ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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In order to advance the development of these devices, there is a need to develop simulation models which replicate the behavior of these devices in circuits. In this thesis, a verilogA model for the PMC has been developed. The behavior of the model has been tested using DC and transient simulations. Experimental data obtained from testing PMC devices fabricated at Arizona State University have been compared to results obtained from simulation.
A basic memory cell known as the 1T 1R cell built using the PMC has also been simulated and verified. These memory cells have the potential to be building blocks of large scale memories. I believe that the verilogA model developed in this thesis will prove to be a powerful tool for researchers and circuit developers looking to develop non-volatile memories using alternative technologies.
To advance the PMC modeling effort, this thesis presents a precise physical model parameterizing materials associated with both ion-rich and ion-poor layers of the PMC's solid electrolyte, so that captures the static electrical behavior of the PMC in both its low-resistance on-state (LRS) and high resistance off-state (HRS). The experimental data is measured from a chalcogenide glass PMC designed and manufactured at ASU. The static on- and off-state resistance of a PMC device composed of a layered (Ag-rich/Ag-poor) Ge30Se70 ChG film is characterized and modeled using three dimensional simulation code written in Silvaco Atlas finite element analysis software. Calibrating the model to experimental data enables the extraction of device parameters such as material bandgaps, workfunctions, density of states, carrier mobilities, dielectric constants, and affinities.
The sensitivity of our modeled PMC to the variation of its prominent achieved material parameters is examined on the HRS and LRS impedance behavior.
The obtained accurate set of material parameters for both Ag-rich and Ag-poor ChG systems and process variation verification on electrical characteristics enables greater fidelity in PMC device simulation, which significantly enhances our ability to understand the underlying physics of ChG-based resistive switching memory.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
controllers, power line monitoring and protection systems, instrumentation systems and battery monitors require direct digitization of a high voltage input signals. Analog-to-Digital Converters (ADCs) that can digitize high voltage signals require high linearity and low voltage coefficient capacitors. A built in self-calibration and digital-trim algorithm correcting static mismatches in Capacitive Digital-to-Analog Converter (CDAC) used in Successive Approximation Register Analog to Digital Converters (SARADCs) is proposed. The algorithm uses a dynamic error correction (DEC) capacitor to cancel the static errors occurring in each capacitor of the array as the first step upon power-up and eliminates the need for an extra calibration DAC. Self-trimming is performed digitally during normal ADC operation. The algorithm is implemented on a 14-bit high-voltage input range SAR ADC with integrated dynamic error correction capacitors. The IC is fabricated in 0.6-um high voltage compliant CMOS process, accepting up to 24Vpp differential input signal. The proposed approach achieves 73.32 dB Signal to Noise and Distortion Ratio (SNDR) which is an improvement of 12.03 dB after self-calibration at 400 kS/s sampling rate, consuming 90-mW from a +/-15V supply. The calibration circuitry occupies 28% of the capacitor DAC, and consumes less than 15mW during operation. Measurement results shows that this algorithm reduces INL from as high as 7 LSBs down to 1 LSB and it works even in the presence of larger mismatches exceeding 260 LSBs. Similarly, it reduces DNL errors from 10 LSBs down to 1 LSB. The ADC occupies an active area of 9.76 mm2.
The tool, referred to as Deppy, deposits material via hypersonic impaction, a two chamber process that takes advantage of compressible fluids operating in the choked flow regime to accelerate particles to up several thousand meters per second before they impact and stick to the substrate. This allows for the energetic separation of the synthesis and deposition processes while still behaving as a continuous flow reactor giving Deppy the unique ability to independently control the particle properties and the deposited film properties. While the ultimate goal is to design a tool capable of producing a broad range of nanomaterial films, this work will showcase Deppy's ability to produce silicon nano-particle films as a proof of concept.
By adjusting parameters in the upstream chamber the particle composition was varied from completely amorphous to highly crystalline as confirmed by Raman spectroscopy. By adjusting parameters in the downstream chamber significant variation of the film's density was achieved. Further it was shown that the system is capable of making these adjustments in each chamber without affecting the operation of the other.