Effect of High-Pressure Torsion on Texture, Microstructure, and Raman Spectroscopy: Case Study of Fe- and Te-Substituted CoSb3

Fe0.05Co0.95Sb2.875Te0.125, a double-element-substituted skutterudite, was prepared by induction melting, annealing, and hot pressing (HP). The hot-pressed sample was subjected to high-pressure torsion (HPT) with 4 GPa pressure at 673 K. X-ray diffraction was performed before and after HPT processing of the sample; the skutterudite phase was observed as a main phase, but an additional impurity phase (CoSb2) was observed in the HPT-processed sample. Surface morphology was determined by high-resolution scanning electron microscopy. In the HP sample, coarse grains with sizes in the range of approximately 100 nm to 300 nm were obtained. They changed to fine grains with a reduction in grain size to 75 nm to 125 nm after HPT due to severe plastic deformation. Crystallographic texture, as measured by x-ray diffraction, indicated strengthening of (112), (102) poles and weakening of the (123) pole of the HPT-processed sample. Raman-active vibrational modes showed a peak position shift towards the lower energy side, indicating softening of the modes after HPT. The distortion of the rectangular Sb-Sb rings leads to broadening of Sb-Sb vibrational modes due to local strain fluctuation. In the HPT process, a significant effect on the shorter Sb-Sb bond was observed as compared with the longer Sb-Sb bond.

Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle

The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.

Characterizing the pocketome of Mycobacterium tuberculosis and application in rationalizing polypharmacological target selection

Polypharmacology is beginning to emerge as an important concept in the field of drug discovery. However, there are no established approaches to either select appropriate target sets or design polypharmacological drugs. Here, we propose a structural-proteomics approach that utilizes the structural information of the binding sites at a genome-scale obtained through in-house algorithms to characterize the pocketome, yielding a list of ligands that can participate in various biochemical events in the mycobacterial cell. The pocket-type space is seen to be much larger than the sequence or fold-space, suggesting that variations at the site-level contribute significantly to functional repertoire of the organism. All-pair comparisons of binding sites within Mycobacterium tuberculosis (Mtb), pocket-similarity network construction and clustering result in identification of binding-site sets, each containing a group of similar binding sites, theoretically having a potential to interact with a common set of compounds. A polypharmacology index is formulated to rank targets by incorporating a measure of druggability and similarity to other pockets within the proteome. This study presents a rational approach to identify targets with polypharmacological potential along with possible drugs for repurposing, while simultaneously, obtaining clues on lead compounds for use in new drug-discovery pipelines.

Improvement of electrical conductivity in Pb0.96-yMn0.04SnyTe alloys for high temperature thermoelectric applications

Lead-tin-telluride is a well-known thermoelectric material in the temperature range 350-750 K. Here, this alloy doped with manganese (Pb0.96-yMn0.04SnyTe) was prepared for different amounts of tin. X-ray diffraction showed a decrease of the lattice constant with increasing tin content, which indicated solid solution formation. Microstructural analysis showed a wide distribution of grain sizes from <1 mu m to 10 mm and the presence of a SnTe rich phase. All the transport properties were measured in the range of 300-720 K. The Seebeck coefficient showed that all the samples were p-type indicating holes as dominant carriers in the measurement range. The magnitude increased systematically on reduction of the Sn content due to possible decreasing hole concentration. Electrical conductivity showed the degenerate nature of the samples. Large values of the electrical conductivity could have possibly resulted from a large hole concentration due to a high Sn content and secondly, due to increased mobility by sp-d orbital interaction between the Pb1-ySnyTe sublattice and the Mn2+ ions. High thermal conductivity was observed due to higher electronic contribution, which decreased systematically with decreasing Sn content. The highest zT = 0.82 at 720 K was obtained for the alloy with the lowest Sn content (y = 0.56) due to the optimum doping level.

Design and Development of Thermoelectric Generator

In this paper we discuss the fabrication, working and characteristics of a thermoelectric generator made up of p and n type semiconductor materials. The device consists of Fe0.2Co3.8Sb11.5Te0.5 (zT = 1.04 at 818 K) as the n-type and Zn4Sb3 (zT= 0.8 at 550 K) as the p-type material synthesized by vacuum hot press method. Carbon paste has been used to join the semiconductor legs to metal (Molybdenum) electrodes to reduce the contact resistance. The multi-couple (4 legs) generator results a maximum output power of 1.083 mW at a temperature difference of 240 K between the hot and cold sides. In this investigation, an I-V characteristic, maximum output power of the thermoelectric module is presented. The efficiency of thermoelectric module is obtained as eta= 0.273 %.

Elastic Properties Of Sulphur And Selenium Doped Ternary PbTe Alloys By First Principles

Lead telluride (PbTe) is an established thermoelectric material which can be alloyed with sulphur and selenium to further enhance the thermoelectric properties. Here, a first principles study of ternary alloys PbSxTe(1-x) and PbSexTe(1-x) (0 <= x <= 1) based on the Virtual Crystal Approximation (VCA) is presented for different ratios of the isoelectronic atoms in each series. Equilibrium lattice parameters and elastic constants have been calculated and compared with the reported data. Anisotropy parameter calculated from the stiffness constants showed a slight improvement in anisotropy of elastic properties of the alloys over undoped PbTe. Furthermore, the alloys satisfied the predicted stability criteria from the elastic constants, showing stable structures, which agreed with the previously reported experimental results.

High Temperature XRD of Cu2.1Zn0.9SnSe4

Quaternary compound with chemical composition Cu2.1ZnSnSe4 is prepared by solid state synthesis. High temperature XRD (X-Ray Diffraction) of this compound is used in studying the effect of temperature on lattice parameters and thermal expansion coefficients. Thermal expansion coefficient is one of the important quantities in evaluating the Gruneisen parameter which further useful in determining the lattice thermal conductivity of the material. The high temperature XRD of the material revealed that the lattice parameters as well as thermal expansion coefficients of the material increased with increase in temperature which confirms the presence of anharmonicty.

Spectrum of the three-dimensional fuzzy well

We develop the formalism of quantum mechanics on three-dimensional fuzzy space and solve the Schrodinger equation for the free particle, finite and infinite fuzzy wells. We show that all results reduce to the appropriate commutative limits. A high energy cut-off is found for the free particle spectrum, which also results in the modification of the high energy dispersion relation. An ultra-violet/infra-red duality is manifest in the free particle spectrum. The finite well also has an upper bound on the possible energy eigenvalues. The phase shifts due to scattering around the finite fuzzy potential well are calculated.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Logarithmic corrections to extremal black hole entropy in N=2, 4 and 8 supergravity

We compute the logarithmic correction to black hole entropy about exponentially suppressed saddle points of the Quantum Entropy Function corresponding to Z(N) orbifolds of the near horizon geometry of the extremal black hole under study. By carefully accounting for zero mode contributions we show that the logarithmic contributions for quarter-BPS black holes in N = 4 supergravity and one-eighth BPS black holes in N = 8 supergravity perfectly match with the prediction from the microstate counting. We also find that the logarithmic contribution for half-BPS black holes in N = 2 supergravity depends non-trivially on the Z(N) orbifold. Our analysis draws heavily on the results we had previously obtained for heat kernel coefficients on Z(N) orbifolds of spheres and hyperboloids in arXiv:1311.6286 and we also propose a generalization of the Plancherel formula to Z(N) orbifolds of hyperboloids to an expression involving the Harish-Chandra character of sl (2, R), a result which is of possible mathematical interest.

Quantum entropy for the fuzzy sphere and its monopoles

Using generalized bosons, we construct the fuzzy sphere S-F(2) and monopoles on S-F(2) in a reducible representation of SU(2). The corresponding quantum states are naturally obtained using the GNS-construction. We show that there is an emergent nonabelian unitary gauge symmetry which is in the commutant of the algebra of observables. The quantum states are necessarily mixed and have non-vanishing von Neumann entropy, which increases monotonically under a bistochastic Markov map. The maximum value of the entropy has a simple relation to the degeneracy of the irreps that constitute the reducible representation that underlies the fuzzy sphere.

Rollover-Preventive Force Synthesis at Active Suspensions in a Vehicle Performing a Severe Maneuver With Wheels Lifted Off

Among the intelligent safety technologies for road vehicles, active suspensions controlled by embedded computing elements for preventing rollover have received a lot of attention. The existing models for synthesizing and allocating forces in such suspensions are conservatively based on the constraints that are valid until no wheels lift off the ground. However, the fault tolerance of the rollover-preventive systems can be enhanced if the smart/active suspensions can intervene in the more severe situation in which the wheels have just lifted off the ground. The difficulty in computing control in the last situation is that the vehicle dynamics then passes into the regime that yields a model involving disjunctive constraints on the dynamics. Simulation of dynamics with disjunctive constraints in this context becomes necessary to estimate, synthesize, and allocate the intended hardware realizable forces in an active suspension. In this paper, we give an algorithm for the previously mentioned problem by solving it as a disjunctive dynamic optimization problem. Based on this, we synthesize and allocate the roll-stabilizing time-dependent active suspension forces in terms of sensor output data. We show that the forces obtained from disjunctive dynamics are comparable with existing force allocations and, hence, are possibly realizable in the existing hardware framework toward enhancing the safety and fault tolerance.

Rapid Characterization of Molecular Diffusion by NMR Spectroscopy

An NMR-based approach for rapid characterization of translational diffusion of molecules has been developed. Unlike the conventional method of acquiring a series of 2D C-13 and H-1 spectra, the proposed approach involves a single 2D NMR spectrum, which can be acquired in minutes. Using this method, it was possible to detect the presence of intermediate oligomeric species of diphenylalanine in solution during the process of its selfassembly to form nanotubular structures.

ELLIPSE FITTING USING FINITE RATE OF INNOVATION PRINCIPLES

We address the problem of parameter estimation of an ellipse from a limited number of samples. We develop a new approach for solving the ellipse fitting problem by showing that the x and y coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals. Uniform samples of x and y coordinate functions of the ellipse are modeled as a sum of weighted complex exponentials, for which we propose an efficient annihilating filter technique to estimate the ellipse parameters from the samples. The FRI framework allows for estimating the ellipse parameters reliably from partial or incomplete measurements even in the presence of noise. The efficiency and robustness of the proposed method is compared with state-of-art direct method. The experimental results show that the estimated parameters have lesser bias compared with the direct method and the estimation error is reduced by 5-10 dB relative to the direct method.

ON THE ROLE OF THE HILBERT TRANSFORM IN BOOSTING THE PERFORMANCE OF THE ANNIHILATING FILTER

We consider the problem of parameter estimation from real-valued multi-tone signals. Such problems arise frequently in spectral estimation. More recently, they have gained new importance in finite-rate-of-innovation signal sampling and reconstruction. The annihilating filter is a key tool for parameter estimation in these problems. The standard annihilating filter design has to be modified to result in accurate estimation when dealing with real sinusoids, particularly because the real-valued nature of the sinusoids must be factored into the annihilating filter design. We show that the constraint on the annihilating filter can be relaxed by making use of the Hilbert transform. We refer to this approach as the Hilbert annihilating filter approach. We show that accurate parameter estimation is possible by this approach. In the single-tone case, the mean-square error performance increases by 6 dB for signal-to-noise ratio (SNR) greater than 0 dB. We also present experimental results in the multi-tone case, which show that a significant improvement (about 6 dB) is obtained when the parameters are close to 0 or pi. In the mid-frequency range, the improvement is about 2 to 3 dB.