868 resultados para SENSING APPLICATION
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We report on the novel flow sensing application of piezoelectric ZnO thin film deposited on Phynox alloy sensing element. Characterization of piezoelectric ZnO films deposited on Phynox (Elgiloy) substrate at different RF powers is discussed. ZnO films deposited at RF power of 100W were found to have fine c-axis orientation, possesses excellent surface morphology with lower rms surface roughness of 1.87 nm and maximum d(31) coefficient value 4.7 pm V-1. The thin cantilever strip of Phynox alloy with ZnO film as a sensing layer for flow sensing has been tested for flow rates ranging from 2 to 18 L min(-1). A detailed theoretical analysis of the experimental set-up showing the relationship between output voltage and force at a particular flow rate has been discussed. The sensitivity of now sensing element is similar to 18 mV/(L min(-1)) and typical response time is of the order of 20 m s. The sensing element is calibrated using in-house developed testing set-up. (C) 2012 Elsevier B.V. All rights reserved.
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Ready-to-use screen printed glucose sensors are fabricated using Prussian Blue (PB) and Cobalt Phthalocyanine (CoPC) mediated carbon inks as working electrodes. The reference and counter electrodes are screen printed using silver/silver chloride and graphitic carbon paste respectively. The screen printed reference electrodes (internal reference electrode (IRE)) are found to be stable for more than 60 minutes when examined with saturated calomel electrode. Optimal operating voltage for PB and CoPC screen printed sensors are determined by hydrodynamic voltammetric technique. Glucose oxidase is immobilized on the working electrodes by cross-linking method. PB mediated glucose sensor exhibits a sensitivity of 5.60 mA cm(-2)/mM for the range, 10 to 1000 mu M. Sensitivity of CoPC mediated glucose sensor is found to be 5.224 mu A cm(-2)/mM and amperometeric response is linear for the range, 100 to 1500 mu M. Interference studies on the fabricated glucose sensors are conducted with species like uric acid and ascorbic acid. PB mediated sensors showed a completely interference-free behavior. The sensing characteristics of PB mediated glucose sensors are also studied in diluted human serum samples and the results are compared with the values obtained through standard clinical method. The co-efficient of variation is found to be less than 5%. (C) 2015 The Electrochemical Society. All rights reserved.
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The unique strategy for electrochemiluminescence (ECL) sensor based on the quantum dots (QDs) oxidation in aqueous solution to detect amines is proposed for the first time. Actually, there existed two QDs ECL peaks in anhydrous solution, one at high positive potential and another at high negative potential. However, here we introduced the QDs oxidation ECL in aqueous solution to fabricate a novel ECL sensor. Such sensor needed only lower positive potential to produce ECL, which could prevent the interferences resulted from high potential as that of QDs reduction ECL in aqueous solution. Therefore, the present work not only extended the QDs oxidation ECL application field from anhydrous to aqueous solution but also enriched the variety of ECL system in aqueous solution. Furthermore, we investigated the QDs oxidation ECL toward different kinds of amines, and found that both aliphatic alkyl and hydroxy groups could lead to the enhancement of ECL intensity. Among these amines, 2-(dibutylamino)ethanol (DBAE) is the most effective one, and accordingly, the first ECL sensing application of the QDs oxidation ECL toward DBAE is developed; the as-prepared ECL sensor shows wide linear range, high sensitivity, and good stability.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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I utilized state the art remote sensing and GIS (Geographical Information System) techniques to study large scale biological, physical and ecological processes of coastal, nearshore, and offshore waters of Lake Michigan and Lake Superior. These processes ranged from chlorophyll a and primary production time series analysies in Lake Michigan to coastal stamp sand threats on Buffalo Reef in Lake Superior. I used SeaWiFS (Sea-viewing Wide Field-of-view Sensor) satellite imagery to trace various biological, chemical and optical water properties of Lake Michigan during the past decade and to investigate the collapse of early spring primary production. Using spatial analysis techniques, I was able to connect these changes to some important biological processes of the lake (quagga mussels filtration). In a separate study on Lake Superior, using LiDAR (Light Detection and Ranging) and aerial photos, we examined natural coastal erosion in Grand Traverse Bay, Michigan, and discussed a variety of geological features that influence general sediment accumulation patterns and interactions with migrating tailings from legacy mining. These sediments are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.
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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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We consider nonparametric sequential hypothesis testing when the distribution under null hypothesis is fully known and the alternate hypothesis corresponds to some other unknown distribution. We use easily implementable universal lossless source codes to propose simple algorithms for such a setup. These algorithms are motivated from spectrum sensing application in Cognitive Radios. Universal sequential hypothesis testing using Lempel Ziv codes and Krichevsky-Trofimov estimator with Arithmetic Encoder are considered and compared for different distributions. Cooperative spectrum sensing with multiple Cognitive Radios using universal codes is also considered.
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We report on the systematic comparative study of highly c-axis oriented and crystalline piezoelectric ZnO thin films deposited on four different flexible substrates for vibration sensing application. The flexible substrates employed for present experimental study were namely a metal alloy (Phynox), metal (aluminum), polyimide (Kapton), and polyester (Mylar). ZnO thin films were deposited by an RF reactive magnetron sputtering technique. ZnO thin films of similar thicknesses of 700 +/- 30 nm were deposited on four different flexible substrates to have proper comparative studies. The crystallinity, surface morphology, chemical composition, and roughness of ZnO thin films were evaluated by respective material characterization techniques. The transverse piezoelectric coefficient (d(31)) value for assessing the piezoelectric property of ZnO thin films on different flexible substrates was measured by a four-point bending method. ZnO thin films deposited on Phynox alloy substrate showed relatively better material characterization results and a higher piezoelectric d(31) coefficient value as compared to ZnO films on metal and polymer substrates. In order to experimentally verify the above observations, vibration sensing studies were performed. As expected, the ZnO thin film deposited on Phynox alloy substrate showed better vibration sensing performance. It has generated the highest peak to peak output voltage amplitude of 256 mV as compared to that of aluminum (224 mV), Kapton (144 mV), and Mylar (46 mV). Therefore, metal alloy flexible substrate proves to be a more suitable, advantageous, and versatile choice for integrating ZnO thin films as compared to metal and polymer flexible substrates for vibration sensing applications. The present experimental study is extremely important and helpful for the selection of a suitable flexible substrate for various applications in the field of sensor and actuator technology.
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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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Based on shape memory effect of the sputtered thin film shape memory alloys, different types of micromirror structures were designed and fabricated for optical sensing application. Using surface micromachining, TiNi membrane mirror structure has been fabricated, which can be actuated based on intrinsic two-way shape memory effect of the free-standing TiNi film. Using bulk micromachining, TiNi/Si and TiNi/Si 3N 4microcantilever mirror structures were fabricated. © 2007 IOP Publishing Ltd.
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A novel series of polymerisable squaramides has been synthesised in high yields using simple chemical reactions, and evaluated in the binding of anionic species. These vinyl monomers can be used as functional building blocks in co-polymerisations with a plethora of co-monomers or cross-linkers, grace to their compatibility with free-radical polymerisation reactions. Aromatic substituted squaramides were found to be the strongest receptors, while binding of certain anions was accompanied by a strong colour change, attributed to the de-protonation of the squaramide. The best performing squaramide monomers were incorporated in molecularly imprinted polymers (MIPs) targeting a model anion and their capacities and selectivity were evaluated by rebinding experiments. Polymers prepared using the new squaramide monomers were compared to urea based co-polymers, and were found to contain up to 80% of the theoretical maximum number of binding sites, an exceptionally high value compared to previous reports. Strong polymer colour changes were observed upon rebinding of certain anions, equivalent to those witnessed in solution, paving the way for application of such materials in anion sensing devices.
Graphical abstract: Polymerisable squaramide receptors for anion binding and sensing
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Tecniche per l'acquisizione a basso consumo di segnali sparsi tramite compressed sensing
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Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.
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An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs). Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV. This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management.
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Creating nanoscale heterostructures with molecular-scale (<2 nm) metal wires is critical for many applications and remains a challenge. Here, we report the first time synthesis of nanoscale heterostructures with single-crystal molecular-scale Au nanowires attached to different nanostructure substrates. Our method involves the formation of Au nanoparticle seeds by the reduction of rocksalt AuCl nanocubes heterogeneously nucleated on the Substrates and subsequent nanowire growth by oriented attachment of Au nanoparticles from the Solution phase. Nanoscale heterostructures fabricated by such site-specific nucleation and growth are attractive for many applications including nanoelectronic device wiring, catalysis, and sensing.