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Well-crystallized anatase and mixed (anatase-rutile) phase TiO2 thin films were deposited by DC magnetron sputtering technique at various DC powers in the range of 80-140 W. Pure anatase phase was observed in the TiO2 films deposited at low power of 80 W. Films deposited at 120 W were composed of both anatase and rutile phases. At higher power of 140 W, the films are rutile dominated and the rutile percentage increased from 0 to 82% with increase of DC power. The same results of phase change were confirmed by Raman studies. The surface morphology of the TiO2 films showed that the density of the films increased with increase of sputter power. The optical band gap of the films varied from 3.35 to 3.14 eV with increase of DC power. The photocatalytic activity of the TiO2 films increased with increasing DC power up to 120 W and after that it decreases. We found that the TiO2 films deposited at 120 W with 48% of rutile phase, exhibited high photocatalytic activity (43% of degradation) under UV light compared with other TiO2 films. After loading the optimized Ag nanoparticles on the mixed phase TiO2 films, the photocatalytic activity shifted from UV to visible region with enhancement of photocatalytic activity (55% of degradation). (C) 2015 Elsevier B.V. All rights reserved.

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This paper presents the design and implementation of PolyMage, a domain-specific language and compiler for image processing pipelines. An image processing pipeline can be viewed as a graph of interconnected stages which process images successively. Each stage typically performs one of point-wise, stencil, reduction or data-dependent operations on image pixels. Individual stages in a pipeline typically exhibit abundant data parallelism that can be exploited with relative ease. However, the stages also require high memory bandwidth preventing effective utilization of parallelism available on modern architectures. For applications that demand high performance, the traditional options are to use optimized libraries like OpenCV or to optimize manually. While using libraries precludes optimization across library routines, manual optimization accounting for both parallelism and locality is very tedious. The focus of our system, PolyMage, is on automatically generating high-performance implementations of image processing pipelines expressed in a high-level declarative language. Our optimization approach primarily relies on the transformation and code generation capabilities of the polyhedral compiler framework. To the best of our knowledge, this is the first model-driven compiler for image processing pipelines that performs complex fusion, tiling, and storage optimization automatically. Experimental results on a modern multicore system show that the performance achieved by our automatic approach is up to 1.81x better than that achieved through manual tuning in Halide, a state-of-the-art language and compiler for image processing pipelines. For a camera raw image processing pipeline, our performance is comparable to that of a hand-tuned implementation.

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A combustion technique is used to study the synthesis of carbon nano tubes from waste plastic as a precursor and Ni/Mo/MgO as a catalyst. The catalytic activity of three components Ni, Mo, MgO is measured in terms of amount of carbon product obtained. Different proportions of metal ions are optimized using mixture experiment in Design expert software. D-optimal design technique is adopted due to nonsimplex region and presence of constraints in the mixture experiment. The activity of the components is observed to be interdependent and the component Ni is found to be more effective. The catalyst containing Ni0.8Mo0.1MgO0.1 yields more carbon product. The structure of catalyst and CNTs are studied by using SEM, XRD, and Raman spectroscopy. SEM analysis shows the formation of longer CNTs with average diameter of 40-50 nm.

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A new approach is proposed to estimate the thermal diffusivity of optically transparent solids at ambient temperature based on the velocity of an effective temperature point (ETP), and by using a two-beam interferometer the proposed concept is corroborated. 1D unsteady heat flow via step-temperature excitation is interpreted as a `micro-scale rectilinear translatory motion' of an ETP. The velocity dependent function is extracted by revisiting the Fourier heat diffusion equation. The relationship between the velocity of the ETP with thermal diffusivity is modeled using a standard solution. Under optimized thermal excitation, the product of the `velocity of the ETP' and the distance is a new constitutive equation for the thermal diffusivity of the solid. The experimental approach involves the establishment of a 1D unsteady heat flow inside the sample through step-temperature excitation. In the moving isothermal surfaces, the ETP is identified using a two-beam interferometer. The arrival-time of the ETP to reach a fixed distance away from heat source is measured, and its velocity is calculated. The velocity of the ETP and a given distance is sufficient to estimate the thermal diffusivity of a solid. The proposed method is experimentally verified for BK7 glass samples and the measured results are found to match closely with the reported value.

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We discuss the potential application of high dc voltage sensing using thin-film transistors (TFTs) on flexible substrates. High voltage sensing has potential applications for power transmission instrumentation. For this, we consider a gate metal-substrate-semiconductor architecture for TFTs. In this architecture, the flexible substrate not only provides mechanical support but also plays the role of the gate dielectric of the TFT. Hence, the thickness of the substrate needs to be optimized for maximizing transconductance, minimizing mechanical stress, and minimizing gate leakage currents. We discuss this optimization, and develop n-type and p-type organic TFTs using polyvinyldene fluoride as the substrate-gate insulator. Circuits are also realized to achieve level shifting, amplification, and high drain voltage operation.

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Primary and secondary zinc-air batteries based on ceramic, stable, one dimensional titanium carbonitride (TiCN) nanostructures are reported. The optimized titanium carbonitride composition by density functional theory reveals their good activity towards the oxygen reduction reaction (ORR). Electrochemical measurements show their superior performance for the ORR in alkaline media coupled with favourable kinetics. The nanostructured TiCN lends itself amenable to be used as an air cathode material in primary and rechargeable zinc-air batteries. The battery performance and cyclability are found to be good. Further, we have demonstrated a gel-based electrolyte for rechargeable zinc-air batteries based on a TiCN cathode under ambient, atmospheric conditions without any oxygen supply from a cylinder. The present cell can work at current densities of 10-20 mA cm(2) (app. 10 000 mA g(-1) of TiCN) for several hours (63 h in the case of 10 mA cm(-2)) with a charge retention of 98%. The low cost, noble metal-free, mechanically stable and corrosion resistant TiCN is a very good alternative to Pt for metal-air battery chemistry.

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Small size actuators (8 mm x 1 mm), IPMNC (RuO2/Nafion) and IPMNC (LbL/CNC) are studied for flapping at the frequency of insects and compared to Platinum IPMC-Pt. Flapping wing actuators based on IPMNC (RuO2/Nafion) are modeled with the size of three dragonfly species. To achieve maximum actuation performance with Sympetrum Frequens scale actuator with optimized Young's modulus, the effect of variation of thickness of electrode and Nafion region of Sympetrum Frequens scale actuator is studied. A trade-off in the electrode thickness and Young's modulus for dragonfly size IPMNC-RuO2/Nafion actuator is essential to achieve the desirable flapping performance.

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We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.