Chitosan-polyvinyl alcohol-sulfonated polyethersulfone mixed-matrix membranes as methanol-barrier electrolytes for DMFCs

Chitosan (CS)-polyvinyl alcohol (PVA) cross-linked with sulfosuccinic acid (SSA) and modified with sulfonated polyethersulfone (SPES) mixed-matrix membranes are reported for their application in direct methanol fuel cells (DMFCs). Polyethersulfone (PES) is sulfonated by chlorosulfonic acid and factors affecting the sulfonation reaction, such as time and temperature, are studied. The ion-exchange capacity, degree of sulfonation, sorption, and proton conductivity for the mixed-matrix membranes are investigated. The mixed-matrix membranes are also characterised for their mechanical and thermal properties. The methanol-crossover flux across the mixed-matrix membranes is studied by measuring the mass balance of methanol using the density meter. The methanol cross-over for these membranes is found to be about 33% lower in relation to Nafion-117 membrane. The DMFC employing CS-PVA-SPES mixed-matrix membrane with an optimum content of 25 wt % SPES delivers a peak power-density of 5.5 mW cm-2 at a load current-density of 25 mA cm-2 while operating at 70 degrees C. (C) 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Density matrix renormalization group algorithm for Bethe lattices of spin-1/2 or spin-1 sites with Heisenberg antiferromagnetic exchange

A density matrix renormalization group (DMRG) algorithm is presented for the Bethe lattice with connectivity Z = 3 and antiferromagnetic exchange between nearest-neighbor spins s = 1/2 or 1 sites in successive generations g. The algorithm is accurate for s = 1 sites. The ground states are magnetic with spin S(g) = 2(g)s, staggered magnetization that persists for large g > 20, and short-range spin correlation functions that decrease exponentially. A finite energy gap to S > S(g) leads to a magnetization plateau in the extended lattice. Closely similar DMRG results for s = 1/2 and 1 are interpreted in terms of an analytical three-site model.

A novel ``pro-sensitizer'' based sensing of enzymes using Tb(III) luminescence in a hydrogel matrix

Chemically synthesized ``pro-sensitizers'' release the sensitizer in the presence of lipase or beta-glucosidase, triggering a significant luminescence response from a lanthanide based hydrogel.

On the microstructure-tensile property correlations in bulk metallic glass matrix composites with crystalline dendrites

Bulk metallic glass (BMG) matrix composites with crystalline dendrites as reinforcements exhibit a wide variance in their microstructures (and thus mechanical properties), which in turn can be attributed to the processing route employed, which affects the size and distribution of the dendrites. A critical investigation on the microstructure and tensile properties of Zr/Ti-based BMG composites of the same composition, but produced by different routes, was conducted so as to identify ``structure-property'' connections in these materials. This was accomplished by employing four different processing methods-arc melting, suction casting, semi-solid forging and induction melting on a water-cooled copper boat-on composites with two different dendrite volume fractions, V-d. The change in processing parameters only affects microstructural length scales such as the interdendritic spacing, lambda, and dendrite size, delta, whereas compositions of the matrix and dendrite are unaffected. Broadly, the composite's properties are insensitive to the microstructural length scales when V-d is high (similar to 75%), whereas they become process dependent for relatively lower V-d (similar to 55%). Larger delta in arc-melted and forged specimens result in higher ductility (7-9%) and lower hardening rates, whereas smaller dendrites increase the hardening rate. A bimodal distribution of dendrites offers excellent ductility at a marginal cost of yield strength. Finer lambda result in marked improvements in both ductility and yield strength, due to the confinement of shear band nucleation sites in smaller volumes of the glassy phase. Forging in the semi-solid state imparts such a microstructure. (c) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Nonlocal continuum mechanics based ultrasonic flexural wave dispersion characteristics of a monolayer graphene embedded in polymer matrix

Wave propagation in graphene sheet embedded in elastic medium (polymer matrix) has been a topic of great interest in nanomechanics of graphene sheets, where the equivalent continuum models are widely used. In this manuscript, we examined this issue by incorporating the nonlocal theory into the classical plate model. The influence of the nonlocal scale effects has been investigated in detail. The results are qualitatively different from those obtained based on the local/classical plate theory and thus, are important for the development of monolayer graphene-based nanodevices. In the present work, the graphene sheet is modeled as an isotropic plate of one-atom thick. The chemical bonds are assumed to be formed between the graphene sheet and the elastic medium. The polymer matrix is described by a Pasternak foundation model, which accounts for both normal pressure and the transverse shear deformation of the surrounding elastic medium. When the shear effects are neglected, the model reduces to Winkler foundation model. The normal pressure or Winkler elastic foundation parameter is approximated as a series of closely spaced, mutually independent, vertical linear elastic springs where the foundation modulus is assumed equivalent to stiffness of the springs. For this model, the nonlocal governing differential equations of motion are derived from the minimization of the total potential energy of the entire system. An ultrasonic type of flexural wave propagation model is also derived and the results of the wave dispersion analysis are shown for both local and nonlocal elasticity calculations. From this analysis we show that the elastic matrix highly affects the flexural wave mode and it rapidly increases the frequency band gap of flexural mode. The flexural wavenumbers obtained from nonlocal elasticity calculations are higher than the local elasticity calculations. The corresponding wave group speeds are smaller in nonlocal calculation as compared to local elasticity calculation. The effect of y-directional wavenumber (eta(q)) on the spectrum and dispersion relations of the graphene embedded in polymer matrix is also observed. We also show that the cut-off frequencies of flexural wave mode depends not only on the y-direction wavenumber but also on nonlocal scaling parameter (e(0)a). The effect of eta(q) and e(0)a on the cut-off frequency variation is also captured for the cases of with and without elastic matrix effect. For a given nanostructure, nonlocal small scale coefficient can be obtained by matching the results from molecular dynamics (MD) simulations and the nonlocal elasticity calculations. At that value of the nonlocal scale coefficient, the waves will propagate in the nanostructure at that cut-off frequency. In the present paper, different values of e(0)a are used. One can get the exact e(0)a for a given graphene sheet by matching the MD simulation results of graphene with the results presented in this article. (c) 2012 Elsevier Ltd. All rights reserved.

Positive Relationships between Association Strength and Phenotypic Similarity Characterize the Assembly of Mixed-Species Bird Flocks Worldwide

Competition theory predicts that local communities should consist of species that are more dissimilar than expected by chance. We find a strikingly different pattern in a multicontinent data set (55 presence-absence matrices from 24 locations) on the composition of mixed-species bird flocks, which are important sub-units of local bird communities the world over. By using null models and randomization tests followed by meta-analysis, we find the association strengths of species in flocks to be strongly related to similarity in body size and foraging behavior and higher for congeneric compared with noncongeneric species pairs. Given the local spatial scales of our individual analyses, differences in the habitat preferences of species are unlikely to have caused these association patterns; the patterns observed are most likely the outcome of species interactions. Extending group-living and social-information-use theory to a heterospecific context, we discuss potential behavioral mechanisms that lead to positive interactions among similar species in flocks, as well as ways in which competition costs are reduced. Our findings highlight the need to consider positive interactions along with competition when seeking to explain community assembly.

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

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.

Fast acoustic likelihood computation using low-rank matrix approximation

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for LVCSR systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication.In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on a 1138 word vocabulary RM1 task using Sphinx 3.7 system show that, for a typical case the matrix multiplication approach leads to overall speedup of 46%. Both the low-rank approximation methods increase the speedup to around 60%, with the former method increasing the word error rate (WER) from 3.2% to 6.6%, while the latter increases the WER from 3.2% to 3.5%.

A soluble-lead redox flow battery with corrugated graphite sheet and reticulated vitreous carbon as positive and negative current collectors

A soluble-lead redox flow battery with corrugated-graphite sheet and reticulated-vitreous carbon as positive and negative current collectors is assembled and performance tested. In the cell, electrolyte comprising of 1 center dot 5 M lead (II) methanesulfonate and 0 center dot 9 M methanesulfonic acid with sodium salt of lignosulfonic acid as additive is circulated through the reaction chamber at a flow rate of 50 ml min (-aEuro parts per thousand 1). During the charge cycle, pure lead (Pb) and lead dioxide (PbO2) from the soluble lead (II) species are electrodeposited onto the surface of the negative and positive current collectors, respectively. Both the electrodeposited materials are characterized by XRD, XPS and SEM. Phase purity of synthesized lead (II) methanesulfonate is unequivocally established by single crystal X-ray diffraction followed by profile refinements using high resolution powder data. During the discharge cycle, electrodeposited Pb and PbO2 are dissolved back into the electrolyte. Since lead ions are produced during oxidation and reduction at the negative and positive plates, respectively there is no risk of crossover during discharge cycle, preventing the possibility of lowering the overall efficiency of the cell. As the cell employs a common electrolyte, the need of employing a membrane is averted. It has been possible to achieve a capacity value of 114 mAh g (-aEuro parts per thousand 1) at a load current-density of 20 mA cm (-aEuro parts per thousand 2) with the cell at a faradaic efficiency of 95%. The cell is tested for 200 cycles with little loss in its capacity and efficiency.

Spatial Wavelet Approach to Local Matrix Crack Detection in Composite Beams with Ply Level Material Uncertainty

Wavelet coefficients based on spatial wavelets are used as damage indicators to identify the damage location as well as the size of the damage in a laminated composite beam with localized matrix cracks. A finite element model of the composite beam is used in conjunction with a matrix crack based damage model to simulate the damaged composite beam structure. The modes of vibration of the beam are analyzed using the wavelet transform in order to identify the location and the extent of the damage by sensing the local perturbations at the damage locations. The location of the damage is identified by a sudden change in spatial distribution of wavelet coefficients. Monte Carlo Simulations (MCS) are used to investigate the effect of ply level uncertainty in composite material properties such as ply longitudinal stiffness, transverse stiffness, shear modulus and Poisson's ratio on damage detection parameter, wavelet coefficient. In this study, numerical simulations are done for single and multiple damage cases. It is observed that spatial wavelets can be used as a reliable damage detection tool for composite beams with localized matrix cracks which can result from low velocity impact damage.

Learning from positive and unlabelled examples using maximum margin clustering

Learning from Positive and Unlabelled examples (LPU) has emerged as an important problem in data mining and information retrieval applications. Existing techniques are not ideally suited for real world scenarios where the datasets are linearly inseparable, as they either build linear classifiers or the non-linear classifiers fail to achieve the desired performance. In this work, we propose to extend maximum margin clustering ideas and present an iterative procedure to design a non-linear classifier for LPU. In particular, we build a least squares support vector classifier, suitable for handling this problem due to symmetry of its loss function. Further, we present techniques for appropriately initializing the labels of unlabelled examples and for enforcing the ratio of positive to negative examples while obtaining these labels. Experiments on real-world datasets demonstrate that the non-linear classifier designed using the proposed approach gives significantly better generalization performance than the existing relevant approaches for LPU.

Tb3+ sensitization in a deoxycholate organogel matrix, and selective quenching of luminescence by an aromatic nitro derivative

In this article, we present the discovery of a metallo-organogel derived from a Tb3+ salt and sodium deoxycholate (NaDCh) in methanol. The gel was made luminescent through sensitization of Tb3+ by doping with 2,3-dihydroxynaphthalene (DHN) in micromolar concentrations. Rheological measurements of the mechanical properties of the organogel confirmed the characteristics of a true gel. Significant quenching of Tb3+ luminescence was observed in the deoxycholate gel matrix by 2,4,7-trinitrofluorenone (TNF), but not by several other polynitro aromatics. Microscopic studies (AFM, TEM and SEM) revealed a highly entangled fibrous network. The xerogels retained luminescent properties suggesting the possibility for application in coatings, etc.

Polymer template-assisted microemulsion synthesis of large surface area, porous Li2MnO3 and its characterization as a positive electrode material of Li-ion cells

Lithium-rich manganese oxide (Li2MnO3) is prepared by reverse microemulsion method employing Pluronic acid (P123) as a soft template and studied as a positive electrode material. The as-prepared sample possesses good crystalline structure with a broadly distributed mesoporosity but low surface area. As expected, cyclic voltammetry and charge-discharge data indicate poor electrochemical activity. However, the sample gains surface area with narrowly distributed mesoporosity and also electrochemical activity after treating in 4 M H2SO4. A discharge capacity of about 160 mAh g(-1) is obtained. When the acid-treated sample is heated at 300 A degrees C, the resulting porous sample with a large surface area and dual porosity provides a discharge capacity of 240 mAh g(-1). The rate capability study suggests that the sample provides about 150 mAh g(-1) at a specific discharge current of 1.25 A g(-1). Although the cycling stability is poor, the high rate capability is attributed to porous nature of the material.

Effect of analyte concentration on the laser-induced plasma temperature and electron density in liquid matrix

In the present work, we report spectroscopic studies of laser-induced plasmas produced by focusing the second harmonic (532nm) of a Nd:YAG laser onto the laminar flow of a liquid containing chromium. The plasma temperature is determined from the coupled Saha-Boltzmann plot and the electron density is evaluated from the Stark broadening of an ionic line of chromium Cr(II)] at 267.7nm. Our results reveal a decrease in plasma temperature with an increase in Cr concentration up to a certain concentration level; after that, it becomes approximately constant, while the electron density increases with an increase in analyte (Cr) concentration in liquid matrix.

Positive temperature coefficient and structural relaxations in selectively localized MWNTs in PE/PEO blends

The dispersion state of multiwall carbon nanotubes (MWNTs) in melt mixed polyethylene/polyethylene oxide (PE/PEO) blends has been assessed by both surface and volume electrical conductivity measurements and the structural relaxations have been assessed by broadband dielectric spectroscopy. The selective localization of MWNTs in the blends was controlled by the flow characteristics of the components, which led to their localization in the energetically less favored phase (PE). The electrical conductivity and positive temperature co-efficient (PTC) measurements were carried out on hot pressed samples. The neat blends exhibited only a negative temperature coefficient (NTC) effect while the blends with MWNTs exhibited both a PTC and a NTC at the melting temperatures of PE and PEO respectively. These phenomenal changes were corroborated with the different crystalline morphology in the blends. It was deduced that during compression molding, the more viscous PEO phase spreads less in contrast to the less viscous PE phase. This has further resulted in a gradient in morphology as well as the distribution state of the MWNTs in the samples and was supported by scanning electron and scanning acoustic microscopy (SAM) studies and contact angle measurements. SAM from different depths of the samples revealed a gradient in the microstructure in the PE/PEO blends which is contingent upon the flow characteristics of the components. Interestingly, the surface and volume electrical conductivity was different due to the different dispersion state of the MWNTs at the surface and bulk. The observed surface and volume electrical conductivity measurements were corroborated with the evolved morphology during processing. The structural relaxations in both PE and PEO were discerned from broadband dielectric spectroscopy. The segmental dynamics below and above the melting temperature of PEO were significantly different in the presence of MWNTs.