Lateral programmable metallization cells (PMC) utilize the properties of electrodeposits grown over a solid electrolyte channel. Such devices have an active anode and an inert cathode separated by a long electrodeposit channel in a coplanar arrangement. The ability to transport large amount of metallic mass across the channel makes these devices attractive for various More-Than-Moore applications. Existing literature lacks a comprehensive study of electrodeposit growth kinetics in lateral PMCs. Moreover, the morphology of electrodeposit growth in larger, planar devices is also not understood. Despite the variety of applications, lateral PMCs are not embraced by the semiconductor industry due to incompatible materials and high operating voltages needed for such devices. In this work, a numerical model based on the basic processes in PMCs – cation drift and redox reactions – is proposed, and the effect of various materials parameters on the electrodeposit growth kinetics is reported. The morphology of the electrodeposit growth and kinetics of the electrodeposition process are also studied in devices based on Ag-Ge30Se70 materials system. It was observed that the electrodeposition process mainly consists of two regimes of growth – cation drift limited regime and mixed regime. The electrodeposition starts in cation drift limited regime at low electric fields and transitions into mixed regime as the field increases. The onset of mixed regime can be controlled by applied voltage which also affects the morphology of electrodeposit growth. The numerical model was then used to successfully predict the device kinetics and onset of mixed regime. The problem of materials incompatibility with semiconductor manufacturing was solved by proposing a novel device structure. A bilayer structure using semiconductor foundry friendly materials was suggested as a candidate for solid electrolyte. The bilayer structure consists of a low resistivity oxide shunt layer on top of a high resistivity ion carrying oxide layer. Devices using Cu2O as the low resistivity shunt on top of Cu doped WO3 oxide were fabricated. The bilayer devices provided orders of magnitude improvement in device performance in the context of operating voltage and switching time. Electrical and materials characterization revealed the structure of bilayers and the mechanism of electrodeposition in these devices.

In recent years, the Silicon Super-Junction (SJ) power metal-oxide semiconductor field-effect transistor (MOSFET), has garnered significant interest from spacecraft designers. This is due to their high breakdown voltage and low specific on-state resistance characteristics. Most of the previous research work on power MOSFETS for space applications concentrated on improving the radiation tolerance of low to medium voltage (~ 300V) power MOSFETs. Therefore, understanding and improving the reliability of high voltage SJMOS for the harsh space radiation environment is an important endeavor.In this work, a 600V commercially available silicon planar gate SJMOS is used to study the SJ technology’s tolerance against total ionizing dose (TID) and destructive single event effects (SEE), such as, single event burnout (SEB) and single event gate rupture (SEGR). A technology computer aided design (TCAD) software tool is used to design the SJMOS and simulate its electrical characteristics.
Electrical characterization of SJMOS devices showed substantial decrease in threshold voltage and increase in leakage current due to TID. Therefore, as a solution to improve the TID tolerance, metal-nitride-oxide-semiconductor (MNOS) capacitors with different oxide
itride thickness combinations were fabricated and irradiated using a Co-60 gamma-source. Electrical characterization showed all samples with oxide
itride stack gate insulators exhibited significantly higher tolerance to irradiation when compared to metal-oxide-semiconductor capacitors.
Heavy ion testing of the SJMOS showed the device failed due to SEB and SEGR at 10% of maximum rated bias values. In this work, a 600V SJMOS structure is designed that is tolerant to both SEB and SEGR. In a SJMOS with planar gate, reducing the neck width improves the tolerance to SEGR but significantly changes the device electrical characteristics. The trench gate SJ device design is shown to overcome this problem. A buffer layer and larger P+-plug are added to the trench gate SJ power transistor to improve SEB tolerance. Using TCAD simulations, the proposed trench gate structure and the tested planar gate SJMOS are compared. The simulation results showed that the SEB and SEGR hardness in the proposed structure has improved by a factor of 10 and passes at the device’s maximum rated bias value with improved electrical performance.

The purpose of this research is to optically characterize the band gaps of sulfide-based chalcogenides and copper oxide thin films. The analysis on the copper oxide thin films will view the effects of various annealing temperatures and the analysis of the chalcogenides will view the effects of silver doping on the thin films. Using UV-Vis spectroscopy, parameters such as the absorption coefficient and determined which then provide details on the optical band gaps of these various semiconductors. With a better understanding of the bandgap of these materials, the behavior can be better predicted in fields of nanoionics and photonics.

With the rapid advancement in the technologies related to renewable energies such

as solar, wind, fuel cell, and many more, there is a definite need for new power con

verting methods involving data-driven methodology. Having adequate information is

crucial for any innovative ideas to fructify; accordingly, moving away from traditional

methodologies is the most practical way of giving birth to new ideas. While working

on a DC-DC buck converter, the input voltages considered for running the simulations

are varied for research purposes. The critical aspect of the new data-driven method

ology is to propose a machine learning algorithm. In this design, solving for inductor

value and power switching losses, the parameters can be achieved while keeping the

input and output ratio close to the value as necessary. Thus, implementing machine

learning algorithms with the traditional design of a non-isolated buck converter deter

mines the optimal outcome for the inductor value and power loss, which is achieved

by assimilating a DC-DC converter and data-driven methodology.

The present thesis investigates the different outcomes from machine learning al

gorithms in comparison with the dynamic equations. Specifically, the DC-DC buck

converter will be focused on the thesis. In order to determine the most effective way

of keeping the system in a steady-state, different circuit buck converter with different

parameters have been performed.

At present, artificial intelligence plays a vital role in power system control and

theory. Consequently, in this thesis, the approximation error estimation has been

analyzed in a DC-DC buck converter model, with specific consideration of machine

learning algorithms tools that can help detect and calculate the difference in terms

of error. These tools, called models, are used to analyze the collected data. In the

present thesis, a focus on such models as K-nearest neighbors (K-NN), specifically

the Weighted-nearest neighbor (WKNN), is utilized for machine learning algorithm

purposes. The machine learning concept introduced in the present thesis lays down

the foundation for future research in this area so that to enable further research on

efficient ways to improve power electronic devices with reduced power switching losses

and optimal inductor values.

The Barrett Honors Student, Cameron Berns, was asked to characterize a torque control solution for a myoelectric controlled prosthetic hand. The student performed several tasks above the senior design scope for the honors portion that include: experimentation to find the best torque control solution, design of a digital control system and debug board, perform idealistic characterization on the chosen torque control option, and finally research future implementation for total system identification. The experiments were a success and a crude implementation was achieved.

Interposers have been used in the system packaging industry for years. They have advanced from basic devices used for connection to providing new opportunities for System-in-Package and System-on-Chip architectures. Currently interposers cannot be reconfigured. Systems may implement extra input-output connections for hard reconfiguration. However, programmable metallization cells (PMC) offer the opportunity to change this. PMCs offer reliable and fast switching that has the potential to be used as resistive memory cells as well. PMCs operate by growing a metal filament from the device cathode to its anode through a solid electrolyte by applying a voltage. By reversing the voltage bias, the filament will retract. The PMC’s electrolyte can also be made from a range of materials being chalcogen or oxide based, allowing for integration in a variety of systems. By utilizing PMCs in an interposer to create a “smart interposer,” it would be possible to create easily reconfigurable systems. This project investigated how PMCs function in a lab setting. By using a probe station, the current-voltage characteristics were generated for a variety of limiting current values. The PMC on and off state resistances were extrapolated for further understanding of its switch function. In addition, works-like prototypes were developed to show the function a smart interposer. In these prototypes, transistors or relays were used as the switching mechanism in place of the PMCs. The final works-like prototype demonstrated how a smart interposer might function by using a switching mechanism to swap between half adder and full adder outputs for the same inputs.

There is a demonstrable issue in how new medical technologies are developed. The consumer market is always overflowing with the newest possible technologies; however, this is often not the case in the medical field. The consumer market refers to a product that any individual can buy in a retail store, whereas a product for the medical field is prescribed by a clinician for use by a patient. The development of devices usually targets the consumer market rather than the medical field. This trend leads to the development of devices that may have consumer and clinical benefits not receiving consideration in the clinical market because they are not designed with a strictly medical purpose in mind. This is an issue that needs rectification, as injured patients deserve the best possible care with the best technologies available. The development of these technologies should not be limited by a lack of communication between clinicians and engineers. This thesis will explore why product development in the medical field lags behind that of the consumer market. It will also offer practical solutions, as well as having an engineering team develop a device specifically for use in the medical field. The development of this product will show that the lack of communication between clinicians and engineers is possible to overcome. From this development process, recommendations will be made to offer specific solutions to overcome the communication barrier and aid future product development.

Metallically embedded dendritic structures have the potential to become a cost-effective means of conducting microwave frequency identification. They are grown quickly and contain no extra circuitry. However, their reaction to microwave frequency signatures has been unknown. Fractals Unlimited (the thesis group) aimed to test the viability of the dendritic structures to produce unique electromagnetic signatures through the transmission and reflection of microwaves. This report will detail the work that was done by one team member throughout the last two semesters.

The diagnosis for an attention deficit/hyperactivity disorder (ADHD) in children is heavily based on teacher or parent opinion, and not on scientific evidence. This causes children to be wrongly diagnosed with a disorder and be prescribed medicine that they do not need to be taking. This paper discusses a project that was completed for the Child Study Lab (CSL) preschool at Arizona State University (ASU), in which children’s activity within a classroom was automatically recorded using ultra-wideband technology. This project’s goal was to gather location data on the children in the CSL and analyze and assess the collected data for any patterns of behavior. The hope was that if a child’s data displayed a pattern that strayed from the norm, that this analysis could pose as a more objective way to indicate that a child may have an attention deficit problem. Fractal Dimensions and Levy Flights were researched and applied to the data analysis portion of this project.

The NASA Psyche Iron Meteorite Imaging System (IMIS) is a standalone system created to image metal meteorites from ASU’s Center for Meteorite Studies’ collection that have an etched surface. Meteorite scientists have difficulty obtaining true-to-life images of meteorites through traditional photography methods due to the meteorites’ shiny, irregular surfaces, which interferes with their ability to identify meteorites’ component materials through image analysis. Using the IMIS, scientists can easily and consistently obtain glare-free photographs of meteorite surface that are suitable for future use in an artificial intelligence-based meteorite component analysis system. The IMIS integrates a lighting system, a mounted camera, a sample positioning area, a meteorite leveling/positioning system, and a touch screen control panel featuring an interface that allows the user to see a preview of the image to be taken as well as an edge detection view, a glare detection view, a button that allows the user to remotely take the picture, and feedback if very high levels of glare are detected that may indicate a camera or positioning error. Initial research and design work were completed by the end of Fall semester, and Spring semester consisted of building and testing the system. The current system is fully functional, and photos taken by the current system have been approved by a meteorite expert and an AI expert. The funding for this project was tentatively capped at $1000 for miscellaneous expenses, not including a camera to be supplied by the School of Earth and Space Exploration. When SESE was unable to provide a camera, an additional $4000 were allotted for camera expenses. So far, $1935 of the total $5000 budget has been spent on the project, putting the project $3065 under budget. While this system is a functional prototype, future capstone projects may involve the help of industrial designers to improve the technician’s experience through automating the sample positioning process.