220 resultados para TUNNELING STRUCTURES
Resumo:
The crystal structures of the 1:1 proton-transfer compounds of isonipecotamide (piperidine-4-carboxamide) with the monocyclic heteroaromatic carboxylic acids, isonicotinic acid, picolinic acid, dipicolinic acid and pyrazine-2,3-dicarboxylic acid have been determined at 200 K and their hydrogen-bonding patterns examined. The compounds are respectively anhydrous 4-carbamoylpiperidinium pyridine-4-carboxylate (1), the partial hydrate 4-carbamoylpiperidinium pyridine-2-carboxylate 0.25 water (2), the solvate 4-carbamoylpiperidinium 6-carboxypyridine-2-carboxylate methanol monosolvate (3), and anhydrous 4-carbamoylpiperidinium 3-carboxypyrazine-2-carboxylate (4). In compounds 1 and 3, hydrogen-bonding interactions give two-dimensional sheet structures which feature enlarged cyclic ring systems, while in compounds 2 and 4, three-dimensional structures are found. The previously described cyclic R2/2(8) hydrogen-bonded amide-amide dimer is present in 2 and 3. The hydrogen-bonding in 2 involves the partial-occupancy water molecule while the structure of 4 is based on inter-linked homomolecular hydrogen-bonded cation-cation and anion-anion associated chains comprising head-to-tail interactions. This work further demonstrates the utility of the isonipecotamide cation in the generation of chemically stable hydrogen-bonded systems, particularly with aromatic carboxylate anions, providing crystalline solids.
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Carbon nanotubes (CNTs) have excellent electrical, mechanical and electromechanical properties. When CNTs are incorporated into polymers, electrically conductive composites with high electrical conductivity at very low CNT content (often below 1% wt CNT) result. Due to the change in electrical properties under mechanical load, carbon nanotube/polymer composites have attracted significant research interest especially due to their potential for application in in-situ monitoring of stress distribution and active control of strain sensing in composite structures or as strain sensors. To sucessfully develop novel devices for such applications, some of the major challenges that need to be overcome include; in-depth understanding of structure-electrical conductivity relationships, response of the composites under changing environmental conditions and piezoresistivity of different types of carbon nanotube/polymer sensing devices. In this thesis, direct current (DC) and alternating current (AC) conductivity of CNT-epoxy composites was investigated. Details of microstructure obtained by scanning electron microscopy were used to link observed electrical properties with structure using equivalent circuit modeling. The role of polymer coatings on macro and micro level electrical conductivity was investigated using atomic force microscopy. Thermal analysis and Raman spectroscopy were used to evaluate the heat flow and deformation of carbon nanotubes embedded in the epoxy, respectively, and related to temperature induced resistivity changes. A comparative assessment of piezoresistivity was conducted using randomly mixed carbon nanotube/epoxy composites, and new concept epoxy- and polyurethane-coated carbon nanotube films. The results indicate that equivalent circuit modelling is a reliable technique for estimating values of the resistance and capacitive components in linear, low aspect ratio-epoxy composites. Using this approach, the dominant role of tunneling resistance in determining the electrical conductivity was confirmed, a result further verified using conductive-atomic force microscopy analysis. Randomly mixed CNT-epoxy composites were found to be highly sensitive to mechanical strain and temperature variation compared to polymer-coated CNT films. In the vicinity of the glass transition temperature, the CNT-epoxy composites exhibited pronounced resistivity peaks. Thermal and Raman spectroscopy analyses indicated that this phenomenon can be attributed to physical aging of the epoxy matrix phase and structural rearrangement of the conductive network induced by matrix expansion. The resistivity of polymercoated CNT composites was mainly dominated by the intrinsic resistivity of CNTs and the CNT junctions, and their linear, weakly temperature sensitive response can be described by a modified Luttinger liquid model. Piezoresistivity of the polymer coated sensors was dominated by break up of the conducting carbon nanotube network and the consequent degradation of nanotube-nanotube contacts while that of the randomly mixed CNT-epoxy composites was determined by tunnelling resistance between neighbouring CNTs. This thesis has demonstrated that it is possible to use microstructure information to develop equivalent circuit models that are capable of representing the electrical conductivity of CNT/epoxy composites accurately. New designs of carbon nanotube based sensing devices, utilising carbon nanotube films as the key functional element, can be used to overcome the high temperature sensitivity of randomly mixed CNT/polymer composites without compromising on desired high strain sensitivity. This concept can be extended to develop large area intelligent CNT based coatings and targeted weak-point specific strain sensors for use in structural health monitoring.
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The recently released Mathematics, Engineering & Science in the National Interest report (May, 2012) highlights the universal perspective that an education in these disciplines is essential to a nation’s future prosperity. Although studies in STEM (Science, Technology, Engineering, Mathematics) are being implemented across many schools, progress to date has been slow especially with respect to incorporating engineering experiences in the middle and primary grades. Our concerns for the limited attention given to engineering in STEM and the low uptake of university engineering courses in universities, prompted us to conduct a longitudinal project on engineering education across grade levels 7-9.
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Poorly characterized phases (PCP's) may constitute up to 30 volume percent of some C2M carbonaceous chondrite matrices [1] and are an important key to an understanding of matrix evolution. PCPs are usually fine-grained (
Resumo:
Structure and chemistry of poorly characterized phases (PCP). We suggest here that approximately 10 angstrom PCP, a dominant matrix variety, has a structure equivalent to iron-rich tochilinite [6Fe (sub 0.9) S 5(Fe, Mg) (OH) (sub 2) ] which consists of coherently interstratified mackinawite and brucite sheets. approximately 17 angstrom PCP, previously described as an SBB-type mixed-layer structure, is a commensurate intergrowth of serpentine and tochilinite layers. A wide range of cation substitutions is possible within both tochilinite and serpentine-tochilinite structural types. Various forms of PCP observed in carbonaceous chondrites are intergrowths of tochilinite, serpentine, serpentine-tochilinite and/or valleriite-type minerals.--Modified journal abstract.
Resumo:
High resolution transmission electron microscopy of the Mighei carbonaceous chondrite matrix has revealed the presence of a new mixed layer structure material. This mixed-layer material consists of an ordered arrangement of serpentine-type (S) and brucite-type (B) layers in the sequence ... SBBSBB. ... Electron diffraction and imaging techniques show that the basal periodicity is ~ 17 Å. Discrete crystals of SBB-type material are typically curved, of small size (<1 μm) and show structural variations similar to the serpentine group minerals. Mixed-layer material also occurs in association with planar serpentine. Characteristics of SBB-type material are not consistent with known terrestrial mixed-layer clay minerals. Evidence for formation by a condensation event or by subsequent alteration of preexisting material is not yet apparent. © 1982.
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Transport between compartments of eukaryotic cells is mediated by coated vesicles. The archetypal protein coats COPI, COPII, and clathrin are conserved from yeast to human. Structural studies of COPII and clathrin coats assembled in vitro without membranes suggest that coat components assemble regular cages with the same set of interactions between components. Detailed three-dimensional structures of coated membrane vesicles have not been obtained. Here, we solved the structures of individual COPI-coated membrane vesicles by cryoelectron tomography and subtomogram averaging of in vitro reconstituted budding reactions. The coat protein complex, coatomer, was observed to adopt alternative conformations to change the number of other coatomers with which it interacts and to form vesicles with variable sizes and shapes. This represents a fundamentally different basis for vesicle coat assembly.
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This paper investigates the response of multi-storey structures under simulated earthquake loads with friction dampers, viscoelastic dampers and combined friction-viscoelastic damping devices strategically located within shear walls. Consequently, evaluations are made as to how the damping systems affect the seismic response of these structures with respect to deflections and accelerations. In particular, this paper concentrates on the effects of damper types, configurations and their locations within the cut-outs of shear walls. The initial stiffness of the cut out section of the shear wall is removed and replaced by the stiffness and damping of the device. Influence of parameters of damper properties such as stiffness, damping coefficient, location, configuration and size are studied and evaluated using results obtained under several different earthquake scenarios. Structural models with cut outs at different heights are treated in order to establish the effectiveness of the dampers and their optimal placement. This conceptual study has demonstrated the feasibility of mitigating the seismic response of building structures by using embedded dampers.
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Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop.com/snlpred_page.php.
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Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.
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The structures of the anhydrous proton-transfer compounds of the sulfa drug sulfamethazine with 5-nitrosalicylic acid and picric acid, namely 2-(4-aminobenzenesulfonamido)-4,6-dimethylpyrimidinium 2-hydroxy-5-nitrobenzoate, C12H15N4O2S(+)·C7H4NO4(-), (I), and 2-(4-aminobenzenesulfonamido)-4,6-dimethylpyrimidinium 2,4,6-trinitrophenolate, C12H15N4O2S(+)·C6H2N3O7(-), (II), respectively, have been determined. In the asymmetric unit of (I), there are two independent but conformationally similar cation-anion heterodimer pairs which are formed through duplex intermolecular N(+)-H...Ocarboxylate and N-H...Ocarboxylate hydrogen-bond pairs, giving a cyclic motif [graph set R2(2)(8)]. These heterodimers form separate and different non-associated substructures through aniline N-H...O hydrogen bonds, one one-dimensional, involving carboxylate O-atom acceptors, the other two-dimensional, involving both carboxylate and hydroxy O-atom acceptors. The overall two-dimensional structure is stabilized by π-π interactions between the pyrimidinium ring and the 5-nitrosalicylate ring in both heterodimers [minimum ring-centroid separation = 3.4580 (8) Å]. For picrate (II), the cation-anion interaction involves a slightly asymmetric chelating N-H...O R2(1)(6) hydrogen-bonding association with the phenolate O atom, together with peripheral conjoint R1(2)(6) interactions between the same N-H groups and O atoms of the ortho-related nitro groups. An inter-unit amine N-H...Osulfone hydrogen bond gives one-dimensional chains which extend along a and inter-associate through π-π interactions between the pyrimidinium rings [centroid-centroid separation = 3.4752 (9) Å]. The two structures reported here now bring to a total of four the crystallographically characterized examples of proton-transfer salts of sulfamethazine with strong organic acids.
'Information in context' : co-designing workplace structures and systems for organizational learning
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With the aim of advancing professional practice through better understanding how to create workplace contexts that cultivate individual and collective learning through situated 'information in context' experiences, this paper presents insights gained from three North American collaborative design (co-design) implementations. In the current project at the Auraria Library in Denver, Colorado, USA, participants use collaborative information practices to redesign face-to-face and technology-enabled communication, decision making, and planning systems. Design processes are described and results-to-date described, within an appreciative framework which values information sharing and enables knowledge creation through shared leadership.
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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.