410 resultados para Chemical Sensing
Resumo:
A simple thermal evaporation method is presented for the growth of crystalline SnO2 nanowires at a low substrate temperature of 450 degrees C via an gold-assisted vapor-liquid-solid mechanism. The as-grown nanowires were characterized by scanning electron microscopy, transmission electron microscopy and X-ray diffraction, and were also tested for methanol vapor sensing. Transmission electron microscopy studies revealed the single-crystalline nature of the each nanowire. The fabricated sensor shows good response to methanol vapor at an operating temperature of 450 degrees C. (C) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
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Coordination self-assembly of a series of tetranuclear Pt(II) macrocycles containing an organometallic backbone incorporating ethynyl functionality is presented. The 1 : 1 combination of a linear acceptor 1,4-bistrans-Pt(PEt3)(2)(NO3)(ethynyl)]benzene (1) with three different dipyridyl donor `clips' (L-a-L-c) afforded three 2 + 2] self-assembled Pt-4(II) macrocycles (2a-2c) in quantitative yields, respectively L-a = 1,3-bis-(3-pyridyl)isothalamide; L-b = 1,3-bis(3-pyridyl)ethynylbenzene; L-c = 1,8-bis(4-pyridyl)ethynylanthracene]. These macrocycles were characterized by multinuclear NMR (H-1 and P-31); ESI-MS spectroscopy and the molecular structures of 2a and 2b were established by single crystal X-ray diffraction analysis. These macrocycles (2a-2c) are fluorescent in nature. The amide functionalized macrocycle 2a is used as a receptor to check the binding affinity of aliphatic acyclic dicarboxylic acids. Such binding affinity is examined using fluorescence and UV-Vis spectroscopic methods. A solution state fluorescence study showed that macrocycle 2a selectively binds (K-SV = 1.4 x 10(4) M-1) maleic acid by subsequent enhancement in emission intensity. Other aliphatic dicarboxylic acids such as fumaric, succinic, adipic, mesaconic and itaconic acids caused no change in the emission spectra; thereby demonstrating its potential use as a macrocyclic receptor in distinction of maleic acid from other aliphatic dicarboxylic acids.
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This paper presents computational work on the biogas early phase combustion in spark ignition (SI) engines using detailed chemical kinetics. Specifically, the early phase combustion is studied to assess the effect of various ignition parameters such as spark plug location, spark energy, and number of spark plugs. An integrated version of the KIVA-3V and CHEMKIN codes was developed and used for the simulations utilizing detailed kinetics involving 325 reactions and 53 species The results show that location of the spark plug and local flow field play an important role. A central plug configuration, which is associated with higher local flow velocities in the vicinity of the spark plug, showed faster initial combustion. Although a dual plug configuration shows the highest rate of fuel consumption, it is comparable to the rate exhibited by the central plug case. The radical species important in the initiation of combustion are identified, and their concentrations are monitored during the early phase of combustion. The concentration of these radicals is also observed to correlate very well with the above-mentioned trend.Thus, the role of these radicals in promoting faster combustion has been clearly established. It is also observed that the minimum ignition energy required to initiate a self-sustained flame depends on the flow field condition in the vicinity of the spark plug.Increasing the methane content in the biogas has shown improved combustion.
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This paper analyzes the error exponents in Bayesian decentralized spectrum sensing, i.e., the detection of occupancy of the primary spectrum by a cognitive radio, with probability of error as the performance metric. At the individual sensors, the error exponents of a Central Limit Theorem (CLT) based detection scheme are analyzed. At the fusion center, a K-out-of-N rule is employed to arrive at the overall decision. It is shown that, in the presence of fading, for a fixed number of sensors, the error exponents with respect to the number of observations at both the individual sensors as well as at the fusion center are zero. This motivates the development of the error exponent with a certain probability as a novel metric that can be used to compare different detection schemes in the presence of fading. The metric is useful, for example, in answering the question of whether to sense for a pilot tone in a narrow band (and suffer Rayleigh fading) or to sense the entire wide-band signal (and suffer log-normal shadowing), in terms of the error exponent performance. The error exponents with a certain probability at both the individual sensors and at the fusion center are derived, with both Rayleigh as well as log-normal shadow fading. Numerical results are used to illustrate and provide a visual feel for the theoretical expressions obtained.
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Compressive Sensing (CS) is a new sensing paradigm which permits sampling of a signal at its intrinsic information rate which could be much lower than Nyquist rate, while guaranteeing good quality reconstruction for signals sparse in a linear transform domain. We explore the application of CS formulation to music signals. Since music signals comprise of both tonal and transient nature, we examine several transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT), Fourier basis and also non-orthogonal warped transforms to explore the effectiveness of CS theory and the reconstruction algorithms. We show that for a given sparsity level, DCT, overcomplete, and warped Fourier dictionaries result in better reconstruction, and warped Fourier dictionary gives perceptually better reconstruction. “MUSHRA” test results show that a moderate quality reconstruction is possible with about half the Nyquist sampling.
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We consider cooperative spectrum sensing for cognitive radios. We develop an energy efficient detector with low detection delay using sequential hypothesis testing. Sequential Probability Ratio Test (SPRT) is used at both the local nodes and the fusion center. We also analyse the performance of this algorithm and compare with the simulations. Modelling uncertainties in the distribution parameters are considered. Slow fading with and without perfect channel state information at the cognitive radios is taken into account.
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This paper considers cooperative spectrum sensing in Cognitive Radios. In our previous work we have developed DualSPRT, a distributed algorithm for cooperative spectrum sensing using Sequential Probability Ratio Test (SPRT) at the Cognitive Radios as well as at the fusion center. This algorithm works well, but is not optimal. In this paper we propose an improved algorithm- SPRT-CSPRT, which is motivated from Cumulative Sum Procedures (CUSUM). We analyse it theoretically. We also modify this algorithm to handle uncertainties in SNR's and fading.
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While the under-utilization of licensed spectrum based on measurement studies conducted in a few developed countries has spurred lots of interest in opportunistic spectrum access, there exists no infrastructure today for measuring real-time spectrum occupancy across vast geographical regions. In this paper, we present the design and implementation of SpecNet, a first-of-its-kind platform that allows spectrum analyzers around the world to be networked and efficiently used in a coordinated manner for spectrum measurement as well as implementa- tion and evaluation of distributed sensing applications. We demonstrate the value of SpecNet through three applications: 1) remote spectrum measurement, 2) primary transmitter coverage estimation and 3) Spectrum-Cop that quickly identifies and localizes transmitters in a frequency range and geographic region of interest.
Resumo:
We consider cooperative spectrum sensing for cognitive radios. We develop an energy efficient detector with low detection delay using sequential hypothesis testing. Sequential Probability Ratio Test (SPRT) is used at both the local nodes and the fusion center. We also analyse the performance of this algorithm and compare with the simulations. Modelling uncertainties in the distribution parameters are considered. Slow fading with and without perfect channel state information at the cognitive radios is taken into account.
Resumo:
Signal acquisition under a compressed sensing scheme offers the possibility of acquisition and reconstruction of signals sparse on some basis incoherent with measurement kernel with sub-Nyquist number of measurements. In particular when the sole objective of the acquisition is the detection of the frequency of a signal rather than exact reconstruction, then an undersampling framework like CS is able to perform the task. In this paper we explore the possibility of acquisition and detection of frequency of multiple analog signals, heavily corrupted with additive white Gaussian noise. We improvise upon the MOSAICS architecture proposed by us in our previous work to include a wider class of signals having non-integral frequency components. This makes it possible to perform multiplexed compressed sensing for general frequency sparse signals.
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The impact of chemical treatment on the surface morphology and other physical properties of tin monosulphide (SnS) thin films have been investigated. The SnS films treated with selected organic solvents exhibited strong improvement in their crystalline-quality and considerable decrease in electrical resistivity. Particularly, the films treated with chloroform showed very low electrical resistivity of similar to 5 Omega cm and a low optical band gap of 1.81 eV as compared to untreated and treated SnS films with other chemicals. From these studies we realized that the chemical treatment of SnS films has strong impact on their surface morphology and also on other physical properties. (C) 2012 Elsevier B.V. All rights reserved.
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Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.
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We report a special, hitherto-unexplored property of (-)-epigallocatechin gallate (EGCG) as a chiral solvating agent for enantiodiscrimination of alpha-amino acids in the polar solvent DMSO. This phenomenon has been investigated by H-1 NMR spectroscopy. The mechanism of the interaction property of EGCG with alpha-amino acids has been understood as arising out of hydrogen-bonded noncovalent interactions, where the -OH groups of two phenyl rings of EGCG play dominant roles. The conversion of the enantiomeric mixture into diastereomers yielded well-resolved peaks for D and L amino acids permitting the precise measurement of enantiomeric composition. Often one encounters complex situations when the spectra are severely overlapped or partially resolved hampering the testing of enantiopurity and the precise measurement of enantiomeric excess (ee). Though higher concentration of EGCG yielded better discrimination, the use of lower concentration being economical, we have exploited an appropriate 2D NMR experiment in overcoming such problems. Thus, in the present study we have successfully demonstrated the utility of the bioflavonoid (-)-EGCG, a natural product as a chiral solvating agent for the discrimination of large number of alpha-amino acids in a polar solvent DMSO. Another significant advantage of this new chiral sensing agent is that it is a natural product and does not require tedious multistep synthesis unlike many other chiral auxiliaries.
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The analysis of a fully integrated optofluidic lab-on-a-chip sensor is presented in this paper. This device is comprised of collinear input and output waveguides that are separated by a microfluidic channel. When light is passed through the analyte contained in the fluidic gap, optical power loss occurs owing to absorption of light. Apart from absorption, a mode-mismatch between the input and output waveguides occurs when the light propagates through the fluidic gap. The degree of mode-mismatch and quantum of optical power loss due to absorption of light by the fluid form the basis of our analysis. This sensor can detect changes in refractive index and changes in concentration of species contained in the analyte. The sensitivity to detect minute changes depends on many parameters. The parameters that influence the sensitivity of the sensor are mode spot size, refractive index of the fluid, molar concentration of the species contained in the analyte, width of the fluidic gap, and waveguide geometry. By correlating various parameters, an optimal fluidic gap distance corresponding to a particular mode spot size that achieves the best sensitivity is determined both for refractive index and absorbance-based sensing.
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A series of fluoranthene derivatives (F1-F5) varied with nature and type of substituents were synthesized via Diels-Alder reaction followed by in situ decarbonylation. The solid state structures have been established through single crystal X-ray diffraction (XRD). The presence of extended conjugation and having two alkyloxy chains on phenyl rings induces flexibility to orient opposite to each other and interacts with another fluoranthene unit with weak pi-pi interactions and show unique supramolecular arrangements. The envisaged photophysical and DFT studies demonstrated that HOMO-LUMO levels were effectively tuned by different substituents with an optical band gap from 3.44 to 3.88 eV provoked to examine as sensitive fluorescent chemosensors for the detection of nitroaromatic compounds (NACs). The sensitivity toward the detection of NACs was evaluated through fluorescence quenching in solution (aqueous and non-aqueous) and solid state (vapor and contact mode). Fluorescence studies demonstrated that electron transfer occurs from the electron rich fluoranthene fluorophores to the electron deficient NACs by the dominant static quenching mechanism and the quenching process is reversible. It was found that the detection sensitivity increases with extent of conjugation on fluoranthene unit. The contact mode approach using thin layer silica chromatographic plates exhibits a femtogram (1.15 fg/cm(2)) detection limit for trinitrotoluene (TNT) and picric acid (PA), while the solution state fluorescence quenching shows for PA detection at the 2-20 ppb level. The sensing performance of fluoranthene thin films to NACs in aqueous solution reveals that fluorophores are highly selective towards the detection of PA. The smart performances of thin film fluorophores with high photostability have great advantage than those of conjugated polymers with superior sensitive detection of PA in groundwater.