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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.


Potential-Induced Degradation (PID) is an extremely serious photovoltaic (PV) durability issue significantly observed in crystalline silicon PV modules due to its rapid power degradation, particularly when compared to other PV degradation modes. The focus of this dissertation is to understand PID mechanisms and to develop PID-free cells and modules. PID-affected modules have been claimed to be fully recovered by high temperature and reverse potential treatments. However, the results obtained in this work indicate that the near-full recovery of efficiency can be achieved only at high irradiance conditions, but the full recovery of efficiency at low irradiance levels, of shunt resistance, …

Contributors
Oh, Jaewon, Bowden, Stuart, Tamizhmani, Govindasamy, et al.
Created Date
2016

Non-volatile memories (NVM) are widely used in modern electronic devices due to their non-volatility, low static power consumption and high storage density. While Flash memories are the dominant NVM technology, resistive memories such as phase change access memory (PRAM) and spin torque transfer random access memory (STT-MRAM) are gaining ground. All these technologies suffer from reliability degradation due to process variations, structural limits and material property shift. To address the reliability concerns of these NVM technologies, multi-level low cost solutions are proposed for each of them. My approach consists of first building a comprehensive error model. Next the error characteristics …

Contributors
Yang, Chengen, Chakrabarti, Chaitali, Cao, Yu, et al.
Created Date
2014

The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible and controllable loads, bidirectional communications using smart meters and other technologies. Sensory technology may be utilized as a tool that enhances operation including operation of the distribution system. Addressing this point, a distribution system state estimation algorithm is developed in this thesis. The state estimation algorithm developed here utilizes distribution …

Contributors
Haughton, Daniel Andrew, Heydt, Gerald T, Vittal, Vijay, et al.
Created Date
2012

Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following …

Contributors
Anand, Sindhu, Muthuswamy, Jitendran, Tillery, Stephen H, et al.
Created Date
2013