Engineering Commons^™

Design, Fabrication And Characterization Of Zero Power Sensor/Harvester For Smart Grid Applications, Zeynel Guler

Mechanical Engineering ETDs

This study presents a flexible sensor/harvester device to be used in both electromagnetic sensing and energy harvesting applications for smart grids. When a current passes through a wire, the sensor detects the magnetic field created by that current. The sensor magnet interacts with the wire magnetic field resulting in a transfer of energy through the piezoelectric cantilever. Piezoelectric, conductive, magnetic, and magnetostrictive composite thin films were prepared to fabricate this device.

Initially, the magnet of the cantilever was optimized considering its shape, thickness, length, taper angle etc. via both simulations and experiments. Peak to peak voltage versus cantilever position graph …

Modeling And Characterization Of Cmos Logic Gates Under Large Signal Rf Injection, Zahra Abedi

Electrical and Computer Engineering ETDs

This research addresses the issue of electromagnetic interference (EMI) in digital electronics, which can cause undesired behavior in active electronic components and systems. As technology advances and transistor size decreases, devices become more susceptible to EMI. In addition, as voltage is scaled down to save energy, silicon chips become more susceptible to soft errors. While there are several ways to mitigate the impact of severe EMI on digital systems, minimal electromagnetic coupling can still cause significant problems. We develop analytical models to predict device upset due to EMI. The study focuses on identifying vulnerable parameters of operation related to device …

Vi Energy-Efficient Memristor-Based Neuromorphic Computing Circuits And Systems For Radiation Detection Applications, Jorge Iván Canales Verdial

Electrical and Computer Engineering ETDs

Radionuclide spectroscopic sensor data is analyzed with minimal power consumption through the use of neuromorphic computing architectures. Memristor crossbars are harnessed as the computational substrate in this non-conventional computing platform and integrated with CMOS-based neurons to mimic the computational dynamics observed in the mammalian brain’s visual cortex. Functional prototypes using spiking sparse locally competitive approximations are presented. The architectures are evaluated for classification accuracy and energy efficiency. The proposed systems achieve a 90% true positive accuracy with a high-resolution detector and 86% with a low-resolution detector.

Evaluation Of The Dynamic Vision Sensor’S Photoreceptor Circuit For Infrared Event-Based Sensing, Zinah M. Alsaad

Electrical and Computer Engineering ETDs

For space surveillance applications, neuromorphic imaging is being studied as it may perform sensing and tracking tasks with less power and downstream datalink demand. The read-out of the event-based camera is made to only be sensitive to changes in the signals it receives from the photodetector, which results in a datastream of events indicating where and when changes in illumination occur. This is in contrast to the conventional framing camera, which produces images by essentially counting the electrons produced by light incident on each pixel’s photodetector. These cameras are commercially available with siliconbased detectors for applications involving visible wavelengths. However, …