1000 resultados para Structural nanoconstriction


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Chromium nitride (CrN) thin films were deposited at room temperature on silicon and glass substrates using DC reactive magnetron sputtering in Ar + N-2 plasma. Structure and mechanical properties of these films were examined by using XRD, FESEM and nanoindentation techniques. XRD studies revealed that films are of mixed phase at lower nitrogen partial pressure (P-N2) and single phase at higher (P-N2). Microscopy results show that the films were composed of non-equiaxed columns with nanocrystallite morphology. The hardness and elastic modulus of the films increase with increasing nitrogen partial pressure (P-N2). A maximum hardness of similar to 29 GPa and elastic modulus of 341 GPa were obtained, which make these films useful for several potential applications. (C) 2012 Elsevier Ltd. All rights reserved.

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Red light emitting cubic Y1.95Eu0.05O3 nanophosphors have been synthesized by a low temperature solution combustion method using ethylene diamine tetra acetic acid (EDTA) as fuel. The systematic studies on the effect of calcination temperature on its structural, photoluminescence (PL), and thermoluminescence (TL) properties were reported. The crystallinity of the samples increases, and the strain is reduced with increasing calcination temperature. SEM micrographs reveal that samples lose their porous nature with an increase in calcination temperature. PL spectra show that the intensity of the red emission (611 nm) is highly dependent on the calcination temperature and is found to be 10 times higher when compared to as-formed samples. The optical band gap (E-g) was found to reduce with an increase of calcination temperature due to reduction of surface defects. The thermoluminescence (TL) intensity was found to be much enhanced in the 1000 degrees C calcined sample. The increase of PL and TL intensity with calcination temperature is attributed to the decrease of the nonradiative recombination probability, which occurs through the elimination of quenching defects. The trap parameters (E, b, s) were estimated from Chen's glow peak shape method and are discussed in detail for their possible usage in dosimetry.

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In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to compu- tational biology or computer vision and have been tackled using algorithms, referred to as structured output learning algorithms. We consider the problem of structured classifi- cation. In the last few years, large margin classifiers like sup-port vector machines (SVMs) have shown much promise for structured output learning. The related optimization prob -lem is a convex quadratic program (QP) with a large num-ber of constraints, which makes the problem intractable for large data sets. This paper proposes a fast sequential dual method (SDM) for structural SVMs. The method makes re-peated passes over the training set and optimizes the dual variables associated with one example at a time. The use of additional heuristics makes the proposed method more efficient. We present an extensive empirical evaluation of the proposed method on several sequence learning problems.Our experiments on large data sets demonstrate that the proposed method is an order of magnitude faster than state of the art methods like cutting-plane method and stochastic gradient descent method (SGD). Further, SDM reaches steady state generalization performance faster than the SGD method. The proposed SDM is thus a useful alternative for large scale structured output learning.

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Domain swapping is an interesting feature of some oligomeric proteins in which each protomer of the oligomer provides an identical surface for exclusive interaction with a segment or domain belonging to another protomer. Here we report results of mutagenesis experiments on the structure of C-terminal helix swapped dimer of a stationary phase survival protein from Salmonella typhimurium (StSurE). Wild type StSurE is a dimer in which a large helical segment at the C-terminus and a tetramerization loop comprising two beta strands are swapped between the protomers. Key residues in StSurE that might promote C-terminal helix swapping were identified by sequence and structural comparisons. Three mutants in which the helix swapping is likely to be avoided were constructed and expressed in E. coli. Three-dimensional X-ray crystal structures of the mutants H234A and D230A/H234A could be determined at 2.1 angstrom and 2.35 angstrom resolutions, respectively. Contrary to expectations, helix swapping was mostly retained in both the mutants. The loss of the crucial D230 OD2- H234 NE2 hydrogen bond (2.89 angstrom in the wild type structure) in the hinge region was compensated by new inter and intra-chain interactions. However, the two fold molecular symmetry was lost and there were large conformational changes throughout the polypeptide. In spite of these changes, the dimeric structure and an approximate tetrameric organization were retained, probably due to the interactions involving the tetramerization loop. Mutants were mostly functionally inactive, highlighting the importance of precise inter-subunit interactions for the symmetry and function of StSurE.

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TiO2 and Al2O3 are commonly used materials in optical thin films in the visible and near‐infrared wavelength region due to their high transparency and good stability. In this work, TiO2 and Al2O3 single, and nano composite thin films with different compositions were deposited on glass and silicon substrates at room temperature using a sol‐gel spin coater. The optical properties like reflectance, transmittance and refractive index have been studied using Spectrophotometer, and structural properties using X‐Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM).

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alpha-Fe2O3 nanoparticles were synthesized by a low temperature solution combustion method. The structural, magnetic and luminescence properties were studied. Powder X-ray diffraction (PXRD) pattern of alpha-Fe2O3 exhibits pure rhombohedral structure. SEM micrographs reveal the dumbbell shaped particles. The EPR spectrum shows an intense resonance signal at g approximate to 5.61 corresponding to isolated Fe3+ ions situated in axially distorted sites, whereas the g approximate to 2.30 is due to Fe3+ ions coupled by exchange interaction. Raman studies show A(1g) (225 cm(-1)) and E-g (293 and 409 cm(-1)) phonon modes. The absorption at 300 nm results from the ligand to metal charge transfer transitions whereas the 540 nm peak is mainly due to the (6)A(1) + (6)A(1) —> T-4(1)(4G) + T-4(1)(4G) excitation of an Fe3+-Fe3+ pair. A prominent TL glow peak was observed at 140 C at heating rate of 5 degrees C s(-1). The trapping parameters namely activation energy (E), frequency factor (s) and order of kinetics (b) were evaluated and discussed. (C) 2012 Elsevier B.V. All rights reserved.

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Polycrystalline Ca0.18Sr0.226Ba0.594Nb2O6 (CSBN18) was synthesized via the solid-state reaction route. X-ray structural studies confirmed it belonged to the tetragonal tungsten bronze family. Rietveld refinement of the X-ray data has been carried out for CSBN18 where the atomic positions and site occupancy factors for A-sites have been determined. The dielectric properties of CSBN18 ceramic were studied as a function of temperature in the 100 Hz - 1 MHz frequency range. The dielectric relaxation followed the Vogel-Fulcher relation wherein E-a = 37.4 meV; T-f = 131.5 degrees C and omega(0) = 4.31 x 10(9) rad s(-1). A high pyroelectric coefficient of similar to 250 mu C m(-2).K was obtained around the transition temperature (similar to 150 degrees C). This is significantly higher than that reported for polycrystalline SrxBa1-xNb2O6 (SBN). However, the piezoelectric coefficient (d(33)) of the title composition was as low as 6 pC N-1.

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Optically active Lewis acids and Lewis pairs were synthesized and characterized by multinuclear NMR, UV/Vis spectroscopy and elemental analysis. Optical rotation measurements were carried out and the absolute configuration of the new chiral molecules confirmed by single crystal X-ray diffraction.

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A systematic x-ray and neutron powder diffraction study of the giant tetragonality multiferroic (1-x) BiFeO3-(x) PbTiO3 have revealed that the compositions close to the morphotropic phase boundary present two different structural phase transition scenarios on cooling from the cubic phase: (i) cubic -> tetragonal (T-2) + tetragonal (T-1) -> tetragonal (T-1) and (ii) cubic -> tetragonal (T-2) + tetragonal (T-1) + rhombohedral (R3c) -> tetragonal (T-1) + rhombohedral (R3c). The comparatively larger tetragonality (c/a - 1) of the T-1 phase as compared to the coexisting isostructural T-2 phase is shown to be a result of significantly greater degree of overlap of the Pb/Bi-6s and Ti/Fe-3d with the O-2p orbitals as compared to that in the T-2 phase. The formation/suppression of the minor metastable rhombohedral phase seems to be governed by subtle play of local kinetic factors. In the scenario when the minor rhombohedral (R) phase is formed along with the tetragonal phases it is able to accommodate the large transformation stress in the system due to formation of the tetragonal phases, and prevent the solid from disintegration into powder after sintering. When the metastable rhombohedral phase is not formed, the large transformation strain ruptures the grain boundaries leading to fragmentation of the dense solid to powder. (C) 2013 American Institute of Physics. http://dx.doi.org/10.1063/1.4792215]

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A few variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of the model parameters appears to be quite noticeable. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers.

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Mn doping in ZnS nanoplatelets has been shown to induce a structural transition from the wurtzite to the zinc blende phase. We trace the origin of this transition to quantum confinement effects, which shift the valence band maximum of the wurtzite and zinc blende polyrnorphs of ZnS at different rates as a function of the nanocrystal size, arising from different effective hole masses in the two structures. This modifies the covalency associated with Mn incorporation and is reflected in the size-dependent binding energy difference for the two structures.

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The synthesis of the dipeptide antibiotic bacilysin involves the sequential action of multiple enzymes in the bac operon. YwfH (also referred to as BacG) catalyzes the stereoselective reduction of dihydro-hydroxyphenylpyruvate (H2HPP) to tetrahydro-hydroxyphenylpyruvate (H4HPP) in this biosynthetic pathway. YwfH is an NADPH-dependent reductase that facilitates the conjugate addition of a hydride at the C4 olefin terminus of H2HPP. Here, the structure of YwfH is described at three conformational steps: the apo form, an apo-like conformation and the NADPH complex. YwfH is structurally similar to other characterized short-chain dehydrogenase/reductases despite having marginal sequence similarity. The structures of YwfH in different conformational states provide a rationale for the ping-pong reaction mechanism. The identification and role of the residues in the catalytic tetrad (Lys113Tyr117Ser155Asn158) in proton transfer were examined by mutational analysis. Together, the structures and biochemical features revealed synchronized conformational changes that facilitate cofactor specificity and catalysis of H4HPP formation en route to tetrahydrotyrosine synthesis.

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Titanium nitride (TiN), which is widely used for hard coatings, reportedly undergoes a pressure-induced structural phase transformation, from a NaCl to a CsCl structure, at similar to 7 GPa. In this paper, we use first-principles calculations based on density functional theory with a generalized gradient approximation of the exchange correlation energy to determine the structural stability of this transformation. Our results show that the stress required for this structural transformation is substantially lower (by more than an order of magnitude) when it is deviatoric in nature vis-a-vis that under hydrostatic pressure. Local stability of the structure is assessed with phonon dispersion determined at different pressures, and we find that CsCl structure of TiN is expected to distort after the transformation. From the electronic structure calculations, we estimate the electrical conductivity of TiN in the CsCl structure to be about 5 times of that in NaCl structure, which should be observable experimentally. (C) 2013 American Institute of Physics. http://dx.doi.org/10.1063/1.4798591]

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Structural Support Vector Machines (SSVMs) have recently gained wide prominence in classifying structured and complex objects like parse-trees, image segments and Part-of-Speech (POS) tags. Typical learning algorithms used in training SSVMs result in model parameters which are vectors residing in a large-dimensional feature space. Such a high-dimensional model parameter vector contains many non-zero components which often lead to slow prediction and storage issues. Hence there is a need for sparse parameter vectors which contain a very small number of non-zero components. L1-regularizer and elastic net regularizer have been traditionally used to get sparse model parameters. Though L1-regularized structural SVMs have been studied in the past, the use of elastic net regularizer for structural SVMs has not been explored yet. In this work, we formulate the elastic net SSVM and propose a sequential alternating proximal algorithm to solve the dual formulation. We compare the proposed method with existing methods for L1-regularized Structural SVMs. Experiments on large-scale benchmark datasets show that the proposed dual elastic net SSVM trained using the sequential alternating proximal algorithm scales well and results in highly sparse model parameters while achieving a comparable generalization performance. Hence the proposed sequential alternating proximal algorithm is a competitive method to achieve sparse model parameters and a comparable generalization performance when elastic net regularized Structural SVMs are used on very large datasets.