920 resultados para Strain Sensing
Resumo:
The chiral sensing property of helicin (the derivative of natural product obtained by partial oxidation of salicin, extracted from willow tree (Salix helix)) is reported. The use of helicin as a chiral derivatizing agent for the discrimination of amines and amino alcohols is convincingly established using H-1 NMR spectroscopy. The large chemical shift separation achieved between the discriminated peaks facilitated the accurate quantification of enantiomeric composition. The consistent trend observed in the shifting of imine proton peak (Delta delta) of helicin in all the derivatized molecules might aid the determination of spatial configuration. (C) 2015 Elsevier B.V. All rights reserved.
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Ni2+ ion induced unusual conductivity reversal and an enhancement in the gas sensing properties of ferrites based gas sensors, is reported. The Co1-xNixFe2O4 (for x = 0, 0.5 and 1) nanoparticles were synthesized by wet chemical co-precipitation method and gas sensing properties were studied as a function of composition and temperature. The structural, morphological and microstructural characterization revealed crystallite size of in the range 10-20 nm with porous morphology consisting of nano-sized grains. The Energy Dispersive X-ray (EDX) mapping confirms homogeneous distribution of Co, Ni, Fe and O elements in the ferrites. The non-stoichiometry of the inverse spinel type ferrites and the relative concentration of Ni3+/Co3+ defects were studied using X-ray photoelectron spectroscopy. It is found that the addition of Ni2+ ions into cobalt ferrite shows preferred selectivity towards CO gas at high temperature (325 degrees C) and ethanol gas at low temperature (250 degrees C), unlike undoped cobalt ferrite or undoped nickel ferrite, which show similar response for both these gases. Moreover, an unusual conductivity reversal is observed, except cobalt ferrite due to the difference in reactivity of the gases as well as characteristic non-stoichiometry of ferrites. This behavior is highly gas ambient dependent and hence can be well-exploited for selective detection of gases. (C) 2015 Elsevier B.V. All rights reserved.
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Ultralight and macroporous three-dimensional reduced graphene oxide (rGO) foams are prepared by lyophilization (freeze-drying) technique to avoid a conventional template method. This method allows tailoring the porosity of the foams by varying the weight percentages of graphene oxide dispersions in water. Three different rGO foams of 0.2, 0.5 and 1.0 wt% are used for NO2 sensing. Sensing response from the tailored structure of rGO is found to be directly related to the density. A maximum of 20% sensing response is observed for a higher porosity of the structure, better than the known results so far on graphene foams in the literature. (C) 2015 Elsevier B.V. All rights reserved.
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Aside of size and shape, the strain induced by the mismatch of lattice parameters between core and shell in the nanocrystalline regime is an additional degree of freedom to engineer the electron energy levels. Herein, CdS/ZnS core/shell nanocrystals (NCs) with shell thickness up to four monolayers are studied. As a manifestation of strain, the low temperature radiative lifetime measurements indicate a reduction in Stokes shift from 36 meV for CdS to 5 meV for CdS/ZnS with four monolayers of overcoating. Concomitant crossover of S- and P-symmetric hole levels is observed which can be understood in the framework of theoretical calculations predicting flipping the hierarchy of ground hole state by the strain in CdS NCs. Furthermore, a nonmonotonic variation of higher energy levels in strained CdS NCs is discussed.
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We report the implementation of a micro-patterned, glass-based photonic sensing element that is capable of label-free biosensing. The diffractive optical analyzer is based on the differential response of diffracted orders to bulk as well as surface refractive index changes. The differential read-out suppresses signal drifts and enables time-resolved determination of refractive index changes in the sample cell. A remarkable feature of this device is that under appropriate conditions, the measurement sensitivity of the sensor can be enhanced by more than two orders of magnitude due to interference between multiply reflected diffracted orders. A noise-equivalent limit of detection (LoD) of 6 x 10(-7) was achieved with this technique with scope for further improvement.
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This paper considers the problem of energy-based, Bayesian spectrum sensing in cognitive radios under various fading environments. Under the well-known central limit theorem based model for energy detection, we derive analytically tractable expressions for near-optimal detection thresholds that minimize the probability of error under lognormal, Nakagami-m, and Weibull fading. For the Suzuki fading case, a generalized gamma approximation is provided, which saves on the computation of an integral. In each case, the accuracy of the theoretical expressions as compared to the optimal thresholds are illustrated through simulations.
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In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.
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Using in situ, high-speed imaging of a hard wedge sliding against pure aluminum, and image analysis by particle image velocimetry, the deformation field in sliding is mapped at high resolution. This model system is representative of asperity contacts on engineered surfaces and die-workpiece contacts in deformation and machining processes. It is shown that large, uniform plastic strains of 1-5 can be imposed at the Al surface, up to depths of 500 mu m, under suitable sliding conditions. The spatial strain and strain rate distributions are significantly influenced by the initial deformation state of the Al, e.g., extent of work hardening, and sliding incidence angle. Uniform straining occurs only under conditions of steady laminar flow in the metal. Large pre-strains and higher sliding angles promote breakdown in laminar flow due to surface fold formation or flow localization in the form of shear bands, thus imposing limits on uniform straining by sliding. Avoidance of unsteady sliding conditions, and selection of parameters like sliding angle, thus provides a way to control the deformation field. Key characteristics of the sliding deformation such as strain and strain rate, laminar flow, folding and prow formation are well predicted by finite element simulation. The deformation field provides a quantitative basis for interpreting wear particle formation. Implications for engineering functionally graded surfaces, sliding wear and ductile failure in metals are discussed.
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Investigations on chromium niobate (CrNbO4) have shown that the material responds to a wide hydrogen concentration range of 0.01%-0.40% at 613 K. The conductivity of CrNbO4 is independent of oxygen partial pressure and offers to be a promising candidate for monitoring H-2 in radioactive spent fuel storage facilities. Reduction of metal ions to lower valence states during hydrogen sensing was evidenced by X-ray photoelectron spectroscopic studies.
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This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
In this work, spectrum sensing for cognitive radios is considered in the presence of multiple Primary Users (PU) using frequency-hopping communication over a set of frequency bands. The detection performance of the Fast Fourier Transform (FFT) Average Ratio (FAR) algorithm is obtained in closed-form, for a given FFT size and number of PUs. The effective throughput of the Secondary Users (SU) is formulated as an optimization problem with a constraint on the maximum allowable interference on the primary network. Given the hopping period of the PUs, the sensing duration that maximizes the SU throughput is derived. The results are validated using Monte Carlo simulations. Further, an implementation of the FAR algorithm on the Lyrtech (now, Nutaq) small form factor software defined radio development platform is presented, and the performance recorded through the hardware is observed to corroborate well with that obtained through simulations, allowing for implementation losses. (C) 2015 Elsevier B.V. All rights reserved.
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We report the temperature-dependent photoluminescence (PL) properties of polymeric graphite-like carbon nitride (g-C3N4) and a methodology for the determination of quantum efficiency along with the activation energy. The PL is shown to originate from three different pathways of transitions: sigma*-LP, pi*-LP, and pi*-pi, respectively. The overall activation energy is found to be similar to 73.58 meV which is much lower than the exciton binding energy reported theoretically but ideal for highly sensitive wide-range temperature sensing. The quantum yield derived from the PL data is 23.3%, whereas the absolute quantum yield is 5.3%. We propose that the temperature-dependent PL can be exploited for the evaluation of the temperature dependency of quantum yield as well as for temperature sensing. Our analysis further indicates that g-C3N4 is well-suited for wide-range temperature sensing.
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Using density functional theory (DFT) we investigate the changes in electronic and transport properties of graphene bilayer caused by sliding one of the layers. Change in stacking pattern breaks the lattice symmetry, which results in Lifshitz transition together with the modulation of the electronic structure. Going from AA to AB stacking by sliding along armchair direction leads to a drastic transition in electronic structure from linear to parabolic dispersion. Our transport calculations show a significant change in the overall transmission value for large sliding distances along zigzag direction. The increase in interlayer coupling with normal compressive strain increases the overlapping of conduction and valence band, which leads to further shift in the Dirac points and an enhancement in the Lifshitz transition. The ability to tune the topology of band structure by sliding and/or applying normal compressive strain will open doors for controlled tuning of many physical phenomenon such as Landau levels and quantum Hall effect in graphene. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
Fiber-reinforced plastics (FRPs) are typically difficult to machine due to their highly heterogeneous and anisotropic nature and the presence of two phases (fiber and matrix) with vastly different strengths and stiffnesses. Typical machining damage mechanisms in FRPs include series of brittle fractures (especially for thermosets) due to shearing and cracking of matrix material, fiber pull-outs, burring, fuzzing, fiber-matrix debonding, etc. With the aim of understanding the influence of the pronounced heterogeneity and anisotropy observed in FRPs, ``Idealized'' Carbon FRP (I-CFRP) plates were prepared using epoxy resin with embedded equispaced tows of carbon fibers. Orthogonal cutting of these I-CFRPs was carried out, and the chip formation characteristics, cutting force signals and strain distributions obtained during machining were analyzed using the Digital Image Correlation (DIC) technique. In addition, the same procedure was repeated on Uni-Directional CFRPs (UD-CFRPs). Chip formation mechanisms in FRPs were found to depend on the depth of cut and fiber orientation with pure epoxy showing a pronounced ``size effect.'' Experimental results indicate that in-situ full field strain measurements from DIC coupled with force measurements using dynamometry provide an adequate measure of anisotropy and heterogeneity during orthogonal cutting.
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The effect of Radio Frequency (RF) power on the properties of magnetron sputtered Al doped ZnO thin films and the related sensor properties are investigated. A series of 2 wt% Al doped ZnO; Zn0.98Al0.02O (AZO) thin films prepared with magnetron sputtering at different RF powers, are examined. The structural results reveal a good adhesive nature of thin films with quartz substrates as well as increasing thickness of the films with increasing RF power. Besides, the increasing RF power is found to improve the crystallinity and grain growth as confirmed by X-ray diffraction. On the other hand, the optical transmittance is significantly influenced by the RF power, where the transparency values achieved are higher than 82% for all the AZO thin films and the estimated optical band gap energy is found to decrease with RF power due to an increase in the crystallite size as well as the film thickness. In addition, the defect induced luminescence at low temperature (77 K) and room temperature (300 K) was studied through photoluminescence spectroscopy, it is found that the defect density of electronic states of the Al3+ ion increases with an increase of RF power due to the increase in the thickness of the film and the crystallite size. The gas sensing behavior of AZO films was studied for NO2 at 350 degrees C. The AZO film shows a good response towards NO2 gas and also a good relationship between the response and the NO2 concentration, which is modeled using an empirical formula. The sensing mechanism of NO2 is discussed.