the plenoptic sensor

In this thesis, we will introduce the innovative concept of a plenoptic sensor that can determine the phase and amplitude distortion in a coherent beam, for example a laser beam that has propagated through the turbulent atmosphere.. The plenoptic sensor can be applied to situations involving strong or deep atmospheric turbulence. This can improve free space optical communications by maintaining optical links more intelligently and efficiently. Also, in directed energy applications, the plenoptic sensor and its fast reconstruction algorithm can give instantaneous instructions to an adaptive optics (AO) system to create intelligent corrections in directing a beam through atmospheric turbulence. The hardware structure of the plenoptic sensor uses an objective lens and a microlens array (MLA) to form a mini “Keplerian” telescope array that shares the common objective lens. In principle, the objective lens helps to detect the phase gradient of the distorted laser beam and the microlens array (MLA) helps to retrieve the geometry of the distorted beam in various gradient segments. The software layer of the plenoptic sensor is developed based on different applications. Intuitively, since the device maximizes the observation of the light field in front of the sensor, different algorithms can be developed, such as detecting the atmospheric turbulence effects as well as retrieving undistorted images of distant objects. Efficient 3D simulations on atmospheric turbulence based on geometric optics have been established to help us perform optimization on system design and verify the correctness of our algorithms. A number of experimental platforms have been built to implement the plenoptic sensor in various application concepts and show its improvements when compared with traditional wavefront sensors. As a result, the plenoptic sensor brings a revolution to the study of atmospheric turbulence and generates new approaches to handle turbulence effect better.

MEMS SENSOR PLATFORMS FOR IN SITU CHARACTERIZATION OF LI-ION BATTERY ELECTRODES

Lithium-ion batteries provide high energy density while being compact and light-weight and are the most pervasive energy storage technology powering portable electronic devices such as smartphones, laptops, and tablet PCs. Considerable efforts have been made to develop new electrode materials with ever higher capacity, while being able to maintain long cycle life. A key challenge in those efforts has been characterizing and understanding these materials during battery operation. While it is generally accepted that the repeated strain/stress cycles play a role in long-term battery degradation, the detailed mechanisms creating these mechanical effects and the damage they create still remain unclear. Therefore, development of techniques which are capable of capturing in real time the microstructural changes and the associated stress during operation are crucial for unravelling lithium-ion battery degradation mechanisms and further improving lithium-ion battery performance. This dissertation presents the development of two microelectromechanical systems sensor platforms for in situ characterization of stress and microstructural changes in thin film lithium-ion battery electrodes, which can be leveraged as a characterization platform for advancing battery performance. First, a Fabry-Perot microelectromechanical systems sensor based in situ characterization platform is developed which allows simultaneous measurement of microstructural changes using Raman spectroscopy in parallel with qualitative stress changes via optical interferometry. Evolutions in the microstructure creating a Raman shift from 145 cm−1 to 154 cm−1 and stress in the various crystal phases in the LixV2O5 system are observed, including both reversible and irreversible phase transitions. Also, a unique way of controlling electrochemically-driven stress and stress gradient in lithium-ion battery electrodes is demonstrated using the Fabry-Perot microelectromechanical systems sensor integrated with an optical measurement setup. By stacking alternately stressed layers, the average stress in the stacked electrode is greatly reduced by 75% compared to an unmodified electrode. After 2,000 discharge-charge cycles, the stacked electrodes retain only 83% of their maximum capacity while unmodified electrodes retain 91%, illuminating the importance of the stress gradient within the electrode. Second, a buckled membrane microelectromechanical systems sensor is developed to enable in situ characterization of quantitative stress and microstructure evolutions in a V2O5 lithium-ion battery cathode by integrating atomic force microscopy and Raman spectroscopy. Using dual-mode measurements in the voltage range of the voltage range of 2.8V – 3.5V, both the induced stress (~ 40 MPa) and Raman intensity changes due to lithium cycling are observed. Upon lithium insertion, tensile stress in the V2O5 increases gradually until the α- to ε-phase and ε- to δ-phase transitions occur. The Raman intensity change at 148 cm−1 shows that the level of disorder increases during lithium insertion and progressively recovers the V2O5 lattice during lithium extraction. Results are in good agreement with the expected mechanical behavior and disorder change in V2O5, highlighting the potential of microelectromechanical systems as enabling tools for advanced scientific investigations. The work presented here will be eventually utilized for optimization of thin film battery electrode performance by achieving fundamental understanding of how stress and microstructural changes are correlated, which will also provide valuable insight into a battery performance degradation mechanism.

Electrical characterization of the rectifying contact between aluminium and electrodeposited poly(3-methylthiophene)

A detailed investigation both of the DC and of the AC electrical properties of the Schottky barrier formed between aluminium and electrodeposited poly(3-methylthiophene) is reported. The devices show rectification ratios up to 2 x 10(4) which can be increased further after post-metal annealing. The reverse characteristics of the devices follow predictions based on the image-force lowering of the Schottky barrier, from which the doping density can be estimated, As the forward voltage increases, the device current is limited by the bulk resistance of the polymer with some evidence for injection limitation at the gold counter-electrode at high bias. In the bulk-limited regime, the device current is thermally activated near room temperature with an activation energy in the range 0.2-0.3 eV. Below about 150 K the device current is almost independent of temperature. Capacitance-voltage plots obtained at frequencies well below the device relaxation frequency indicate the presence of two distinct acceptor states, A set of shallow acceptor states are active in forward bias and are believed to determine the bulk conductivity of the polymer. A set of deeper accepters are active only for very small forward voltages and for all reverse voltages, namely when band banding causes the Fermi energy to cross these states. The density of these deeper states is approximately an order of magnitude greater than that of the shallow states. Evidence is presented also for the influence of fabrication conditions on the formation of an insulating interfacial layer at the rectifying interface. The presence of such a layer leads to inversion at the polymer surface and a modification of the I-V characteristics.

Electrical characterization of the rectifying contact between aluminium and electrodeposited poly(3-methylthiophene)

A detailed investigation both of the DC and of the AC electrical properties of the Schottky barrier formed between aluminium and electrodeposited poly(3-methylthiophene) is reported. The devices show rectification ratios up to 2 x 10(4) which can be increased further after post-metal annealing. The reverse characteristics of the devices follow predictions based on the image-force lowering of the Schottky barrier, from which the doping density can be estimated, As the forward voltage increases, the device current is limited by the bulk resistance of the polymer with some evidence for injection limitation at the gold counter-electrode at high bias. In the bulk-limited regime, the device current is thermally activated near room temperature with an activation energy in the range 0.2-0.3 eV. Below about 150 K the device current is almost independent of temperature. Capacitance-voltage plots obtained at frequencies well below the device relaxation frequency indicate the presence of two distinct acceptor states, A set of shallow acceptor states are active in forward bias and are believed to determine the bulk conductivity of the polymer. A set of deeper accepters are active only for very small forward voltages and for all reverse voltages, namely when band banding causes the Fermi energy to cross these states. The density of these deeper states is approximately an order of magnitude greater than that of the shallow states. Evidence is presented also for the influence of fabrication conditions on the formation of an insulating interfacial layer at the rectifying interface. The presence of such a layer leads to inversion at the polymer surface and a modification of the I-V characteristics.

Rapid and sensitive ethanol sensor based on hollow Au/V2O5 nanotubes via emulsion-electrospinning route

Hollow electrospun V2O5 and Au/V2O5 nanotubes have been successfully synthesized by combining emulsion electrospinning (EE) and post calcination treatment. Immiscible polyvinyl pyrrolidone (PVP)/metal salts/dimethylformamide (DMF) solution and polystyrene (PS)/DMF solution are chosen for the EE to form PS PVP/metal salts) core-sheath nanofibers, in which PS nanorods were formed and encapsulated within in the PVP/metal salts nanofibers owing to the stretching forces and de-emulsified force during the electrospinning. Excellent sensitivity and rapid response-recovery behaviors against ethanol have been successfully achieved based on our hollow ceramic (V2O5 and Au/V2O5) nanotubes.

Anodization parameters influencing the morphology and electrical properties of TiO2 nanotubes for living cell interfacing and investigations

Nanotube structures have attracted tremendous attention in recent years in many applications. Among such nanotube structures, titania nanotubes (TiO2) have received paramount attention in the medical domain due to their unique properties, represented by high corrosion resistance, good mechanical properties, high specific surface area, as well as great cell proliferation, adhesion and mineralization. Although lot of research has been reported in developing optimized titanium nanotube structures for different medical applications, however there is a lack of unified literature source that could provide information about the key parameters and experimental conditions required to develop such optimized structure. This paper addresses this gap, by focussing on the fabrication of TiO2 nanotubes through anodization process on both pure titanium and titanium alloys substrates to exploit the biocompatibility and electrical conductivity aspects, critical factors for many medical applications from implants to in-vivo and in-vitro living cell studies. It is shown that the morphology of TiO2 directly impacts the biocompatibility aspects of the titanium in terms of cell proliferation, adhesion and mineralization. Similarly, TiO2 nanotube wall thickness of 30-40nm has shown to exhibit improved electrical behaviour, a critical factor in brain mapping and behaviour investigations if such nanotubes are employed as micro-nano-electrodes.

Robot coordination for energy-balanced matching and sequence dispatch of robots to events

Given a set of events and a set of robots, the dispatch problem is to allocate one robot for each event to visit it. In a single round, each robot may be allowed to visit only one event (matching dispatch), or several events in a sequence (sequence dispatch). In a distributed setting, each event is discovered by a sensor and reported to a robot. Here, we present novel algorithms aimed at overcoming the shortcomings of several existing solutions. We propose pairwise distance based matching algorithm (PDM) to eliminate long edges by pairwise exchanges between matching pairs. Our sequence dispatch algorithm (SQD) iteratively finds the closest event-robot pair, includes the event in dispatch schedule of the selected robot and updates its position accordingly. When event-robot distances are multiplied by robot resistance (inverse of the remaining energy), the corresponding energy-balanced variants are obtained. We also present generalizations which handle multiple visits and timing constraints. Our localized algorithm MAD is based on information mesh infrastructure and local auctions within the robot network for obtaining the optimal dispatch schedule for each robot. The simulations conducted confirm the advantages of our algorithms over other existing solutions in terms of average robot-event distance and lifetime.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Mechanical and Electrical Properties of Single-walled Carbon Nanotubes Synthesized by Chemical Vapor Deposition

Despite the tremendous application potentials of carbon nanotubes (CNTs) proposed by researchers in the last two decades, efficient experimental techniques and methods are still in need for controllable production of CNTs in large scale, and for conclusive characterizations of their properties in order to apply CNTs in high accuracy engineering. In this dissertation, horizontally well-aligned high quality single-walled carbon nanotubes (SWCNTs) have been successfully synthesized on St-cut quartz substrate by chemical vapor deposition (CVD). Effective radial moduli (Eradial) of these straight SWCNTs have been measured by using well-calibrated tapping mode and contact mode atomic force microscopy (AFM). It was found that the measured Eradial decreased from 57 to 9 GPa as the diameter of the SWCNTs increased from 0.92 to 1.91 nm. The experimental results were consistent with the recently reported theoretical simulation data. The method used in this mechanical property test can be easily applied to measure the mechanical properties of other low-dimension nanostructures, such as nanowires and nanodots. The characterized sample is also an ideal platform for electrochemical tests. The electrochemical activities of redox probes Fe(CN)63-/4-, Ru(NH3)63+, Ru(bpy)32+ and protein cytochrome c have been studied on these pristine thin films by using aligned SWCNTs as working electrodes. A simple and high performance electrochemical sensor was fabricated. Flow sensing capability of the device has been tested for detecting neurotransmitter dopamine at physiological conditions with the presence of Bovine serum albumin. Good sensitivity, fast response, high stability and anti-fouling capability were observed. Therefore, the fabricated sensor showed great potential for sensing applications in complicated solution.

Properties of polycrystalline gas sensors based on d.c. and a.c. electrical measurements

Electrical properties of polycrystalline gas sensors are analyzed by d.c. and a.c. measurements. d.c. electrical conductivity values compared with those obtained by admittance spectroscopy methods help to obtain a detailed 'on line' analysis of conductivity-modulated gas sensors. The electrical behaviour of grain boundaries is obtained and a new design of sensors can be achieved by enhancing the activity of surface states in the detecting operation. A Schottky barrier model is used to explain the grain boundary action under the presence of surrounding gases. The height of this barrier is a function of gas concentration due to the trapping of excess charge generated by gas adsorption at the interface. A comparison between this dependence, and a plot of the real and imaginary components of the admittance versus frequency at different gas concentrations, provides information on the different parameters that play a role in the conduction mechanisms. These methods have been applied to the design of a CO sensor based on tin oxide films for domestic purposes, the characteristics of which are presented.

On the race of worms and patches: modeling the spread of information in wireless sensor networks

Sensor networks are a branch of distributed ad hoc networks with a broad range of applications in surveillance and environment monitoring. In these networks, message exchanges are carried out in a multi-hop manner. Due to resource constraints, security professionals often use lightweight protocols, which do not provide adequate security. Even in the absence of constraints, designing a foolproof set of protocols and codes is almost impossible. This leaves the door open to the worms that take advantage of the vulnerabilities to propagate via exploiting the multi-hop message exchange mechanism. This issue has drawn the attention of security researchers recently. In this paper, we investigate the propagation pattern of information in wireless sensor networks based on an extended theory of epidemiology. We develop a geographical susceptible-infective model for this purpose and analytically derive the dynamics of information propagation. Compared with the previous models, ours is more realistic and is distinguished by two key factors that had been neglected before: 1) the proposed model does not purely rely on epidemic theory but rather binds it with geometrical and spatial constraints of real-world sensor networks and 2) it extends to also model the spread dynamics of conflicting information (e.g., a worm and its patch). We do extensive simulations to show the accuracy of our model and compare it with the previous ones. The findings show the common intuition that the infection source is the best location to start patching from, which is not necessarily right. We show that this depends on many factors, including the time it takes for the patch to be developed, worm/patch characteristics as well as the shape of the network.

Sensor psychrometric approaches to mitigating aflatoxins in maize dried on farms in Kenya

Kenia liegt in den Äquatorialtropen von Ostafrika und ist als ein weltweiter Hot-Spot für Aflatoxinbelastung insbesondere bei Mais bekannt. Diese toxischen und karzinogenen Verbindungen sind Stoffwechselprodukte von Pilzen und so insbesondere von der Wasseraktivität abhängig. Diese beeinflusst sowohl die Trocknung als auch die Lagerfähigkeit von Nahrungsmitteln und ist somit ein wichtiger Faktor bei der Entwicklung von energieeffizienten und qualitätsorientierten Verarbeitungsprozessen. Die vorliegende Arbeit hat sich zum Ziel gesetzt, die Veränderung der Wasseraktivität während der konvektiven Trocknung von Mais zu untersuchen. Mittels einer Optimierungssoftware (MS Excel Solver) wurde basierend auf sensorerfassten thermo-hygrometrischen Daten der gravimetrische Feuchteverlust von Maiskolben bei 37°C, 43°C und 53°C vorausberechnet. Dieser Bereich stellt den Übergang zwischen Niedrig- und Hochtemperaturtrocknung dar. Die Ergebnisse zeigen deutliche Unterschiede im Verhalten der Körner und der Spindel. Die Trocknung im Bereich von 35°C bis 45°C kombiniert mit hohen Strömungsgeschwindigkeiten (> 1,5 m / s) begünstigte die Trocknung der Körner gegenüber der Spindel und kann daher für eine energieeffiziente Trocknung von Kolben mit hohem Anfangsfeuchtegehalt empfohlen werden. Weitere Untersuchungen wurden zum Verhalten unterschiedlicher Schüttungen bei der bei Mais üblichen Satztrocknung durchgeführt. Entlieschter und gedroschener Mais führte zu einem vergrößerten Luftwiderstand in der Schüttung und sowohl zu einem höheren Energiebedarf als auch zu ungleichmäßigerer Trocknung, was nur durch einen erhöhten technischen Aufwand etwa durch Mischeinrichtungen oder Luftumkehr behoben werden könnte. Aufgrund des geringeren Aufwandes für die Belüftung und die Kontrolle kann für kleine landwirtschaftliche Praxisbetriebe in Kenia daher insbesondere die Trocknung ganzer Kolben in ungestörten Schüttungen empfohlen werden. Weiterhin wurde in der Arbeit die Entfeuchtung mittels eines Trockenmittels (Silikagel) kombiniert mit einer Heizquelle und abgegrenztem Luftvolumen untersucht und der konventionellen Trocknung gegenüber gestellt. Die Ergebnisse zeigten vergleichbare Entfeuchtungsraten während der ersten 5 Stunden der Trocknung. Der jeweilige Luftzustand bei Verwendung von Silikagel wurde insbesondere durch das eingeschlossene Luftvolumen und die Temperatur beeinflusst. Granulierte Trockenmittel sind bei der Maistrocknung unter hygienischen Gesichtspunkten vorteilhaft und können beispielsweise mit einfachen Öfen regeneriert werden, so dass Qualitätsbeeinträchtigungen wie bei Hochtemperatur- oder auch Freilufttrocknung vermieden werden können. Eine hochwertige Maistrocknungstechnik ist sehr kapitalintensiv. Aus der vorliegenden Arbeit kann aber abgeleitet werden, dass einfache Verbesserungen wie eine sensorgestützte Belüftung von Satztrocknern, der Einsatz von Trockenmitteln und eine angepasste Schüttungshöhe praktikable Lösungen für Kleinbauern in Kenia sein können. Hierzu besteht, ggf. auch zum Aspekt der Verwendung regenerativer Energien, weiterer Forschungsbedarf.

A Comparative Analysis Between Genetic Algorithms and Complex Nonlinear Least Squares on Electrical Impedance Characterization

This paper compares the performance of the complex nonlinear least squares algorithm implemented in the LEVM/LEVMW software with the performance of a genetic algorithm in the characterization of an electrical impedance of known topology. The effect of the number of measured frequency points and of measurement uncertainty on the estimation of circuit parameters is presented. The analysis is performed on the equivalent circuit impedance of a humidity sensor.