943 resultados para Self-etching adhesive systems


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Chemistry occupies a unique middle position in the scientific arena, between physics and mathematics on the one side and biology, ecology, sociology and economics on the other [1]. Chemistry is the science of matter and of its transformations, and life is its highest expression [2]. According to reductionist thinking biology is reducible into chemistry, chemistry into physics, and ultimately physics into mathematics. Reductionism implies the ease of understanding one level in terms of another.The work presented this thesis comprises synthesis and characterization of suitably substituted thiocarbohydrazone and carbohydrazone ligand building blocks, self-assembled metallosupramolecular square grid complexes as well as some di/multinuclear complexes. The primary aim was the deliberate syntheses of some novel transition metal framework complexes, mainly metallosupramolecular coordination square grids by self-assembly and their physico-chemical characterization. The work presented, however, also include synthesis and characterization of four mononuclear Ni(II) complexes of two thiosemicarbazones, which we carried out as a preliminary and supporting study. Based on the present work we would like to conclude that the carbohydrazones, thiocarbohydrazones and their coordination framework complexes of transition metals are promising systems for wide application in science and technology varied from physics to biotechnology. Novel classes of materials and biologically important potential compounds open up further scope of researches and we hopefully welcome any sort of related research to make this work more valuable.

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A density-functional self-consistent calculation of the ground-state electronic density of quantum dots under an arbitrary magnetic field is performed. We consider a parabolic lateral confining potential. The addition energy, E(N+1)-E(N), where N is the number of electrons, is compared with experimental data and the different contributions to the energy are analyzed. The Hamiltonian is modeled by a density functional, which includes the exchange and correlation interactions and the local formation of Landau levels for different equilibrium spin populations. We obtain an analytical expression for the critical density under which spontaneous polarization, induced by the exchange interaction, takes place.

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We investigate the influence of the driving mechanism on the hysteretic response of systems with athermal dynamics. In the framework of local mean-field theory at finite temperature (but neglecting thermally activated processes), we compare the rate-independent hysteresis loops obtained in the random field Ising model when controlling either the external magnetic field H or the extensive magnetization M. Two distinct behaviors are observed, depending on disorder strength. At large disorder, the H-driven and M-driven protocols yield identical hysteresis loops in the thermodynamic limit. At low disorder, when the H-driven magnetization curve is discontinuous (due to the presence of a macroscopic avalanche), the M-driven loop is reentrant while the induced field exhibits strong intermittent fluctuations and is only weakly self-averaging. The relevance of these results to the experimental observations in ferromagnetic materials, shape memory alloys, and other disordered systems is discussed.

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Step bunching develops in the epitaxy of SrRuO3 on vicinal SrTiO3(001) substrates. We have investigated the formation mechanisms and we show here that step bunching forms by lateral coalescence of wedgelike three-dimensional islands that are nucleated at substrate steps. After coalescence, wedgelike islands become wider and straighter with growth, forming a self-organized network of parallel step bunches with altitudes exceeding 30 unit cells, separated by atomically flat terraces. The formation mechanism of step bunching in SrRuO3, from nucleated islands, radically differs from one-dimensional models used to describe bunching in semiconducting materials. These results illustrate that growth phenomena of complex oxides can be dramatically different to those in semiconducting or metallic systems.

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Semiclassical theories such as the Thomas-Fermi and Wigner-Kirkwood methods give a good description of the smooth average part of the total energy of a Fermi gas in some external potential when the chemical potential is varied. However, in systems with a fixed number of particles N, these methods overbind the actual average of the quantum energy as N is varied. We describe a theory that accounts for this effect. Numerical illustrations are discussed for fermions trapped in a harmonic oscillator potential and in a hard-wall cavity, and for self-consistent calculations of atomic nuclei. In the latter case, the influence of deformations on the average behavior of the energy is also considered.

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In now-a-days semiconductor and MEMS technologies the photolithography is the working horse for fabrication of functional devices. The conventional way (so called Top-Down approach) of microstructuring starts with photolithography, followed by patterning the structures using etching, especially dry etching. The requirements for smaller and hence faster devices lead to decrease of the feature size to the range of several nanometers. However, the production of devices in this scale range needs photolithography equipment, which must overcome the diffraction limit. Therefore, new photolithography techniques have been recently developed, but they are rather expensive and restricted to plane surfaces. Recently a new route has been presented - so-called Bottom-Up approach - where from a single atom or a molecule it is possible to obtain functional devices. This creates new field - Nanotechnology - where one speaks about structures with dimensions 1 - 100 nm, and which has the possibility to replace the conventional photolithography concerning its integral part - the self-assembly. However, this technique requires additional and special equipment and therefore is not yet widely applicable. This work presents a general scheme for the fabrication of silicon and silicon dioxide structures with lateral dimensions of less than 100 nm that avoids high-resolution photolithography processes. For the self-aligned formation of extremely small openings in silicon dioxide layers at in depth sharpened surface structures, the angle dependent etching rate distribution of silicon dioxide against plasma etching with a fluorocarbon gas (CHF3) was exploited. Subsequent anisotropic plasma etching of the silicon substrate material through the perforated silicon dioxide masking layer results in high aspect ratio trenches of approximately the same lateral dimensions. The latter can be reduced and precisely adjusted between 0 and 200 nm by thermal oxidation of the silicon structures owing to the volume expansion of silicon during the oxidation. On the basis of this a technology for the fabrication of SNOM calibration standards is presented. Additionally so-formed trenches were used as a template for CVD deposition of diamond resulting in high aspect ratio diamond knife. A lithography-free method for production of periodic and nonperiodic surface structures using the angular dependence of the etching rate is also presented. It combines the self-assembly of masking particles with the conventional plasma etching techniques known from microelectromechanical system technology. The method is generally applicable to bulk as well as layered materials. In this work, layers of glass spheres of different diameters were assembled on the sample surface forming a mask against plasma etching. Silicon surface structures with periodicity of 500 nm and feature dimensions of 20 nm were produced in this way. Thermal oxidation of the so structured silicon substrate offers the capability to vary the fill factor of the periodic structure owing to the volume expansion during oxidation but also to define silicon dioxide surface structures by selective plasma etching. Similar structures can be simply obtained by structuring silicon dioxide layers on silicon. The method offers a simple route for bridging the Nano- and Microtechnology and moreover, an uncomplicated way for photonic crystal fabrication.

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The result of the first calculation of a self-consistent relativistic many electron correlation diagram ever done (for the system Au - I) leads to a good agreement of the spectral shape and position of the observed noncharacteristic X-rays within the quasi adiabatic model.

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We present a new scheme to solve the time dependent Dirac-Fock-Slater equation (TDDFS) for heavy many electron ion-atom collision systems. Up to now time independent self consistent molecular orbitals have been used to expand the time dependent wavefunction and rather complicated potential coupling matrix elements have been neglected. Our idea is to minimize the potential coupling by using the time dependent electronic density to generate molecular basis functions. We present the first results for 16 MeV S{^16+} on Ar.

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Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.

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We report on an elementary course in ordinary differential equations (odes) for students in engineering sciences. The course is also intended to become a self-study package for odes and is is based on several interactive computer lessons using REDUCE and MATHEMATICA . The aim of the course is not to do Computer Algebra (CA) by example or to use it for doing classroom examples. The aim ist to teach and to learn mathematics by using CA-systems.

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The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

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Colloidal self assembly is an efficient method for making 3-D ordered nanostructures suitable for materials such as photonic crystals and macroscopic solids for catalysis and sensor applications. Colloidal crystals grown by convective methods exhibit defects on two different scales. Macro defects such as cracks and void bands originate from the dynamics of meniscus motion during colloidal crystal growth while micro defects like vacancies, dislocation and stacking faults are indigenous to the colloidal crystalline structure. This paper analyses the crystallography and energetics of the microscopic defects from the point of view of classical thermodynamics and discusses the strategy for the control of the macroscopic defects through optimization of the liquid-vapor interface.

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High density, uniform GaN nanodot arrays with controllable size have been synthesized by using template-assisted selective growth. The GaN nanodots with average diameter 40nm, 80nm and 120nm were selectively grown by metalorganic chemical vapor deposition (MOCVD) on a nano-patterned SiO2/GaN template. The nanoporous SiO2 on GaN surface was created by inductively coupled plasma etching (ICP) using anodic aluminum oxide (AAO) template as a mask. This selective regrowth results in highly crystalline GaN nanodots confirmed by high resolution transmission electron microscopy. The narrow size distribution and uniform spatial position of the nanoscale dots offer potential advantages over self-assembled dots grown by the Stranski–Krastanow mode.

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Nanoporous GaN films are prepared by UV assisted electrochemical etching using HF solution as an electrolyte. To assess the optical quality and morphology of these nanoporous films, micro-photoluminescence (PL), micro-Raman scattering, scanning electron microscopy (SEM), and atomic force microscopy (AFM) techniques have been employed. SEM and AFM measurements revealed an average pore size of about 85-90 nm with a transverse dimension of 70-75 nm. As compared to the as-grown GaN film, the porous layer exhibits a substantial photoluminescence intensity enhancement with a partial relaxation of compressive stress. Such a stress relaxation is further confirmed by the red shifted E₂(TO) phonon peak in the Raman spectrum of porous GaN.

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We show that the prion protein (PrP) is expressed on the surface of bone marrow cell populations enriched in long-term repopulating hematopoietic stem cells. Affinity purification of the PrP-positive and PrP-negative fractions from these populations, followed by competitive reconstitution assays, show that all long-term repopulating hematopoietic stem cells express PrP. Hematopoietic stem cells from PrP null bone marrow exhibit impaired self-renewal in serial competitive transplantation experiments, and premature exhaustion when exposed to cell cycle-specific myelotoxic injury. Therefore, PrP is a novel marker for hematopoietic stem cells and regulates their self-renewal.