Nanoparticle based devices are becoming of great interest because of their single-electron transport behavior, and high surface charge density. Nanoparticle based devices operate at low power, and are potentially highly stable and extremely robust. Making interconnections to nanoparticle devices, however, has been an impending issue. Also percolating/conductive array of nanoparticles is not easy to build since repulsion between the charged nanoparticles causes them to deposit at distance significantly larger for electron tunneling. In this study, we resolve these challenges to make nanoparticle based electronic devices. Using biological (bacteria) or physical (polyelectrolyte fiber) scaffolds, we selectively deposited percolating array of 30 nm Au nanoparticles, to produce a highly versatile nanoparticle-organic hybrid device. The device is based on electron tunneling phenomena, which is highly sensitive to change in inter-particle distance and dielectric constant between nanoparticles. The key to building this structure is the molecular brushes on the surface of the scaffold, which shield the charge on nanoparticle to allow for percolating deposition. The electrostatic attraction for such a deposition on bacteria was measured to be so strong (0.038 N/m) that it could bend a 400 nm long and 25 nm wide gold nanorod. Once the device is built, the hygroscopic scaffolds were actuated by humidity, to modulate the electron tunneling barrier width (or height) between the metallic nanoparticles. A decrease in inter-particle separation by < 0.2 nm or a change in the dielectric constant from ~ 40 to 3 (for humidity excursion from 20% to ~0%), causes a 40-150 fold increase in electron tunneling current. The coupling between the underlying scaffold and the Au particle structure is essential to achieving such a high and robust change in current. In contrast to most humidity sensors, the sensitivity is extremely high at low humidity. This device is >10-fold better than standard microelectronic and MEMS technology based humidity sensors. After the deposition, the "live" bacterial scaffold retains its biological construct, providing an avenue for active integration of biological functions with electronic transport in nanoparticle device. Such hybrids will be the key to conceptually new electronic devices that can be integrated with power and function of microorganisms, on flexible plastic-like substrates using simple beaker chemistry. The technology has broad potential based on variety of nanoparticles (for example, magnetic, metallic and semi-conducting) to make electro-optical and inorganic devices, bringing a prominent advancement in the present technology. Our work is published in, Angewandte Chemie, JACS and Nano Letters, and featured in places such as, Discover Magazine, Science News and Nature. / Ph. D.

The Meshless Local Petrov-Galerkin (MLPG) method has been employed to analyze the following linear and nonlinear solid mechanics problems: free and forced vibrations of a segmented bar and a cracked beam, pull-in instability of an electrostatically actuated microbeam, and plane strain deformations of incompressible hyperelastic materials. The Moving Least Squares (MLS) approximation is used to generate basis functions for the trial solution, and for the test functions. Local symmetric weak formulations are derived, and the displacement boundary conditions are enforced by the method of Lagrange multipliers. Three different techniques are employed to enforce continuity conditions at the material interfaces: Lagrange multipliers, jump functions, and MLS basis functions with discontinuous derivatives. For the electromechanical problem, the pull-in voltage and the corresponding deflection are extracted by combining the MLPG method with the displacement iteration pull-in extraction algorithm. The analysis of large deformations of incompressible hyperelastic materials is performed by using a mixed pressure-displacement formulation. For every problem studied, computed results are found to compare well with those obtained either analytically or by the Finite Element Method (FEM). For the same accuracy, the MLPG method requires fewer nodes but more CPU time than the FEM. / Ph. D.

We investigate (i) pull-in instabilities in a microelectromechanical (MEM) beam due to the Coulomb force and in MEM membranes due to the Coulomb and the Casimir forces, and (ii) thermomechanical instability in a heat-conducting thermoelastoviscoplastic solid due to thermal softening overcoming hardening caused by strain- and strain-rate effects. Each of these nonlinear multiphysics problems is analyzed by the meshless local Petrov-Galerkin (MLPG) method. The moving least squares (MLS) approximation is used to generate basis functions for the trial solution, and the basis for test functions is taken to be either the weight functions used in the MLS approximation, or the same as for the trial solution. In this case the method becomes Bubnov-Galerkin. Essential (displacement, temperature, electric potential) boundary conditions are enforced by the method of Lagrange multipliers. For the electromechanical problem, the pull-in voltage and the corresponding deflection are extracted by combining the MLPG method with either the displacement iteration pull-in extraction algorithm or the pseudoarclength continuation method. For the thermomechanical problem, the localization of deformation into narrow regions of intense plastic deformation is delineated. For every problem studied, computed results are found to compare well with those obtained either analytically or by the finite element (FE) method. For the same accuracy, the MLPG method generally requires fewer nodes but more CPU time than the FE method; thus additional computational cost is compensated somewhat by the increased efficiency of the MLPG method. / Ph. D.

Vehicle classification data especially trucks has an important role in both pavement maintenance and highway planning strategy. An advanced microelectromechanical system (MEMS) accelerometer for vehicle classification based on axle count and spacing was designed, tested, and applied to the pavement. Vehicle-pavement interaction was collected by the vibration sensor while vehicle axle count and spacing were calibrated later. Collected vibration data also used to analyze the pavement surface condition and compared with simulation using dynamic loading analysis. Laboratory tests using MMLS3 device to verify the accuracy of MEMS accelerometer and reaction under different surface condition were tested. An algorithm for calculating axle spacing and axle count was developed. Acceleration of different pavement surface condition were analyzed and compared with simulation results, the influence of surface condition to the pavement acceleration was concluded. / Master of Science

Recent industry trends toward more complex and interconnected systems have increased the demand for more reliable pressure sensors. One of the best methods to ensure reliability is by regularly calibrating the sensor, checking its functionality and accuracy. By integrating a micro-actuator with a pressure sensor, the sensor can self-calibrate, eliminating the complexities and costs associated with traditional sensor calibration methods. The present work is focused on furthering understanding and improving the thermal performance of a thermopneumatic actuated self-calibrating pressure sensor. A transient numerical model was developed in ANSYS and was calibrated using experimental testing data. The model provided insights into the sensor's performance not previously observed in experimental testing, such as the temperature gradient within the sensor and its implications. Furthermore, the model was utilized for two design studies. First, the sensor's inefficiencies were studied, and it was found that a substrate with low thermal conductivity and high thermal diffusivity is ideal for both the sensor's efficiency and a faster transient response time. The second design study showed that decreasing the size of the sealed reference cavity, decreases power consumption and transient response time. The study also showed that decreasing the cavity base dimension has a larger effect on decreasing power consumption and response time. Overall, the present work increases understanding of the self-calibrating pressure sensor and provides insight into potential design improvements, moving closer to true self-calibrating pressure sensors. / Master of Science / Pressure sensors are used in most engineering applications, and the demand is ever increasing due to emerging fields such as the Internet of things (IOT), automations, and autonomy. One drawback of current pressures sensor technology is their need to be calibrated, ensuring accuracy and function. Sensor calibration requires equipment, trained personnel, and must be done regularly, resulting in significant costs. Borrowing technology, methods, and materials from the integrated circuit industry, the costs of sensor calibration can be addressed by the development of an intelligent MEMS (micro-electromechanical system) pressure sensor with self-calibration capabilities. The self-calibrating capability is achieved by combining a micro-actuator and a micro- pressures sensor into one system. This work focuses on complementing previously obtained experimental testing data with a thermal finite element model to provide a deeper understanding and insight. The model is implemented in the commercial software ANSYS and model uncertainties were addressed via model calibration. The model revealed a temperature gradient within the sensor, and insight into its potential effects. The model is also used as a design tool to reduce energy inefficiencies, decrease the time it takes the sensor to respond, and to study the effects of reducing the sensor size. The studies showed that the power consumption can potentially be decreased up to 92% and the response time can be decreased up to 99% by changing the sensor's substrate material. Furthermore, by halving the sensor reference cavity size, the cavity temperature can be increased by 45% and the time for the sensor to respond can be decrease by 59%.

Embedded sensors are a fixture of most devices in the current computer industry. These small devices are used for a variety of purposes throughout many fields to collect whatever kind of information is needed by the user. From data on device acceleration to data on position relative to the Earth's magnetic field, embedded sensors can provide it for any number of tasks. The advent of these devices has made work and research in the computer industry significantly easier but they are not without their drawbacks. Most of these sensors operate by drawing external data from the environment through send and receive signals. This mode of operation leaves them vulnerable to external malicious users who seek access to the data being stored and handled by the sensors. Concerns over security and privacy of embedded sensor data has become a topic of great concern with the continued digitization of sensitive personal data. Within the last five years, studies have shown the ability to manipulate embedded magnetic sensors in order to gain access to various forms of sensitive personal data. This is of great concern to the developers of mobile devices as most mobile devices possess embedded magnetic sensors. The vulnerability of sensors to external influence leads to concerns for both data privacy and degradation of public trust in the ability of their devices to keep their personal information safe and out of the wrong hands. Degradation of public trust in security methodologies is a major concern to many in the research and tech industry as much of the work conducted to advance both security and technology depends on large amounts of public data. If the public loses trust in the ability of the devices used by researchers to protect and ensure the safety of the data provided to them, then they may stop providing data which would then make the work of researchers and other tech workers considerably more difficult. To address these concerns, this thesis will present an introduction to Magnetic sensor devices (a prominent tool for data collection), how these sensors work and the ways they handle data. We shall then examine the techniques used to interfere with the functioning and output of magnetic sensors employed by mobile devices. Finally, we shall examine existing techniques for defending against these kinds of attacks as well as propose potential new techniques. The end goal of this work is to provide a broader perspective on the nature of environmental/natural interference and its relationship to scientific study and technological advancement. Literature around this topic does exist, however, all existing works currently in the literature focus exclusively on one form of interference i.e., light which leads to a smaller/narrower perspective which this work seeks to remedy. The end result is meant to give a broader perspective of multiple forms of interference and their interrelations between each other than is possible by current perspectives due to their narrow lens. / Master of Science / Embedded sensors are small devices integrated into many mobile devices currently in the public market. These devices serve to collect environmental data of all kinds in order to perform a variety of functions. From directional calibration to magnetic orientation in relation to the magnetic north pole, sensors perform it all. This has led to a massive increase in computer power and quality of life for the general public but not without issue. The increase in storing personal/sensitive data to be processed by these devices has prompted a new breed of privacy concerns and problems to confront. In this thesis, we seek to show the influence and effects of five distinct types of interference rooted in the natural world on the functioning of magnetic sensor devices. Through the experiments conducted in this work, it was found that the interference forms of sound, temperature, and electromagnetism could induce a 32-36 percent average decrease in standard deviation in the data being processed by the sensor. Temperature shifting as an interference form also showed the potential for sizeable impacts on sensor functioning in terms of both increases and decreases. The largest decrease in standard deviation observed was 122 percent from the experiments with low temperature shifting. This work shows the incredible power and influence that the forces of nature can have on everyday devices and their need for data from their environment. The results observed from the temperature shift experiments also highlight the danger of leaving temperature based cyber-attacks under researched. The main use of this work is to fill the void in the current literature created by temperature based cyber-attacks and hopefully spur more research to be conducted into this method of cyber threat.

This research performs an experimental study of a trailing edge blowing system that can adapt to variations in flow parameters and reduce the unsteady stator-rotor interaction at all engine operating conditions. The fan rotor of a 1/14 scale turbofan propulsion simulator is subjected to spatially periodic, circumferential inlet flow distortions. The distortions are generated by four struts that support a centerbody in the inlet mounted onto the simulator. To reduce the unsteady effects of the strut wakes on the rotor blades, the wake is re-energized by injecting mass from the trailing edge of the strut. Each strut is provided with discrete blowing holes that open out through the strut trailing edge. Each blowing hole is connected to a MEMS based microvalve, which controls the blowing rate of the hole. The microvalve is actuated by a signal voltage, generated by a PID controller that accepts free stream and wake axial flow velocities as inputs and minimizes their difference. To quantify the effectiveness of trailing edge blowing the far-field noise is measured in an anechoic chamber. The experiments are performed for two simulator test speeds, 29,500 rpm and 40,000 rpm, with and without trailing edge blowing. The maximum reduction recorded at 29,500 rpm is 8.2 dB, and at 40,000 rpm is 7.3 dB. Reductions of 2.9 dB and greater are observed at the first five harmonics of the blade passing frequency. The sound power level at the blade passing frequency, calculated from measured far-field directivity, is reduced by 4.4 dB at 29,500 rpm and by 2.9 dB at 40,000 rpm. The feasibility and advantage of active control is demonstrated by the ability of the system to respond to a step change in the inlet flow velocity, and achieve optimum wake filling in approximately 8 seconds. / Master of Science

This paper reports the evaluation results of the mechanical structures of MEMS (micro electro mechanical systems) sensor implemented in the integrated MEMS inertial sensor for a wide sensing range from below 0.1 G to 20 G (1 G = 9.8 m/s^2). To investigate the mechanical tolerance, a maximum target acceleration of 20G was applied to the sub-1G sensor which had the heaviest proof mass of all that sensors had. The structure stability of Ti/Au multi-layered structures was also examined by using Ti/Au micro cantilevers. The results showed that the stoppers effectively functioned to prevent the proof mass and the springs from self-destruction, and that the stability of Ti/Au structures increased with an increase in width. Those results suggest that the proposed stopper and spring structures could be promising to realize MEMS sensors.

Då komponenter för tillståndsövervakning idag är billiga, små storleksmässigt och kraftfullare än tidigare, kan hårdvara byggas ihop, mjukvara programmeras och sedan appliceras på kritiska delar i ett system, mer kostnadseffektivt och i större omfattning än tidigare. I stor skala kallas detta sakernas internet, och är framtiden för underhållsarbete då personal inte längre behöver vara fysiskt närvarande i samma grad som tidigare. En proprietär lösning kostar idag vanligtvis över 5 000 kr. Detta projekt har behandlat prototyper till en kostnad av cirka 1 000 kr med öppen hårdvara och mjukvara, vilket stödjer affärsutveckling och bidrar till ett bredare spektra av leverantörer, vilket sätter press på marknaden gällande olika lösningar. Syftet med denna studie är att utveckla och testa mätningar i verklig miljö för tillståndsövervakning av utsatta delar av järnvägsinfrastrukturen, som punktfel i spårläge och spårväxlar. Projektet innefattar prototyper, energihantering, loggning av data och hur användbara dessa data är. Sensorerna är av typen MEMS accelerometrar och olika montage av dessa har testats. Målsättningen har varit att utvärdera hur dessa fungerar i verklig miljö och hur användarvänliga dessa är för att mäta rörelse av räls och sliper. Mer specifikt, avser detta fältprov av accelerometer för uppvakning och energihantering, sensor för insamling av vibrationer för rörelse i spår och analys av insamlad mätdata. Fälttest visade att en accelerometerbaserad uppvakningssensor kan väcka ett mätsystem genom vibrationer i rälsen ca: 70 meter innan tåget kommer fram till sensorn. Tydligaste mätdata för analys erhölls vid montage på slipers samt då ett avstånd på ca: 70 meter togs. Montering i direkt närhet till mätobjektet på rälslivet bidrog till en signal med inslag av högfrekventa vibrationer. Då tydlig mätdata erhölls kunde antal boogies och axlar identifieras vilket kunde verifieras med bild på loket. Mätdata som analyserades kunde via integration erhålla förskjutning i vertikal samt lateral riktning. Detta är användbart, både för infrastrukturförvaltare samt för underhållsentreprenörer, då degradering kan upptäckas i god tid och förebyggande underhållsåtgärder kan sättas in mot berörda feltyper. Den önskade livslängden enligt infrastrukturförvaltare var minst fem år, och efter mätning av strömåtgång enligt nuvarande specifikation så uppnås detta om mätningar sker sju gånger dagligen med litiumbatterier (1200 mAh) som strömkälla. Som ett första steg mot sakernas internet så har detta arbete skapat en god grund för att förverkliga detta. Fortsatt arbete efter detta projekt kan innefatta gprs och Wi-Fi för internetuppkoppling samt strömmätning för att se hur mycket förbrukningen ökar. Parallellkoppling av batterier kan vara en lösning för längre livslängd ifall förbrukningen påverkas markant. Olika varianter av filtrering för en tydligare signal kan också vara av intresse. Andra typer av sensorer, både för verifiering av resultat i denna rapport samt för att utprova alternativ. Detta kan innefatta geofoner, multi-depth deflectometers och andra typer av accelerometrar. / Since condition monitoring devices today are cheap, small size and more powerful than before, hardware can be built together, software programmed, and then applied to critical parts of a system, more cost-effective and to a greater extent than before. On a large scale this is called the Internet of Things, and is the future of today's maintenance work, as staff no longer needs to be physically present to the same extent as before. A proprietary solution today generally costs over 5,000 SEK. This project has processed prototypes at a cost of approximately 1,000 SEK with open hardware and software, which supports business development and contributes to a wider range of suppliers, which puts pressure on the market for different solutions. The purpose of this study is to develop and test measurements in real environment for condition monitoring of exposed parts of the railway infrastructure, such as point errors in track and railroad switches. The project includes prototypes, energy management, data logging and how useful these data are. The sensors are of the type MEMS accelerometers and various assemblies of these have been tested. The goal has been to evaluate how these works in a real environment and how user friendly these are to measure the movement of rails and grinders. Field test showed that an accelerometer-based wake-up sensor can wake a measuring system by vibration in the rail approximately 70 meters before the train reaches the sensor. Clearest measurement data for analysis was obtained when mounted on grinders and when a distance of about 70 meters was taken. Mounting in close proximity to the measurement object on the rail life contributed to a signal with high frequency vibration input. When clear measurement data was obtained, the number of boogies and axes could be identified, this could be verified by image on the train. Measurement data analyzed could through integration obtain displacement in vertical as well as lateral direction. This is useful, both for infrastructure managers and for maintenance entrepreneurs, as degradation can be detected in time and preventive maintenance actions can be set against the relevant failure types. The desired lifespan according to infrastructure managers was at least five years, and after measuring current consumption according to the current specification, this is achieved if measurements take place seven times a day with lithium batteries (1200 mAh) as the power source. As a first step towards the Internet of Things, this work has created a good foundation to make this reality. Continued work after this project may include gprs and Wi-Fi for internet connection as well as current measurement to see how much usage is increasing. Parallel coupling of batteries can be a solution for longer service life if consumption is significantly affected. Different variants of filtering for a clearer signal may also be of interest. Other types of sensors, both for verification of results in this report and for testing alternatives. This may include geophones, multi-depth deflectometers and other types of accelerometers

This thesis is focused on the design and realisation of inertial navigation unit INS. The unit is capable to measure, store and send data to a PC in real-time for a later offline processing. The first part of the thesis introduces the reader with the basic principles of accelerometers, gyroscopes and MEMS sensors. An introduction to coordinate systems and measuring errors is also included. The second and third part of the thesis deals with the analysis of the solution and the implementation of the INS unit. The fourth part of the document is dedicated to the software for the INS unit. This thesis concludes with explanation how the gathered data are processed.