Electrocatalysis and redox behavior of Pt(2+) ion in CeO(2) and Ce(0.85)Ti(0.15)O(2): XPS evidence of participation of lattice oxygen for high activity

Electronic states of CeO(2), Ce(1 -aEuro parts per thousand x) Pt (x) O(2 -aEuro parts per thousand delta) , and Ce(1 -aEuro parts per thousand x -aEuro parts per thousand y) Ti (y) Pt (x) O(2 -aEuro parts per thousand delta) electrodes have been investigated by X-ray photoelectron spectroscopy as a function of applied potential for oxygen evolution and formic acid and methanol oxidation. Ionically dispersed platinum in Ce(1 -aEuro parts per thousand x) Pt (x) O(2 -aEuro parts per thousand delta) and Ce(1 -aEuro parts per thousand x -aEuro parts per thousand y) Ti (y) Pt (x) O(2 -aEuro parts per thousand delta) is active toward these reactions compared with CeO(2) alone. Higher electrocatalytic activity of Pt(2+) ions in CeO(2) and Ce(1 -aEuro parts per thousand x) Ti (x) O(2) compared with the same amount of Pt(0) in Pt/C is attributed to Pt(2+) ion interaction with CeO(2) and Ce(1 -aEuro parts per thousand x) Ti (x) O(2) to activate the lattice oxygen of the support oxide. Utilization of this activated lattice oxygen has been demonstrated in terms of high oxygen evolution in acid medium with these catalysts. Further, ionic platinum in CeO(2) and Ce(1 -aEuro parts per thousand x) Ti (x) O(2) does not suffer from CO poisoning effect unlike Pt(0) in Pt/C due to participation of activated lattice oxygen which oxidizes the intermediate CO to CO(2). Hence, higher activity is observed toward formic acid and methanol oxidation compared with same amount of Pt metal in Pt/C.

Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios

Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.

Direct evidence of redox interaction between metal ion and support oxide in Ce(0.98)Pd(0.02)O(2-delta) by a combined electrochemical and XPS study

A combined electrochemical method and X-ray photo electron spectroscopy (XPS) has been utilized to understand the Pd(2+)/CeO(2) interaction in Ce(1-x)Pd(x)O(2-delta) (x = 0.02). A constant positive potential (chronoamperometry) is applied to Ce(0.98)Pd(0.02)O(2-delta) working electrode which causes Ce(4+) to reduce to Ce(3+) to the extent of similar to 35%, while Pd remains in the +2 oxidation state. Electrochemically cycling this electrode between 0.0-1.2 V reverts back to the original state of the catalyst. This reversibility is attributed to the reversible reduction of Ce(4+) to Ce(3+) state. CeO(2) electrode with no metal component reduces to CeO(2-y) (y similar to 0.4) after applying 1.2 V which is not reversible and the original composition of CeO(2) cannot be brought back in any electrochemical condition. During the electro-catalytic oxygen evolution reaction at a constant 1.2 V for 1000 s, Ce(0.98)Pd(0.02)O(2-delta) reaches a steady state composition with Pd in the +2 states and Ce(4+) : Ce(3+) in the ratio of 0.65 : 0.35. This composition can be denoted as Ce(0.63)(4+)Ce(0.35)(4+)Pd(0.02)O(2-delta-y) (y similar to 0.17). When pure CeO(2) is put under similar electrochemical condition, it never reaches the steady state composition and reduces almost to 85%. Thus, Ce(0.98)Pd(0.02)O(2-delta) forms a stable electrode for the electro-oxidation of H(2)O to O(2) unlike CeO(2) due to the metal support interaction.

Griffiths phase-like behavior and spin-phonon coupling in double perovskite Tb(2)NiMnO(6)

The Griffiths phase-like features and the spin-phonon coupling effects observed in Tb(2)NiMnO(6) are reported. The double perovskite compound crystallizes in monoclinic P2(1)/n space group and exhibits a magnetic phase transition at T(c) similar to 111 K as an abrupt change in magnetization. A negative deviation from ideal Curie-Weiss law exhibited by 1/chi(T) curves and less-than-unity susceptibility exponents from the power-law analysis of inverse susceptibility are reminiscent of Griffiths phase-like features. Arrott plots derived from magnetization isotherms support the inhomogeneous nature of magnetism in this material. The observed effects originate from antiferromagnetic interactions that arise from inherent disorder in the system. Raman scattering experiments display no magnetic-order-induced phonon renormalization below Tc in Tb(2)NiMnO(6), which is different from the results observed in other double perovskites and is correlated to the smaller size of the rare earth. The temperature evolution of full-width-at-half-maximum for the stretching mode at 645 cm(-1) presents an anomaly that coincides with the magnetic transition temperature and signals a close connection between magnetism and lattice in this material. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3671674]

Dynamical behavior in the nonlinear rheology of surfactant solutions

Several surfactant molecules self-assemble in solution to form long, flexible wormlike micelles which get entangled with each other, leading to viscoelastic gel phases. We discuss our recent work on the rheology of such a gel formed in the dilute aqueous solutions of a surfactant CTAT. In the linear rheology regime, the storage modulus G′(ω) and loss modulus G″(ω) have been measured over a wide frequency range. In the nonlinear regime, the shear stress σ shows a plateau as a function of the shear rate math above a certain cutoff shear rate mathc. Under controlled shear rate conditions in the plateau regime, the shear stress and the first normal stress difference show oscillatory time-dependence. The analysis of the measured time series of shear stress and normal stress has been done using several methods incorporating state space reconstruction by embedding of time delay vectors. The analysis shows the existence of a finite correlation dimension and a positive Lyapunov exponent, unambiguously implying that the dynamics of the observed mechanical instability can be described by that of a dynamical system with a strange attractor of dimension varying from 2.4 to 2.9.

Synthesis, Spectral Characterization, Crystal Structure and Thermal Behavior of Tert-butyl 2,2-bis(2,4-dinitrophenyl)ethanoate

Tert-butyl 2,2-bis(2,4-dinitrophenyl)ethanoate was prepared from the ethanolic solution of 1-chloro-2,4-dinitrobenzene, tert-butyl 3-oxobutanoate and triethylamine. Acetyl group in tert-butyl 3-oxobutanoate has cleaved off during the formation of the title molecule. UV-VIS, IR, 1H NMR, 13C NMR, Proton-Proton COSY data and single crystal XRD results support the proposed structure. Flammability test, impact sensitivity test and TG/DTA studies at different heating rates on the synthesized molecule imply that it is an insensitive high energy density material.

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.

A study on the usefulness of Support Vector Machines for the realtime computational simulation of soft biological organs

Realistic and realtime computational simulation of soft biological organs (e.g., liver, kidney) is necessary when one tries to build a quality surgical simulator that can simulate surgical procedures involving these organs. Since the realistic simulation of these soft biological organs should account for both nonlinear material behavior and large deformation, achieving realistic simulations in realtime using continuum mechanics based numerical techniques necessitates the use of a supercomputer or a high end computer cluster which are costly. Hence there is a need to employ soft computing techniques like Support Vector Machines (SVMs) which can do function approximation, and hence could achieve physically realistic simulations in realtime by making use of just a desktop computer. Present work tries to simulate a pig liver in realtime. Liver is assumed to be homogeneous, isotropic, and hyperelastic. Hyperelastic material constants are taken from the literature. An SVM is employed to achieve realistic simulations in realtime, using just a desktop computer. The code for the SVM is obtained from [1]. The SVM is trained using the dataset generated by performing hyperelastic analyses on the liver geometry, using the commercial finite element software package ANSYS. The methodology followed in the present work closely follows the one followed in [2] except that [2] uses Artificial Neural Networks (ANNs) while the present work uses SVMs to achieve realistic simulations in realtime. Results indicate the speed and accuracy that is obtained by employing the SVM for the targeted realistic and realtime simulation of the liver.

Universal flame propagation behavior in packed bed of biomass

This article aims at seeking the universal behavior of propagation rate variation with air superficial velocity (V-s) in a packed bed of a range of biomass particles in reverse downdraft mode while also resolving the differing and conflicting explanations in the literature. Toward this, measurements are made of exit gas composition, gas phase and condensed phase surface temperature (T-g and T-s), and reaction zone thickness for a number of biomass with a range of properties. Based on these data, two regimes are identified: gasificationvolatile oxidation accompanied by char reduction reactions up to 16 +/- 1cm/s of V-s and above this, and char oxidationsimultaneous char oxidation and gas phase combustion. In the gasification regime, the measured T-s is less than T-g; a surface heat balance incorporating a diffusion controlled model for flaming combustion gives and matches with the experimental results to within 5%. In the char oxidation regime, T-g and T-s are nearly equal and match with the equilibrium temperature at that equivalence ratio. Drawing from a recent study of the authors, the ash layer over the oxidizing char particle is shown to play a critical role in regulating the radiation heat transfer to fresh biomass in this regime and is shown to be crucial in explaining the observed propagation behavior. A simple model based on radiation-convection balance that tracks the temperature-time evolution of a fresh biomass particle is shown to support the universal behavior of the experimental data on reaction front propagation rate from earlier literature and the present work for biomass with ash content up to 10% and moisture fraction up to 10%. Upstream radiant heat transfer from the ash-laden hot char modulated by the air flow is shown to be the dominant feature of this model.

Expansions of tau hadronic spectral function moments in a nonpower QCD perturbation theory with tamed large order behavior

The moments of the hadronic spectral functions are of interest for the extraction of the strong coupling alpha(s) and other QCD parameters from the hadronic decays of the tau lepton. Motivated by the recent analyses of a large class of moments in the standard fixed-order and contour-improved perturbation theories, we consider the perturbative behavior of these moments in the framework of a QCD nonpower perturbation theory, defined by the technique of series acceleration by conformal mappings, which simultaneously implements renormalization-group summation and has a tame large-order behavior. Two recently proposed models of the Adler function are employed to generate the higher-order coefficients of the perturbation series and to predict the exact values of the moments, required for testing the properties of the perturbative expansions. We show that the contour-improved nonpower perturbation theories and the renormalization-group-summed nonpower perturbation theories have very good convergence properties for a large class of moments of the so-called ``reference model,'' including moments that are poorly described by the standard expansions. The results provide additional support for the plausibility of the description of the Adler function in terms of a small number of dominant renormalons.

Dynamic state estimation for identifying earthquake support motions in instrumented structures

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

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.

Compressive flow behavior of Al-Si based alloy: Role of heat treatment

The flow characteristics of a near eutectic Al-Si based cast alloy have been examined in compression at strain rates varying from 3 x 10(-4) to 10(2) s(-1) and at three different temperatures, i.e., room temperature (RT), 100 degrees C and 200 degrees C. The dependence of the flow behavior on heat treatment is studied by testing the alloy in non-heat treated (NHT) and heat treated (HT) conditions. The heat treatment has strong influence on strain rate sensitivity (SRS), strength and work hardening behavior of the alloy. It is observed that the strength of the alloy increases with increase in strain rate and it increases more rapidly above the strain rate of 10(-1) s(-1) in HT condition at all the temperatures, and at 100 degrees C and 200 degrees C in NHT condition. The thermally dependent process taking place in the HT matrix is responsible for the observed greater SRS in HT condition. The alloy in HT condition exhibits a larger work hardening rate than in NHT condition during initial stages of straining. However, the hardening rate decreases more sharply at higher strains in HT condition due to precipitate shearing and higher rate of Si particle fracture. Thermal hardening is observed at 200 degrees C in NHT condition due to precipitate formation, which results in increased SRS at higher temperatures. Thermal softening is observed in HT condition at 200 C due to precipitate coarsening, which leads to a decrease in SRS at higher temperatures. Stress simulations by a finite element method support the experimentally observed particle and matrix fracture behavior. A negative SRS and serrated flow are observed in the lower strain rate regime (3 x 10(-4)-10(-2) s(-1)) at RT and 100 degrees C, in both NHT and HT conditions. The observations show that both dynamic strain aging (DSA) and precipitate shearing play a role in serrated flow. (C) 2015 Elsevier B.V. All rights reserved.

Role of Si modification on the compressive flow behavior of Al-Si based alloy

The flow characteristics of a near-eutectic heat-treated Al-Si based cast alloy have been examined in compression at strain rates varying from 3 x 10(-4) to 10(2) s(-1) and at three different temperatures, i.e., room temperature (RT), 100 degrees C and 200 degrees C. The dependence of flow behavior on modification is examined by testing the alloy in both the unmodified and modified conditions. Modification has strong influence on strain rate sensitivity (SRS), strength and work hardening behavior of the alloy. The strength of the alloy is found to increase with increase in strain rate for both the conditions. The increase is more rapid above the strain rate of 10(-1) s(-1) for the unmodified alloy at all the temperatures. This rapid increase is observed at 1 s(-1) at RT and 100 degrees C, and at 10(-2) s(-1) at 200 degrees C for the modified alloy. The thermally dependent process of the Al matrix is rate controlling in the unmodified alloy. On the other hand, the thermally dependent process of both Al matrix and Si particles are rate controlling, which is responsible for the higher strain rate sensitivity (SRS) in the modified alloy. The unmodified alloy exhibits a larger work hardening rate than the modified alloy during the initial stages of straining due to fiber loading of unmodified Si particles. However, the hardening rate decreases sharply at higher strains for the unmodified alloy due to a higher rate of Si particle fracture. Thermal softening is observed for both alloys at 200 degrees C due to precipitate coarsening, which leads to a decrease in SRS at higher temperatures. Stress simulations by microstructure based finite element method support the experimentally observed particle and matrix fracture behavior. Negative SRS and serrated flow are observed at lower strain rate regime (3 x 10(-4) to 10(-2) s(-1)) at RT and 100 degrees C, in both alloys. The critical onset strain is found to be lower and the magnitude of serration is found to be higher for the modified alloy, which suggests that, in addition to dynamic strain aging, Si particle size and morphology also play a role in serrated flow. (C) 2015 Elsevier Inc All rights reserved.

Asymptotic behavior and interpretation of virtual states: The effects of confinement and of basis sets

A real-space high order finite difference method is used to analyze the effect of spherical domain size on the Hartree-Fock (and density functional theory) virtual eigenstates. We show the domain size dependence of both positive and negative virtual eigenvalues of the Hartree-Fock equations for small molecules. We demonstrate that positive states behave like a particle in spherical well and show how they approach zero. For the negative eigenstates, we show that large domains are needed to get the correct eigenvalues. We compare our results to those of Gaussian basis sets and draw some conclusions for real-space, basis-sets, and plane-waves calculations. (C) 2016 AIP Publishing LLC.