quality. Parameters such as the temperature measured at the top of crucible, temperature measured at the bottom of the crucible, and inert gas pressure are used to control the SiC growth process. By measuring the temperatures at the top and bottom of the crucible, the temperatures inside the crucible were predicted with the help of modeling tool. SiC crystals of 6H polytype were obtained and characterized by the Raman scattering spectroscopy and SEM, and crystals of few millimeter size grown inside the crucible were found without micropipes. Expansion of the crystals were also performed with the help of modeling and simulation.

获取无意识结构知识的机制:主观熟悉感与刺激重复结构在人工语法学习中的作用

The nature of the distinction between conscious and unconscious knowledge is a core issue in the implicit learning field. Furthermore, the phenomenological experience associated with having knowledge is central to the conscious or unconscious status of that knowledge. Consistently, Dienes and Scott (2005) measured the conscious or unconscious status of structure knowledge using subjective measures. Believing that one is purely guessing when in fact one knows indicates unconscious knowledge. But unconscious structural knowledge can also be associated with feelings of intuition or familiarity. In this thesis, we explored whether phenomenological feelings, like familiarity, associated with unconscious structural knowledge could be used, paradoxically, to exert conscious control over the use of the knowledge, and whether people could obtain repetition structure knowledge. We also investigated the neural correlates of awareness of knowing, as measured phenomenologically. In study one, subjects were trained on two grammars and then asked to endorse strings from only one of the grammars. Subjects also rated how familiar each string they felt and reported whether or not they used familiarity to make their grammaticality judgment. We found subjects could endorse the strings of just one grammar and ignore the strings from the other. Importantly, when subjects said they were using familiarity, the rated familiarity for test strings consistent with their chosen grammar was greater than that for strings from the other grammar. Familiarity, subjectively defined, is sensitive to intentions and can play a key role in strategic control. In study two, we manipulated the structural characteristic of stings and explored whether participants could learn repetition structures in the grammatical strings. We measured phenomenology again and also ERPs. Deviant letters of ungrammatical strings violating the repetition structure elicited the N2 component; we took this to be an indication of knowledge, whether conscious or not. Strings which were attributed to conscious categories (rules and recollection) rather than phenomenology associated with unconscious structural knowledge (guessing, intuition and familiarity) elicited the P300 component. Different waveforms provided evidence for the neural correlates of different phenomenologies associated with knowledge of an artificial grammar.

Efficiently producing single-walled carbon nanotube rings and investigation of their field emission properties

Single-walled carbon nanotube (SWNT) rings with a diameter of about 100 nm have been prepared by thermally decomposing hydrocarbon in a floating catalyst system. These rings appeared to consist mostly of SWNT toroids. High resolution transmission electron microscopy showed that these rings were composed of tens of SWNTs with a tightly packed arrangement. The production of SWNT rings was improved through optimizing various growth parameters, such as growth temperature, sublimation temperature of the catalyst, different gas flows and different catalyst components. The growth mechanism of the SWNT rings is discussed. In the field emission measurements we found that field emission from a halved ring is better than that from a whole SWNT ring, which contributed to the better emission from two opened ends of the nanotubes of the halved SWNT ring.

PHYSICAL VAPOR TRANSPORT AND CRYSTAL-GROWTH OF GESEXTE1-X SOLID-SOLUTIONS

Physical vapor transport studies of GeSe(x)Te1 - x (x = 0.1, 0.2, 0.3, and 0.4) solid solutions demonstrated, that individual, large single crystals of these materials can be grown in closed ampoules. A compositional analysis of the grown crystals revealed, that the mass transport (crystal growth) process under steady-state conditions is pseudo-congruent and controlled by diffusion processes in the source material. From these experiments, the degree of non-stoichiometry (Ge-vacancy concentrations) of GeSe(x)Te1 - x single crystals could be estimated. The effects of the cubic to rhombohedral phase transformation during cooling on the microstructure and morphology of the grown mixed crystals are observed. This work provides the basis for subsequent defect studies and electrical measurements on these crystals.