919 resultados para CONSTRUCTIVE NANOLITHOGRAPHY
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Reed Smoot, chairman.
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Mode of access: Internet.
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Publication commenced with the 2nd annual debate, 1908/09.
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Mode of access: Internet.
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Title from cover.
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This thesis is an exploration of several completeness phenomena, both in the constructive and the classical settings. After some introductory chapters in the first part of the thesis where we outline the background used later on, the constructive part contains a categorical formulation of several constructive completeness theorems available in the literature, but presented here in an unified framework. We develop them within a constructive reverse mathematical viewpoint, highlighting the metatheory used in each case and the strength of the corresponding completeness theorems. The classical part of the thesis focuses on infinitary intuitionistic propositional and predicate logic. We consider a propositional axiomatic system with a special distributivity rule that is enough to prove a completeness theorem, and we introduce weakly compact cardinals as the adequate metatheoretical assumption for this development. Finally, we return to the categorical formulation focusing this time on infinitary first-order intuitionistic logic. We propose a first-order system with a special rule, transfinite transitivity, that embodies both distributivity as well as a form of dependent choice, and study the extent to which completeness theorems can be established. We prove completeness using a weakly compact cardinal, and, like in the constructive part, we study disjunction-free fragments as well. The assumption of weak compactness is shown to be essential for the completeness theorems to hold.
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Primary data obtained from unionized employees in Singapore were used to examine P. A. Bamberger, A. N. Kluger, and R. Suchard's (1999) integrative model of the antecedents and outcomes of union commitment. Structural equation modeling results revealed support for their integrative model. Specifically, the results revealed the influence of job satisfaction on union loyalty to be indirect through organizational commitment. However, the union-related antecedents (union socialization and union instrumentality) were both directly and indirectly related to union loyalty through pro-union attitudes. In addition, union loyalty was related to the individually and organizationally directed union citizenship behavior dimensions. Limitations of the study and implications of the findings are discussed.
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Using microarrays to probe protein-protein interactions is becoming increasingly attractive due to their compatibility with highly sensitive detection techniques, selectivity of interaction, robustness and capacity for examining multiple proteins simultaneously. The major drawback to using this approach is the relatively large volumes and high concentrations necessary. Reducing the protein array spot size should allow for smaller volumes and lower concentrations to be used as well as opening the way for combination with more sensitive detection technologies. Dip-Pen Nanolithography (DPN) is a recently developed technique for structure creation on the nano to microscale with the capacity to create biological architectures. Here we describe the creation of miniaturised microarrays, 'mesoarrays', using DPN with protein spots 400× smaller by area compared to conventional microarrays. The mesoarrays were then used to probe the ERK2-KSR binding event of the Ras/Raf/MEK/ERK signalling pathway at a physical scale below that previously reported. Whilst the overall assay efficiency was determined to be low, the mesoarrays could detect KSR binding to ERK2 repeatedly and with low non-specific binding. This study serves as a first step towards an approach that can be used for analysis of proteins at a concentration level comparable to that found in the cellular environment.
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Geometric information relating to most engineering products is available in the form of orthographic drawings or 2D data files. For many recent computer based applications, such as Computer Integrated Manufacturing (CIM), these data are required in the form of a sophisticated model based on Constructive Solid Geometry (CSG) concepts. A recent novel technique in this area transfers 2D engineering drawings directly into a 3D solid model called `the first approximation'. In many cases, however, this does not represent the real object. In this thesis, a new method is proposed and developed to enhance this model. This method uses the notion of expanding an object in terms of other solid objects, which are either primitive or first approximation models. To achieve this goal, in addition to the prepared subroutine to calculate the first approximation model of input data, two other wireframe models are found for extraction of sub-objects. One is the wireframe representation on input, and the other is the wireframe of the first approximation model. A new fast method is developed for the latter special case wireframe, which is named the `first approximation wireframe model'. This method avoids the use of a solid modeller. Detailed descriptions of algorithms and implementation procedures are given. In these techniques utilisation of dashed line information is also considered in improving the model. Different practical examples are given to illustrate the functioning of the program. Finally, a recursive method is employed to automatically modify the output model towards the real object. Some suggestions for further work are made to increase the domain of objects covered, and provide a commercially usable package. It is concluded that the current method promises the production of accurate models for a large class of objects.
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There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture.The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability.
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A generalization of the Gram-Schmidt procedure is achieved by providing equations for updating and downdating oblique projectors. The work is motivated by the problem of adaptive signal representation outside the orthogonal basis setting. The proposed techniques are shown to be relevant to the problem of discriminating signals produced by different phenomena when the order of the signal model needs to be adjusted. © 2007 IOP Publishing Ltd.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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We report the results of a study into the quality of functionalized surfaces for nanolithographic imaging. Self-assembled monolayer (SAM) coverage, subsequent post-etch pattern definition and minimum feature size all depend on the quality of the Au substrate used in atomic nanolithographic experiments. We find sputtered Au substrates yield much smoother surfaces and a higher density of {111} oriented grains than evaporated Au surfaces. A detailed study of the self-assembly mechanism using molecular resolution AFM and STM has shown that the monolayer is composed of domains with sizes typically of 5-25 nm, and multiple molecular domains can exist within one Au grain. Exposure of the SAM to an optically-cooled atomic Cs beam traversing a two-dimensional array of submicron material masks ans also standing wave optical masks allowed determination of the minimum average Cs dose (2 Cs atoms per SAM molecule) and the realization of < 50 nm structures. The SAM monolayer contains many non-uniformities such as pin-holes, domain boundaries and monoatomic depressions which are present in the Au surface prior to SAM adsorption. These imperfections limit the use of alkanethiols as a resist in atomic nanolithography experiments. These studies have allowed us to realize an Atom Pencil suitable for deposition of precision quantities of material at the microand nanoscale to an active surface.
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Cs atom beams, transversely collimated and cooled, passing through material masks in the form of arrays of reactive-ion-etched hollow Si pyramidal tips and optical masks formed by intense standing light waves, write submicron features on self-assembled monolayers (SAMs). Features with widths as narrow as 43 ± 6 nm and spatial resolution limited only by the grain boundaries of the substrate have been realized in SAMs of alkanethiols. The material masks write two-dimensional arrays of submicron holes; the optical masks result in parallel lines spaced by half the optical wavelength. Both types of feature are written to the substrate by exposure of the masked SAM to the Cs flux and a subsequent wet chemical etch. For the arrays of pyramidal tips, acting as passive shadow masks, the resolution and size of the resultant feature depends on the distance of the mask array from the SAM, an effect caused by the residual divergence of the Cs atom beam. The standing wave optical mask acts as an array of microlenses focusing the atom flux onto the substrate. Atom 'pencils' writing on SAMs have the potential to create arbitrary submicron figures in massively parallel arrays. The smallest features and highest resolutions were realized with SAMs grown on smooth, sputtered gold substrates.
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We report the results of a study into the factors controlling the quality of nanolithographic imaging. Self-assembled monolayer (SAM) coverage, subsequent postetch pattern definition, and minimum feature size all depend on the quality of the Au substrate used in material mask atomic nanolithographic experiments. We find that sputtered Au substrates yield much smoother surfaces and a higher density of {111}-oriented grains than evaporated Au surfaces. Phase imaging with an atomic force microscope shows that the quality and percentage coverage of SAM adsorption are much greater for sputtered Au surfaces. Exposure of the self-assembled monolayer to an optically cooled atomic Cs beam traversing a two-dimensional array of submicron material masks mounted a few microns above the self-assembled monolayer surface allowed determination of the minimum average Cs dose (2 Cs atoms per self-assembled monolayer molecule) to write the monolayer. Suitable wet etching, with etch rates of 2.2 nm min-1, results in optimized pattern definition. Utilizing these optimizations, material mask features as small as 230 nm in diameter with a fractional depth gradient of 0.820 nm were realized.