938 resultados para Sensors and interfaces
Resumo:
The determination of hydrodynamic coefficients of full scale underwater vehicles using system identification (SI) is an extremely powerful technique. The procedure is based on experimental runs and on the analysis of on-board sensors and thrusters signals. The technique is cost effective and it has high repeatability; however, for open-frame underwater vehicles, it lacks accuracy due to the sensors' noise and the poor modeling of thruster-hull and thruster-thruster interaction effects. In this work, forced oscillation tests were undertaken with a full scale open-frame underwater vehicle. These conducted tests are unique in the sense that there are not many examples in the literature taking advantage of a PMM installation for testing a prototype and; consequently, allowing the comparison between the experimental results and the ones estimated by parameter identification. The Morison's equation inertia and drag coefficients were estimated with two parameter identification methods, that is, the weighted and the ordinary least-squares procedures. It was verified that the in-line force estimated from Morison's equation agrees well with the measured one except in the region around the motion inversion points. On the other hand, the error analysis showed that the ordinary least-squares provided better accuracy and, therefore, was used to evaluate the ratio between inertia and drag forces for a range of Keulegan-Carpenter and Reynolds numbers. It was concluded that, although both experimental and estimation techniques proved to be powerful tools for evaluation of an open-frame underwater vehicle's hydrodynamic coefficients, the research provided a rich amount of reference data for comparison with reduced models as well as for dynamic motion simulation of ROVs. [DOI: 10.1115/1.4004952]
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The wide variety of molecular architectures used in sensors and biosensors and the large amount of data generated with some principles of detection have motivated the use of computational methods, such as information visualization techniques, not only to handle the data but also to optimize sensing performance. In this study, we combine projection techniques with micro-Raman scattering and atomic force microscopy (AFM) to address critical issues related to practical applications of electronic tongues (e-tongues) based on impedance spectroscopy. Experimentally, we used sensing units made with thin films of a perylene derivative (AzoPTCD acronym), coating Pt interdigitated electrodes, to detect CuCl(2) (Cu(2+)), methylene blue (MB), and saccharose in aqueous solutions, which were selected due to their distinct molecular sizes and ionic character in solution. The AzoPTCD films were deposited from monolayers to 120 nm via Langmuir-Blodgett (LB) and physical vapor deposition (PVD) techniques. Because the main aspects investigated were how the interdigitated electrodes are coated by thin films (architecture on e-tongue) and the film thickness, we decided to employ the same material for all sensing units. The capacitance data were projected into a 2D plot using the force scheme method, from which we could infer that at low analyte concentrations the electrical response of the units was determined by the film thickness. Concentrations at 10 mu M or higher could be distinguished with thinner films tens of nanometers at most-which could withstand the impedance measurements, and without causing significant changes in the Raman signal for the AzoPTCD film-forming molecules. The sensitivity to the analytes appears to be related to adsorption on the film surface, as inferred from Raman spectroscopy data using MB as analyte and from the multidimensional projections. The analysis of the results presented may serve as a new route to select materials and molecular architectures for novel sensors and biosensors, in addition to suggesting ways to unravel the mechanisms behind the high sensitivity obtained in various sensors.
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The aim of this study is to develop a new enzymeless electroanalytical method for the indirect quantification of creatinine from urine sample. This method is based on the electrochemical monitoring of picrate anion reduction at a glassy carbon electrode in an alkaline medium before and after it has reacted with creatinine (Jaffe's reaction). By using the differential pulse voltammetry technique under the optimum experimental conditions (step potential, amplitude potential, reaction time, and temperature), a linear analytical curve was obtained for concentrations of creatinine ranging from 1 to 80 mu mol L-1, with a detection limit of 380 nmol L-1. This proposed method was used to measure creatinine in human urine without the interference of most common organic species normally present in biological fluids (e.g., uric acid, ascorbic acid, glucose, and phosphocreatinine). The results obtained using urine samples were highly similar to the results obtained using the reference spectrophotometric method (at a 95% confidence level). (C) 2012 Elsevier B.V. All rights reserved.
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The layer-by-layer (LbL) technique combined with field-effect transistor (FET) based sensors has enabled the production of pH-sensitive platforms with potential application in biosensors. A variation of the FET architecture, so called separative extended gate FET (SEGFET) devices, are promise as an alternative to conventional ion sensitive FET (ISFET). SEGFET configuration exhibits the advantage of combining the field-effect concept with organic and inorganic materials directly adsorbed on the extended gate, allowing the test of new pH-sensitive materials in a simple and low cost way. In this communication, poly(propylene imine) dendrimer (PPI) and TiO2 nanoparticles (TiO2-np) were assembled onto gold-covered substrates via layer-by-layer technique to produce a low cost SEGFET pH sensor. The sensor presented good pH sensitivity, ca. 57 mV pH(-1), showing that our strategy has potential advantages to fabricate low cost pH-sensing membranes. (C) 2012 Elsevier B.V. All rights reserved.
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In this manuscript, an automatic setup for screening of microcystins in surface waters by employing photometric detection is described. Microcystins are toxins delivered by cyanobacteria within an aquatic environment, which have been considered strongly poisonous for humans. For that reason, the World Health Organization (WHO) has proposed a provisional guideline value for drinking water of 1 mu g L-1. In this work, we developed an automated equipment setup, which allows the screening of water for concentration of microcystins below 0.1 mu g V. The photometric method was based on the enzyme-linked immunosorbent assay (ELISA) and the analytical signal was monitored at 458 nm using a homemade LED-based photometer. The proposed system was employed for the detection of microcystins in rivers and lakes waters. Accuracy was assessed by processing samples using a reference method and applying the paired t-test between results. No significant difference at the 95% confidence level was observed. Other useful features including a linear response ranging from 0.05 up to 2.00 mu g L-1 (R-2 =0.999) and a detection limit of 0.03 mu g L-1 microcystins were achieved. (C) 2011 Elsevier B.V. All rights reserved.
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Sensor and actuator based on laminated piezocomposite shells have shown increasing demand in the field of smart structures. The distribution of piezoelectric material within material layers affects the performance of these structures; therefore, its amount, shape, size, placement, and polarization should be simultaneously considered in an optimization problem. In addition, previous works suggest the concept of laminated piezocomposite structure that includes fiber-reinforced composite layer can increase the performance of these piezoelectric transducers; however, the design optimization of these devices has not been fully explored yet. Thus, this work aims the development of a methodology using topology optimization techniques for static design of laminated piezocomposite shell structures by considering the optimization of piezoelectric material and polarization distributions together with the optimization of the fiber angle of the composite orthotropic layers, which is free to assume different values along the same composite layer. The finite element model is based on the laminated piezoelectric shell theory, using the degenerate three-dimensional solid approach and first-order shell theory kinematics that accounts for the transverse shear deformation and rotary inertia effects. The topology optimization formulation is implemented by combining the piezoelectric material with penalization and polarization model and the discrete material optimization, where the design variables describe the amount of piezoelectric material and polarization sign at each finite element, with the fiber angles, respectively. Three different objective functions are formulated for the design of actuators, sensors, and energy harvesters. Results of laminated piezocomposite shell transducers are presented to illustrate the method. Copyright (C) 2012 John Wiley & Sons, Ltd.
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Gunshot residues (GSR) can be used in forensic evaluations to obtain information about the type of gun and ammunition used in a crime. In this work, we present our efforts to develop a promising new method to discriminate the type of gun [four different guns were used: two handguns (0.38 revolver and 0.380 pistol) and two long-barrelled guns (12-calibre pump-action shotgun and 0.38 repeating rifle)] and ammunition (five different types: normal, semi-jacketed, full-jacketed, green, and 3T) used by a suspect. The proposed approach is based on information obtained from cyclic voltammograms recorded in solutions containing GSR collected from the hands of the shooters, using a gold microelectrode; the information was further analysed by non-supervised pattern-recognition methods [(Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA)]. In all cases (gun and ammunition discrimination), good separation among different samples in the score plots and dendrograms was achieved. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Multilayered nanocomposite films (thickness 50-90 nm) of cobalt ferrite nanoparticles (np-CoFe2O4, 18 nm) were deposited on top of interdigitated microelectrodes by the layer-by-layer technique in order to study their dielectric properties. For that purpose, two different types of nanocomposite films were prepared by assembling np-CoFe2O4 either with poly(3,4-ethylenedioxy thiophene):poly(styrene sulfonic acid) or with polyaniline and sulfonated lignin. Despite the different film architectures, the morphology of both was dominated by densely-packed layers of nanoparticles surrounded by polyelectrolytes. The dominant effect of np-CoFe2O4 was also observed after impedance spectroscopy measurements, which revealed that dielectric behavior of the nanocomposites was largely influenced by the charge transport across nanoparticle-polyelectrolyte interfaces. For example, nanocomposites containing np-CoFe2O4 exhibited a single low-frequency relaxation process, with time constants exceeding 15 ms. At 1 kHz, the dielectric constant and the dissipation factor (tan ᵟ) of these nanocomposites were 15 and 0.15, respectively. These values are substantially inferior to those reported for pressed pellets made exclusively of similar nanoparticles. Impedance data were further fitted with equivalent circuit models from which individual contributions of particle's bulk and interfaces to the charge transport within the nanocomposites could be evaluated. The present study evidences that such nanocomposites display a dielectric behavior dissimilar from that exhibited by their individual counterparts much likely due to enlarged nanoparticle- polyelectrolyte interfaces.
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Discotic molecules comprising a rigid aromatic core and flexible side chains have been promisingly applied in OLEDs as self-organizing organic semiconductors. Due to their potentially high charge carrier mobility along the columns, device performance can be readily improved by proper alignment of columns throughout the bulk. In the present work, the charge mobility was increased by 5 orders of magnitude due to homeotropic columnar ordering induced by the boundary interfaces during thermal annealing in the mesophase. State-of-the-art diodes were fabricated using spin-coated films whose homeotropic alignment with formation of hexagonal germs was observed by polarizing optical microscopy. The photophysical properties showed drastic changes at the mesophase-isotropic transition, which is supported by the gain of order observed by X-ray diffraction. The electrical properties were investigated by modeling the current−voltage characteristics by a space-charge-limited current transport with a field dependent mobility.
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In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.
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Increasingly stringent exhaust emission limits and higher fuel economy are the main drivers of the engine development process. As a consequence, the complexity of the propulsion units and its subsystems increase, due to the extensive use of sensors and actuators needed to obtain a precise control over the combustion phase. Since engine calibration process consumes most of the development time, new tools and methodologies are needed to shorten the development time and increase the performance attainable. Real time combustion analysis, based on the in-cylinder pressure signal, can significantly improve the calibration of the engine control strategies and the development of new algorithms, giving instantaneous feedback on the engine behavior. A complete combustion analysis and diagnosis system has been developed, capable of evaluating the most important indicators about the combustion process, such as indicated mean effective pressure, heat release, mass fraction burned and knock indexes. Such a tool is built on top of a flexible, modular and affordable hardware platform, capable of satisfying the requirements needed for accuracy and precision, but also enabling the use directly on-board the vehicle, due to its small form factor.
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The main aims of my PhD research work have been the investigation of the redox, photophysical and electronic properties of carbon nanotubes (CNT) and their possible uses as functional substrates for the (electro)catalytic production of oxygen and as molecular connectors for Quantum-dot Molecular Automata. While for CNT many and diverse applications in electronics, in sensors and biosensors field, as a structural reinforcing in composite materials have long been proposed, the study of their properties as individual species has been for long a challenging task. CNT are in fact virtually insoluble in any solvent and, for years, most of the studies has been carried out on bulk samples (bundles). In Chapter 2 an appropriate description of carbon nanotubes is reported, about their production methods and the functionalization strategies for their solubilization. In Chapter 3 an extensive voltammetric and vis-NIR spectroelectrochemical investigation of true solutions of unfunctionalized individual single wall CNT (SWNT) is reported that permitted to determine for the first time the standard electrochemical potentials of reduction and oxidation as a function of the tube diameter of a large number of semiconducting SWNTs. We also established the Fermi energy and the exciton binding energy for individual tubes in solution and, from the linear correlation found between the potentials and the optical transition energies, one to calculate the redox potentials of SWNTs that are insufficiently abundant or absent in the samples. In Chapter 4 we report on very efficient and stable nano-structured, oxygen-evolving anodes (OEA) that were obtained by the assembly of an oxygen evolving polyoxometalate cluster, (a totally inorganic ruthenium catalyst) with a conducting bed of multiwalled carbon nanotubes (MWCNT). Here, MWCNT were effectively used as carrier of the polyoxometallate for the electrocatalytic production of oxygen and turned out to greatly increase both the efficiency and stability of the device avoiding the release of the catalysts. Our bioinspired electrode addresses the major challenge of artificial photosynthesis, i.e. efficient water oxidation, taking us closer to when we might power the planet with carbon-free fuels. In Chapter 5 a study on surface-active chiral bis-ferrocenes conveniently designed in order to act as prototypical units for molecular computing devices is reported. Preliminary electrochemical studies in liquid environment demonstrated the capability of such molecules to enter three indistinguishable oxidation states. Side chains introduction allowed to organize them in the form of self-assembled monolayers (SAM) onto a surface and to study the molecular and redox properties on solid substrates. Electrochemical studies on SAMs of these molecules confirmed their attitude to undergo fast (Nernstian) electron transfer processes generating, in the positive potential region, either the full oxidized Fc+-Fc+ or the partly oxidized Fc+-Fc species. Finally, in Chapter 6 we report on a preliminary electrochemical study of graphene solutions prepared according to an original procedure recently described in the literature. Graphene is the newly-born of carbon nanomaterials and is certainly bound to be among the most promising materials for the next nanoelectronic generation.
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This thesis adresses the problem of localization, and analyzes its crucial aspects, within the context of cooperative WSNs. The three main issues discussed in the following are: network synchronization, position estimate and tracking. Time synchronization is a fundamental requirement for every network. In this context, a new approach based on the estimation theory is proposed to evaluate the ultimate performance limit in network time synchronization. In particular the lower bound on the variance of the average synchronization error in a fully connected network is derived by taking into account the statistical characterization of the Message Delivering Time (MDT) . Sensor network localization algorithms estimate the locations of sensors with initially unknown location information by using knowledge of the absolute positions of a few sensors and inter-sensor measurements such as distance and bearing measurements. Concerning this issue, i.e. the position estimate problem, two main contributions are given. The first is a new Semidefinite Programming (SDP) framework to analyze and solve the problem of flip-ambiguity that afflicts range-based network localization algorithms with incomplete ranging information. The occurrence of flip-ambiguous nodes and errors due to flip ambiguity is studied, then with this information a new SDP formulation of the localization problem is built. Finally a flip-ambiguity-robust network localization algorithm is derived and its performance is studied by Monte-Carlo simulations. The second contribution in the field of position estimate is about multihop networks. A multihop network is a network with a low degree of connectivity, in which couples of given any nodes, in order to communicate, they have to rely on one or more intermediate nodes (hops). Two new distance-based source localization algorithms, highly robust to distance overestimates, typically present in multihop networks, are presented and studied. The last point of this thesis discuss a new low-complexity tracking algorithm, inspired by the Fano’s sequential decoding algorithm for the position tracking of a user in a WLAN-based indoor localization system.
Resumo:
Das Ziel dieser Arbeit ist die Synthese von Polymerbürsten auf Silizium durch Aufbringen der Reaktionslösung mit einem Pipettiersystem. Dies ist für die Beschichtung von Microcantilever Sensoren interessant, um spezifische Fühler mit funktionellen Polymerschichten, die auf chemische oder physikalische Einflüsse reagieren, zu bauen. Bisherige Synthesemethoden werden in Lösung durchgeführt. Atom Transfer Radical Polymerization ist etabliert, um definierte Schichten von Polymerbürsten herzustellen. Die Kombination mit einer “Spot Printing”-Technik kann eine Alternative sein, um einzelne Cantilever mit einer Breite von 90 μm und einer Länge von 750 μm zu beschichten. Dafür wurde eine Chemie getestet, die mit dem Pipettiersystem Nano-Plotter der Firma Gesim umsetzbar ist. Aus einer Mischung aus Wasser und DMF wurden Poly(N-Isopropylacrylamid)-Bürsten auf Silizium mit Schichtdicken bis zu 40 nm hergestellt. Es war nötig den Nano-Plotter anzupassen, damit zum einen auf die Microcantilever Sensoren pipettiert werden kann und zum andern die Nanoliter großen Tropfen über den Reaktionszeitraum stabil sind. Auf diese Weise konnten Linien mit einer Schichtdicke von ca. 2 nm auf Siliziumwafer hergestellt werden. Die “Spot-Printing” Methode ist daher eine gute Ergänzung zur herkömmlichen Synthese.
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Hydrogen peroxide (H2O2) is a powerful oxidant which is commonly used in a wide range of applications in the industrial field. Several methods for the quantification of H2O2 have been developed. Among them, electrochemical methods exploit the ability of some hexacyanoferrates (such as Prussian Blue) to detect H2O2 at potentials close to 0.0 V (vs. SCE) avoiding the occurrence of secondary reactions, which are likely to run at large overpotentials. This electrocatalytic behaviour makes hexacyanoferrates excellent redox mediators. When deposited in the form of thin films on the electrode surfaces, they can be employed in the fabrication of sensors and biosensors, normally operated in solutions at pH values close to physiological ones. As hexacyanoferrates show limited stability in not strongly acidic solutions, it is necessary to improve the configuration of the modified electrodes to increase the stability of the films. In this thesis work, organic conducting polymers were used to fabricate composite films with Prussian Blue (PB) to be electro-deposited on Pt surfaces, in order to increase their pH stability. Different electrode configurations and different methods of synthesis of both components were tested, and for each one the achievement of a possible increase in the operational stability of Prussian Blue was verified. Good results were obtained for the polymer 3,3''-didodecyl-2,2':5',2''-terthiophene (poly(3,3''-DDTT)), whose presence created a favourable microenvironment for the electrodeposition of Prussian Blue. The electrochemical behaviour of the modified electrodes was studied in both aqueous and organic solutions. Poly(3,3''-DDTT) showed no response in aqueous solution in the potential range where PB is electroactive, thus in buffered aqueous solution is was possible to characterize the composite material, focusing only on the redox behaviour of PB. A combined effect of anion and cation of the supporting electrolyte was noticed. The response of Pt electrodes modified with films of the PB /poly(3,3''-DDTT) composite was evaluated for the determination of H2O2. The performance of such films was found better than that of the PB alone. It can be concluded that poly(3,3''-DDTT) plays a key role in the stabilization of Prussian Blue causing also a wider linearity range for the electrocatalytic response to H2O2.