Thermoelectric properties of Fe(0.2)Co(3.8)Sbi(12-x)Te(x) skutterudites

Skutterudites Fe(0.)2Co(3.8)Sb(12),Te-x (x = 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6) were synthesized by induction melting at 1273 K, followed by annealing at 923 K for 144 h. X-ray powder diffraction and electron microprobe analysis confirmed the presence of the skutterudite phase as the main phase. The temperature-dependent transport properties were measured for all the samples from 300 to 818 K. A positive Seebeck coefficient (holes are majority carriers) was obtained in Fe0.2Co3.8Sb 12 in the whole temperature range. Thermally excited carriers changed from n-type to p-type in Fe(0.)2Co(3.8)Sb(12),Te-x 19Te0.1 at 570 K, while in all the other samples, Fe(0.)2Co(3.8)Sb(12),Te-x (x = 0.2, 0.3, 0.4, 0.5, 0.6) exhibited negative Seebeck coefficients in the entire temperature range measured. Whereas for the alloys up to x = 0.2 (Fe(0.)2Co(3.8)Sb(12),Te-x ) the electrical resistivity decreased by charge compensation, it increased for x> 0.2 with an increase in Te content as a result of an increase in the electron concentration. The thermal conductivity decreased with Te substitution owing to carrier phonon scattering and point defect scattering. The maximum dimensionless thermoelectric figure of merit, ZT = 1.04 at 818 K, was obtained with an optimized Te content for Fe0.2Co3.8Sb1 1.5Te0.5 and a carrier concentration of,,J1/ =- 3.0 x 1020 CM-3 at room temperature. Thermal expansion (a = 8.8 x 10-6 K-1), as measured for Fe(0.)2Co(3.8)Sb(12),Te-x , compared well with that of undoped Co4Sb12. A further increase in the thermoelectric figure of merit up to ZT = 1.3 at 820 K was achieved for Fe(0.)2Co(3.8)Sb(12),Te-x , applying severe plastic deformation in terms of a high-pressure torsion process. (C) 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

CAVVA: Computational Affective Video-in-Video Advertising

Advertising is ubiquitous in the online community and more so in the ever-growing and popular online video delivery websites (e. g., YouTube). Video advertising is becoming increasingly popular on these websites. In addition to the existing pre-roll/post-roll advertising and contextual advertising, this paper proposes an in-stream video advertising strategy-Computational Affective Video-in-Video Advertising (CAVVA). Humans being emotional creatures are driven by emotions as well as rational thought. We believe that emotions play a major role in influencing the buying behavior of users and hence propose a video advertising strategy which takes into account the emotional impact of the videos as well as advertisements. Given a video and a set of advertisements, we identify candidate advertisement insertion points (step 1) and also identify the suitable advertisements (step 2) according to theories from marketing and consumer psychology. We formulate this two part problem as a single optimization function in a non-linear 0-1 integer programming framework and provide a genetic algorithm based solution. We evaluate CAVVA using a subjective user-study and eye-tracking experiment. Through these experiments, we demonstrate that CAVVA achieves a good balance between the following seemingly conflicting goals of (a) minimizing the user disturbance because of advertisement insertion while (b) enhancing the user engagement with the advertising content. We compare our method with existing advertising strategies and show that CAVVA can enhance the user's experience and also help increase the monetization potential of the advertising content.

Investigation on the Sr-doped ceria Ce1-xSrO2-delta (x=0.05-0.2) as an electrolyte for intermediate temperature SOFC

The effect of Sr doping in CeO2 for its use as solid electrolytes for intermediate temperature solid oxide fuel cells (IT-SOFCs) has been explored here. Ce1-xSrxO2-delta (x = 0.05-0.2) are successfully synthesized by citrate-complexation method. XRD, Raman, FT-IR, FE-SEM/EDX and electrochemical impedance spectra are used for structural and electrical characterizations. The formation of well crystalline cubic fluorite structured solid solution is observed for x = 0.05 based on XRD and Raman spectra. For compositions i.e., x > 0.05, however, a secondary phase of SrCeO3 is confirmed by the peak at 342 cm(-1) in Raman spectra. Although the oxygen ion conductivity was found to decrease with increase in x, based on ac-impedance studies, conductivity of Ce0.95Sr0.05O2-delta was found to be higher than of Ce0.95Gd0.1O2-delta and Ce0.8Gd0.2O2-delta. The decrease in conductivity of Ce1-xSrxO2-delta with increasing dopant concentration is ascribed to formation of impurity phase SrCeO3 as well as the formation of neutral associated pairs, Se `' Ce V-o. The activation energies are found to be 0.77, 0.83, 0.85 and 0.90 eV for x = 0.05, 0.1, 0.15 and 0.20, respectively. (C) 2014 Elsevier B.V. All rights reserved.

Enhanced superplasticity for (alpha plus beta)-hot rolled Ti-6Al-4V-0.1B alloy by means of dynamic globularization

Thermo-mechanically processed Ti-6Al-4V alloy, with (0.1 wt.%) and without boron addition, has been subjected to tensile test under superplastic deformation conditions (Temperature, T = 850 degrees C and initial strain rate, (epsilon) over dot = 3 x 10(-4) s(-1)). The boron added alloy exhibited higher elongation (similar to 430%) in comparison to the base alloy without boron (similar to 365%). Superior ductility of the boron added alloy has been attributed to an enhanced alpha/beta interfacial boundary sliding. This was caused by riotous dynamic globularization leading to the abundant presence of equiaxed primary alpha grains with refined sizes and narrow distribution in the deforming microstructure. Cavities do occur around TiB particles during deformation; the cavities are, however, extremely localized and do not cause macroscopic cracking. (C) 2014 Elsevier Ltd. All rights reserved.

Microstructural Features of Hot Deformed Nb-1Zr-0.1C Alloy

Niobium-based alloys are well-established refractory materials; as a result of their high melting temperature and good creep properties, these alloys find their applications in nuclear reactors. The present study deals with a microstructural response of these materials during hot working. The evolution of microstructure and texture during high-temperature deformation has been investigated in the temperature range 1500-1700A degrees C and strain rate range of 0.001-0.1 s(-1). For each deformed sample, the microstructure has been examined in detail. The microstructural features clearly revealed the formation of a substructure and the occurrence of dynamic recrystallization in a proper temperature-strain rate window. At low strain rates, the necklace structure formation was more prominent.

An alluaudite Na-2+Fe-2x(2-x)(SO4)(3)(x=0.2) derivative phase as insertion host for lithium battery

A new desodiated derivative compound, Na0.89Fe1.8(SO4)(3), was prepared by the chemical oxidation of alluaudite Na2.4Fe1.8(SO4)(3) Phase using NOBF4 as oxidant. The structure and valency of Fe were characterized by X-ray diffraction (XRD) and Fe-57 Mossbauer spectroscopy. Intercalation behavior of lithium ions in the structure of Na0.89Fe1.8(SO4)(3) was gauged by electrochemical analyses and ex-situ X-ray diffraction. A high capacity of 110 mAh g(-1) at 0.1 C was obtained with a good rate kinetics within a range of 0.1-10 C(1 C = 118 mAh g-1) involving a high Fe3+/Fe2+ redox potential of 3.75 V (vs. Li/Li+). These results confirmed that the Na2.4-delta Fe1.8(SO4)(3) framework was stable even after oxidation and forms a new competitive cathode for the reversible intercalation of lithium ions. (C) 2014 Elsevier B.V. All rights reserved.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.