971 resultados para Homogeneous Kernels
Resumo:
Boron addition to conventional titanium alloys below the eutectic limit refines the cast microstructure and improves mechanical properties. The present work explores the influence of hypoeutectic boron addition on the microstructure and texture evolution in Ti-6Al-4V alloy under beta extrusion. The beta extruded microstructure of Ti-6Al-4V is characterized by shear bands parallel to the extrusion direction. In contrast, the extruded Ti-6Al-4V-0.1B alloy shows a regular beta worked microstructure consisting of fine prior beta grains and acicular alpha-lamellae with no signs of the microstructural instability. Crystallographic texture after extrusion was almost identical for the two alloys indicating the similarity in their transformation behavior, which is attributed to complete dynamic recrystallization during beta processing. Microstructural features as well as crystallographic texture indicate dominant grain boundary related deformation processes for the boron modified alloy that leads to homogeneous deformation without instability formation. The absence of shear bands has significant technological importance as far as the secondary processing of boron added alloys in (alpha + beta)-phase field are concerned. (C) 2012 Elsevier B.V. All rights reserved.
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A careful comparison of the experimental results reported in the literature reveals different variations of the melting temperature even for the same materials. Though there are different theoretical models, thermodynamic model has been extensively used to understand different variations of size-dependent melting of nanoparticles. There are different hypotheses such as homogeneous melting (HMH), liquid nucleation and growth (LNG) and liquid skin melting (LSM) to resolve different variations of melting temperature as reported in the literature. HMH and LNG account for the linear variation where as LSM is applied to understand the nonlinear behaviour in the plot of melting temperature against reciprocal of particle size. However, a bird's eye view reveals that either HMH or LSM has been extensively used by experimentalists. It has also been observed that not a single hypothesis can explain the size-dependent melting in the complete range. Therefore we describe an approach which can predict the plausible hypothesis for a given data set of the size-dependent melting temperature. A variety of data have been analyzed to ascertain the hypothesis and to test the approach.
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The solution of a bivariate population balance equation (PBE) for aggregation of particles necessitates a large 2-d domain to be covered. A correspondingly large number of discretized equations for particle populations on pivots (representative sizes for bins) are solved, although at the end only a relatively small number of pivots are found to participate in the evolution process. In the present work, we initiate solution of the governing PBE on a small set of pivots that can represent the initial size distribution. New pivots are added to expand the computational domain in directions in which the evolving size distribution advances. A self-sufficient set of rules is developed to automate the addition of pivots, taken from an underlying X-grid formed by intersection of the lines of constant composition and constant particle mass. In order to test the robustness of the rule-set, simulations carried out with pivotwise expansion of X-grid are compared with those obtained using sufficiently large fixed X-grids for a number of composition independent and composition dependent aggregation kernels and initial conditions. The two techniques lead to identical predictions, with the former requiring only a fraction of the computational effort. The rule-set automatically reduces aggregation of particles of same composition to a 1-d problem. A midway change in the direction of expansion of domain, effected by the addition of particles of different mean composition, is captured correctly by the rule-set. The evolving shape of a computational domain carries with it the signature of the aggregation process, which can be insightful in complex and time dependent aggregation conditions. (c) 2012 Elsevier Ltd. All rights reserved.
Resumo:
The application of electromagnetic field in the context of bacteria associated infections on biomaterial surfaces has not been extensively explored. In this work, we applied a moderate intensity static magnetic field (100 mT) to understand the adhesion and growth behavior of both gram positive (S. epidermidis) and gram negative bacteria (E. coli) and also to investigate bactericidal/bacteriostatic property of the applied electromagnetic field. An in-house built magnetometer was used to apply static homogeneous magnetic field during a planned set of in vitro experiments. Both the sintered hydroxyapatite (HA) and the control samples seeded with bacteria were exposed to the magnetic field (100 mT) for different timescale during their log phase growth. Quantitative analysis of the SEM images confirms the effect of electromagnetic field on suppressing bacterial growth. Furthermore, cell integrity and inner membrane permeabilization assays were performed to understand the origin of such effect. The results of these assays were statistically analyzed to reveal the bactericidal effect of magnetic field, indicating cell membrane damage. Under the investigated culture conditions, the bactericidal effect was found to be less effective for S. Epidermidis than E. coli. (c) 2012 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 2012:100B:12061217, 2012.
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Functionally Gradient Materials (FGM) are considered as a novel concept to implement graded functionality that otherwise cannot be achieved by conventional homogeneous materials. For biomedical applications, an ideal combination of bioactivity on the material surface as well as good physical property (strength/toughness/hardness) of the bulk is required in a designed FGM structure. In this perspective, the present work aims at providing a smooth gradation of functionality (enhanced toughening of the bulk, and retained biocompatibility of the surface) in a spark plasma processed hydroxyapatite-alumina-zirconia (HAp-Al2O3-YSZ) FGM bio-composite. In the current work HAp (fracture toughness similar to 1.5 MPa.m(1/2)) and YSZ (fracture toughness similar to 62 MPa.m(1/2)) are coupled with a transition layer of Al2O3 allowing minimum gradient of mechanical properties (especially the fracture toughness similar to 3.5 MPa.m(1/2)).The in vitro cyto-compatibilty of HAp-Al2O3-YSZ FGM was evaluated using L929 fibroblast cells and Saos-2 Osteoblast cells for their adhesion and growth. From analysis of the cell viability data, it is evident that FGM supports good cell proliferation after 2, 3, 4 days culture. The measured variation in hardness, fracture toughness and cellular adhesion across the cross section confirmed the smooth transition achieved for the FGM (HAp-Al2O3-YSZ) nanocomposite, i.e. enhanced bulk toughness combined with unrestricted surface bioactivity. Therefore, such designed biomaterials can serve as potential bone implants. (C) 2012 Elsevier B.V. All rights reserved.
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Compositional dependent investigations of the bulk GeTe chalcogenides alloys added with different selenium concentrations are carried out by X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), electron probe micro-analyzer (EPMA) and differential scanning calorimetry (DSC). The measurements reveal that GeTe crystals are predominant in alloys up to 0.20 at.% of Se content indicating interstitial occupancy of Se in the Ge vacancies. Raman modes in the GeTe alloys changes to GeSe modes with the addition of Se. Amorphousness in the alloy increases with increase of Se and 0.50 at.% Se alloy forms a homogeneous amorphous phase with a mixture of Ge-Se and Te-Se bonds. Structural changes are explained with the help of bond theory of solids. Crystallization temperature is found to be increasing with increase of Se, which will enable the amorphous stability. For the optimum 0.50 at.% Se alloy, the melting temperature has reduced which will reduce the RESET current requirement for the phase change memory applications. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
A strategy called macro-(affinity ligand) facilitated three-phase partitioning (MLFTPP) is described for refolding of a diverse set of recombinant proteins starting from the solubilized inclusion bodies. It essentially consists of: (i) binding of the protein with a suitable smart polymer and (ii) precipitating the polymer-protein complex as an interfacial layer by mixing in a suitable amount of ammonium sulfate and t-butanol. Smart polymers are stimuli-responsive polymers that become insoluble on the application of a suitable stimulus (e.g., a change in the temperature, pH, or concentration of a chemical species such as Ca 2+ or K +). The MLFTPP process required approximately 10min, and the refolded proteins were found to be homogeneous on sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The folded proteins were characterized by fluorescence emission spectroscopy, circular dichroism spectroscopy, biological activity, melting temperature, and surface hydrophobicity measurements by 8-anilino-1-naphthalenesulfonate fluorescence. Two refolded antibody fragments were also characterized by measuring K D by Biacore by using immobilized HIV-1 gp120. The data demonstrate that MLFTPP is a rapid and convenient procedure for refolding a variety of proteins from inclusion bodies at high concentration. Although establishing the generic nature of the approach would require wider trials by different groups, its success with the diverse kinds of proteins tried so far appears to be promising.
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Room temperature, uniaxial compression creep experiments were performed on micro-/nano-sized pillars (having diameters in the range of 250-2000 nm) of a Zr-based bulk metallic glass (BMG) to investigate the influence of sample size on the time-dependent plastic deformation behavior in amorphous alloys. Experimental results reveal that plastic deformation indeed occurs at ambient temperature and at stresses that are well below the nominal quasi-static yield stress. At a given stress, higher total strains accrue in the smaller specimens. In all cases, plastic deformation was found to be devoid of shear bands, i.e., it occurs in homogeneous manner. The stress exponent obtained from the slope of the linear relation between strain rate and applied stress also shows a strong size effect, which is rationalized in terms of the amount of free volume created during deformation and the surface-to-volume ratio of the pillar. (C) 2012 Elsevier Ltd. All rights reserved.
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Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.
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From the analysis of experimentally observed variations in surface strains with loading in reinforced concrete beams, it is noted that there is a need to consider the evolution of strains (with loading) as a stochastic process. Use of Markov Chains for modeling stochastic evolution of strains with loading in reinforced concrete flexural beams is studied in this paper. A simple, yet practically useful, bi-level homogeneous Gaussian Markov Chain (BLHGMC) model is proposed for determining the state of strain in reinforced concrete beams. The BLHGMC model will be useful for predicting behavior/response of reinforced concrete beams leading to more rational design.
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We use a self-consistent strong-coupling expansion for the self-energy (perturbation theory in the hopping) to describe the nonequilibrium dynamics of strongly correlated lattice fermions. We study the three-dimensional homogeneous Fermi-Hubbard model driven by an external electric field showing that the damping of the ensuing Bloch oscillations depends on the direction of the field and that for a broad range of field strengths a long-lived transient prethermalized state emerges. This long-lived transient regime implies that thermal equilibrium may be out of reach of the time scales accessible in present cold atom experiments but shows that an interesting new quasiuniversal transient state exists in nonequilibrium governed by a thermalized kinetic energy but not a thermalized potential energy. In addition, when the field strength is equal in magnitude to the interaction between atoms, the system undergoes a rapid thermalization, characterized by a different quasiuniversal behavior of the current and spectral function for different values of the hopping. DOI: 10.1103/PhysRevLett.109.260402
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In this article, we investigate the performance of a volume integral equation code on BlueGene/L system. Volume integral equation (VIE) is solved for homogeneous and inhomogeneous dielectric objects for radar cross section (RCS) calculation in a highly parallel environment. Pulse basis functions and point matching technique is used to convert the volume integral equation into a set of simultaneous linear equations and is solved using parallel numerical library ScaLAPACK on IBM's distributed-memory supercomputer BlueGene/L by different number of processors to compare the speed-up and test the scalability of the code.
Resumo:
In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.
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We derive exact expressions for the zeroth and the first three spectral moment sum rules for the retarded Green's function and for the zeroth and the first spectral moment sum rules for the retarded self-energy of the inhomogeneous Bose-Hubbard model in nonequilibrium, when the local on-site repulsion and the chemical potential are time-dependent, and in the presence of an external time-dependent electromagnetic field. We also evaluate these expressions for the homogeneous case in equilibrium, where all time dependence and external fields vanish. Unlike similar sum rules for the Fermi-Hubbard model, in the Bose-Hubbard model case, the sum rules often depend on expectation values that cannot be determined simply from parameters in the Hamiltonian like the interaction strength and chemical potential but require knowledge of equal-time many-body expectation values from some other source. We show how one can approximately evaluate these expectation values for the Mott-insulating phase in a systematic strong-coupling expansion in powers of the hopping divided by the interaction. We compare the exact moment relations to the calculated moments of spectral functions determined from a variety of different numerical approximations and use them to benchmark their accuracy. DOI: 10.1103/PhysRevA.87.013628
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ADVANCED MULTIFUNCTIONAL INORGANIC NANOSTRUCTURED OXIDES FOR CONTROLLED RELEASE AND SENSING. We demonstrate here certain examples of multifunctional nanostructured oxidematerials for biotechnological and environmental applications.Various in-house synthesized homogeneous nanostructured viz.mesoporous and nanotubes silica and titania have been employed for controlled drug delivery and electrochemical biosensing applications. Confinement of macromolecules such as proteins studied via electrochemical, thermal and spectroscopic methods showed no detrimental effect on native protein structure and function, thus suggesting effective utility of oxide nanostructures as bio-encapsulators. Multi-functionalitywas demonstrated via employing similar nanostructures for sensing organic water pollutants e.g. textile dyes.