Microelectromechanical systems (MEMS) depend on mechanical deformation to sense their environment, enhance electrical circuitry, or store data. Nonlinear forces arising from multiphysics phenomena at the micro- and nanoscale -- van der Waals forces, electrostatic fields, dielectric charging, capillary forces, surface roughness, asperity interactions -- lead to challenging problems for analysis, simulation, and measurement of the deforming device elements. Herein, a foundation for the study of mechanical deformation is provided through computational and experimental studies of MEMS microcantilever capacitive switches. Numerical techniques are built to capture deformation equilibria expediently. A compact analytical model is developed from principle multiphysics governing operation. Experimental measurements support the phenomena predicted by the analytical model, and finite element method (FEM) simulations confirm device-specific performance. Altogether, the static multistability and quasistatic performance of the electrostatically-actuated switches are confirmed across analysis, simulation, and experimentation. <p><br></p> <p>The nonlinear multiphysics forces present in the devices are critical to the switching behavior exploited for novel applications, but are also a culprit in a common failure mode when the attractive forces overcome the restorative and repulsive forces to result in two elements sticking together. Quasistatic operation is functional for switching between multistable states during normal conditions, but is insufficient under such stiction-failure. Exploration of dynamic methods for stiction release is often the only option for many system configurations. But how and when is release achieved? To investigate the fundamental mechanism of dynamic release, an atomic force microscopy (AFM) system -- a microcantilever with a motion-controlled base and a single-asperity probe tip, measured and actuated via lasers -- is configured to replicate elements of a stiction-failed MEMS device. Through this surrogate, observable dynamic signatures of microcantilever deflection indicate the onset of detachment between the probe and a sample.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / The existing topologies of solar micro inverter use a number of stages before the DC input voltage can be converted to AC output voltage. These stages may contain one or more power converters. It may also contain a diode rectifier, transformer and filter. The number of active and passive components is very high. In this thesis, the design of a new solar micro inverter is proposed. This new micro inverter consists of a new single switch inverter which is obtained by modifying the already existing single ended primary inductor (SEPIC) DC-DC converter. This new inverter is capable of generating pure sinusoidal waveform from DC input voltage. The design and operation of the new inverter are studied in detail. This new inverter works with a controller to produce any kind of output waveform. The inverter is found to have four different modes of operation. The new inverter is modeled using state space averaging. The system is a fourth order system which is non-linear due to the inherent switching involved in the circuit. The system is linearized around an operating point to study the system as a linear system. The control to output transfer function of the inverter is found to be non-minimum phase. The transfer functions are studied using root locus. From the control perspective, the presence of right half zero makes the design of the controller structure complicated. The PV cell is modeled using the cell equations in MATLAB. A maximum power point tracking (MPPT) technique is implemented to make sure the output power of the PV cell is always maximum which allows full utilization of the power from the PV cell. The perturb and observe (P&O) algorithm is the simplest and is used here. The use of this new inverter eliminates the various stages involved in the conventional solar micro inverter. Simulation and experimental results carried out on the setup validate the proposed structure of inverter.

Trötthet i trafiken är ett stort problem i samhället. Det är särskilt farligt att trött framföra tunga lastbilar i trafiken eftersom dessa fordon är stora och har ofta livsavgörande roller vid inblandning i trafikolyckor. För att angripa problemet har det i denna rapport studerats kring vilket sömnstadie som är lämpligast att vakna under, i syfte att vakna pigg och alert samt vilka typer av tekniker och metoder som är lämpliga för att portabelt kunna detektera Rapid-Eye-Movement. Tidigare arbeten och studier har gjorts som påvisar att uppväckning i REM-sömn är optimalt för att känna sig alert. De valda metoderna är baserade på varianter av väletablerade tekniker som används för identifiering av sömnsteg. Elektrookulografi används för att mäta ögonrörelser med hjälp av fyra elektroder som är placerade på huvudet. Kroppsrörelser upptäcks genom en accelerometer som fästs på armen. Pulsmätningar görs och används för att räkna ut pulsvariansen under sömnen. Målet är att skapa en prototyp som ska känna av när användaren är i REM-sömn och sedan väcka användaren. Detta arbete är uppdelat i två inbyggda system som görs mellan två olika examensarbeten. Resultatet blev tre sensorer som fungerar individuellt. På grund av tidsbrist och en längre felsökning blev prototypen inte färdigställd. Innan sensorerna kan tillämpas i en produkt krävs det att ytterligare tester genomförs under monitorering av en sömnspecialist. / Tiredness in traffic is a major problem in society. It is especially dangerous to drive heavy trucks when tired because these vehicles are large and often have vital roles when involved in traffic accidents. To address the problem, this degree project has studied which sleep stage is most appropriate to wake up during, in order to wake up sharp and alert, and what types of techniques and methods are suitable for portable detection of Rapid-Eye-Movement. Previous work and studies have been done which indicates that awakening during REM sleep is optimal for feeling alert. The chosen methods are based on variants of well-established techniques that are used to identify sleep stages. Electrooculography is used to measure eye movements using four electrodes placed on the head. Body movements are detected by an accelerometer attached to the arm. Pulse measurements are made and used to calculate the pulse variation during sleep. The goal is to create a prototype which will know when the user is in REM sleep and then wake the user up. This work is divided into two embedded systems that are made between two different degree projects. The result was three sensors that worked individually. Due to lack of time and a longer troubleshooting, the prototype was not completed. Before the sensors can be used in a product, additional tests are required under the supervision of a sleep specialist.