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- Creators: Phelan, Patrick
- Creators: Goryll, Michael
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Description
Chalcogenide glass (ChG) materials have gained wide attention because of their applications in conductive bridge random access memory (CBRAM), phase change memories (PC-RAM), optical rewritable disks (CD-RW and DVD-RW), microelectromechanical systems (MEMS), microfluidics, and optical communications. One of the significant properties of ChG materials is the change in the resistivity of the material when a metal such as Ag or Cu is added to it by diffusion. This study demonstrates the potential radiation-sensing capabilities of two metal/chalcogenide glass device configurations. Lateral and vertical device configurations sense the radiation-induced migration of Ag+ ions in germanium selenide glasses via changes in electrical resistance between electrodes on the ChG. Before irradiation, these devices exhibit a high-resistance `OFF-state' (in the order of 10E12) but following irradiation, with either 60-Co gamma-rays or UV light, their resistance drops to a low-resistance `ON-state' (around 10E3). Lateral devices have exhibited cyclical recovery with room temperature annealing of the Ag doped ChG, which suggests potential uses in reusable radiation sensor applications. The feasibility of producing inexpensive flexible radiation sensors has been demonstrated by studying the effects of mechanical strain and temperature stress on sensors formed on flexible polymer substrate. The mechanisms of radiation-induced Ag/Ag+ transport and reactions in ChG have been modeled using a finite element device simulator, ATLAS. The essential reactions captured by the simulator are radiation-induced carrier generation, combined with reduction/oxidation for Ag species in the chalcogenide film. Metal-doped ChGs are solid electrolytes that have both ionic and electronic conductivity. The ChG based Programmable Metallization Cell (PMC) is a technology platform that offers electric field dependent resistance switching mechanisms by formation and dissolution of nano sized conductive filaments in a ChG solid electrolyte between oxidizable and inert electrodes. This study identifies silver anode agglomeration in PMC devices following large radiation dose exposure and considers device failure mechanisms via electrical and material characterization. The results demonstrate that by changing device structural parameters, silver agglomeration in PMC devices can be suppressed and reliable resistance switching may be maintained for extremely high doses ranging from 4 Mrad(GeSe) to more than 10 Mrad (ChG).
ContributorsDandamudi, Pradeep (Author) / Kozicki, Michael N (Thesis advisor) / Barnaby, Hugh J (Committee member) / Holbert, Keith E. (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Analysing and measuring of biological or biochemical processes are of utmost importance for medical, biological and biotechnological applications. Point of care diagnostic system, composing of biosensors, have promising applications for providing cheap, accurate and portable diagnosis. Owing to these expanding medical applications and advances made by semiconductor industry biosensors have seen a tremendous growth in the past few decades. Also emergence of microfluidics and non-invasive biosensing applications are other marker propellers. Analyzing biological signals using transducers is difficult due to the challenges in interfacing an electronic system to the biological environment. Detection limit, detection time, dynamic range, specificity to the analyte, sensitivity and reliability of these devices are some of the challenges in developing and integrating these devices. Significant amount of research in the field of biosensors has been focused on improving the design, fabrication process and their integration with microfluidics to address these challenges. This work presents new techniques, design and systems to improve the interface between the electronic system and the biological environment. This dissertation uses CMOS circuit design to improve the reliability of these devices. Also this work addresses the challenges in designing the electronic system used for processing the output of the transducer, which converts biological signal into electronic signal.
ContributorsShah, Sahil S (Author) / Christen, Jennifer B (Thesis advisor) / Allee, David (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
Within the last decade there has been remarkable interest in single-cell metabolic analysis as a key technology for understanding cellular heterogeneity, disease initiation, progression, and drug resistance. Technologies have been developed for oxygen consumption rate (OCR) measurements using various configurations of microfluidic devices. The technical challenges of current approaches include: (1) deposition of multiple sensors for multi-parameter metabolic measurements, e.g. oxygen, pH, etc.; (2) tedious and labor-intensive microwell array fabrication processes; (3) low yield of hermetic sealing between two rigid fused silica parts, even with a compliance layer of PDMS or Parylene-C. In this thesis, several improved microfabrication technologies are developed and demonstrated for analyzing multiple metabolic parameters from single cells, including (1) a modified "lid-on-top" configuration with a multiple sensor trapping (MST) lid which spatially confines multiple sensors to micro-pockets enclosed by lips for hermetic sealing of wells; (2) a multiple step photo-polymerization method for patterning three optical sensors (oxygen, pH and reference) on fused silica and on a polyethylene terephthalate (PET) surface; (3) a photo-polymerization method for patterning tri-color (oxygen, pH and reference) optical sensors on both fused silica and on the PET surface; (4) improved KMPR/SU-8 microfabrication protocols for fabricating microwell arrays that can withstand cell culture conditions. Implementation of these improved microfabrication methods should address the aforementioned challenges and provide a high throughput and multi-parameter single cell metabolic analysis platform.
ContributorsSong, Ganquan (Author) / Meldrum, Deirdre R (Thesis advisor) / Goryll, Michael (Committee member) / Wang, Hong (Committee member) / Tian, Yanqing (Committee member) / Arizona State University (Publisher)
Created2014
Description
Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.
ContributorsYi, Chong-hwan (Author) / Jindrich, Devin L. (Thesis advisor) / Artemiadis, Panagiotis K. (Thesis advisor) / Phelan, Patrick (Committee member) / Santos, Veronica J. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2014
Description
Inductors are fundamental components that do not scale well. Their physical limitations to scalability along with their inherent losses make them the main obstacle in achieving monolithic system-on-chip platform (SoCP). For past decades researchers focused on integrating magnetic materials into on-chip inductors in the quest of achieving high inductance density and quality factor (QF). The state of the art on-chip inductor is made of an enclosed magnetic thin-film around the current carrying wire for maximum flux amplification. Though the integration of magnetic materials results in enhanced inductor characteristics, this approach has its own challenges and limitations especially in power applications. The current-induced magnetic field (HDC) drives the magnetic film into its saturation state. At saturation, inductance and QF drop to that of air-core inductors, eliminating the benefits of integrating magnetic materials. Increasing the current carrying capability without substantially sacrificing benefits brought on by the magnetic material is an open challenge in power applications. Researchers continue to address this challenge along with the continuous improvement in inductance and QF for RF and power applications.
In this work on-chip inductors incorporating magnetic Co-4%Zr-4%Ta -8%B thin films were fabricated and their characteristics were examined under the influence of an externally applied DC magnetic field. It is well established that spins in magnetic materials tend to align themselves in the same direction as the applied field. The resistance of the inductor resulting from the ferromagnetic film can be changed by manipulating the orientation of magnetization. A reduction in resistance should lead to decreases in losses and an enhancement in the QF. The effect of externally applied DC magnetic field along the easy and hard axes was thoroughly investigated. Depending on the strength and orientation of the externally applied field significant improvements in QF response were gained at the expense of a relative reduction in inductance. Characteristics of magnetic-based inductors degrade with current-induced stress. It was found that applying an externally low DC magnetic field across the on-chip inductor prevents the degradation in inductance and QF responses. Examining the effect of DC magnetic field on current carrying capability under low temperature is suggested.
In this work on-chip inductors incorporating magnetic Co-4%Zr-4%Ta -8%B thin films were fabricated and their characteristics were examined under the influence of an externally applied DC magnetic field. It is well established that spins in magnetic materials tend to align themselves in the same direction as the applied field. The resistance of the inductor resulting from the ferromagnetic film can be changed by manipulating the orientation of magnetization. A reduction in resistance should lead to decreases in losses and an enhancement in the QF. The effect of externally applied DC magnetic field along the easy and hard axes was thoroughly investigated. Depending on the strength and orientation of the externally applied field significant improvements in QF response were gained at the expense of a relative reduction in inductance. Characteristics of magnetic-based inductors degrade with current-induced stress. It was found that applying an externally low DC magnetic field across the on-chip inductor prevents the degradation in inductance and QF responses. Examining the effect of DC magnetic field on current carrying capability under low temperature is suggested.
ContributorsKhdour, Mahmoud (Author) / Yu, Hongbin (Thesis advisor) / Pan, George (Committee member) / Goryll, Michael (Committee member) / Bearat, Hamdallah (Committee member) / Arizona State University (Publisher)
Created2014
Description
Semiconductor manufacturing economics necessitate the development of innovative device measurement techniques for quick assessment of products. Several novel electrical measurement techniques will be proposed for screening silicon device parameters. The studied parameters range from oxide reliability, and carrier lifetime in MOS capacitors to the power MOSFET reverse recovery.
It will be shown that positive charge trapping is a dominant process when thick oxides are stressed through the ramped voltage test (RVT). Exploiting the physics behind positive charge generation/trapping at high electric fields, a fast I-V measurement technique is proposed that can be used to effectively distinguish the ultra-thick oxides' intrinsic quality at low electric fields.
Next, two novel techniques will be presented for studying the carrier lifetime in MOS Capacitor devices. It will be shown that the deep-level transient spectroscopy (DLTS) can be applied to MOS test structures as a swift mean for screening the generation lifetime. Recombination lifetime will also be addressed by introducing the optically-excited MOS technique as a promising tool.
The last part of this work is devoted to the reverse recovery behavior of the body diode of power MOSFETs. The correct interpretation of the LDMOS reverse recovery is challenging and requires special attention. A simple approach will be presented to extract meaningful lifetime values from the reverse recovery of LDMOS body-diodes exploiting their gate voltage and the magnitude of the reverse bias.
It will be shown that positive charge trapping is a dominant process when thick oxides are stressed through the ramped voltage test (RVT). Exploiting the physics behind positive charge generation/trapping at high electric fields, a fast I-V measurement technique is proposed that can be used to effectively distinguish the ultra-thick oxides' intrinsic quality at low electric fields.
Next, two novel techniques will be presented for studying the carrier lifetime in MOS Capacitor devices. It will be shown that the deep-level transient spectroscopy (DLTS) can be applied to MOS test structures as a swift mean for screening the generation lifetime. Recombination lifetime will also be addressed by introducing the optically-excited MOS technique as a promising tool.
The last part of this work is devoted to the reverse recovery behavior of the body diode of power MOSFETs. The correct interpretation of the LDMOS reverse recovery is challenging and requires special attention. A simple approach will be presented to extract meaningful lifetime values from the reverse recovery of LDMOS body-diodes exploiting their gate voltage and the magnitude of the reverse bias.
ContributorsElhami Khorasani, Arash (Author) / Alford, Terry L. (Thesis advisor) / Goryll, Michael (Committee member) / Theodore, David (Committee member) / Arizona State University (Publisher)
Created2015
Description
This work explores how flexible electronics and display technology can be applied to develop new biomedical devices for medical, biological, and life science applications. It demonstrates how new biomedical devices can be manufactured by only modifying or personalizing the upper layers of a conventional thin film transistor (TFT) display process. This personalization was applied first to develop and demonstrate the world's largest flexible digital x-ray detector for medical and industrial imaging, and the world's first flexible ISFET pH biosensor using TFT technology. These new, flexible, digital x-ray detectors are more durable than conventional glass substrate x-ray detectors, and also can conform to the surface of the object being imaged. The new flexible ISFET pH biosensors are >10X less expensive to manufacture than comparable CMOS-based ISFETs and provide a sensing area that is orders of magnitude larger than CMOS-based ISFETs. This allows for easier integration with area intensive chemical and biological recognition material as well as allow for a larger number of unique recognition sites for low cost multiple disease and pathogen detection.
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.
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.
ContributorsSmith, Joseph T. (Author) / Allee, David (Thesis advisor) / Goryll, Michael (Committee member) / Kozicki, Michael (Committee member) / Blain Christen, Jennifer (Committee member) / Couture, Aaron (Committee member) / Arizona State University (Publisher)
Created2014
Optimization of the implementation of renewable resources in a municipal electric utility in Arizona
Description
A municipal electric utility in Mesa, Arizona with a peak load of approximately 85 megawatts (MW) was analyzed to determine how the implementation of renewable resources (both wind and solar) would affect the overall cost of energy purchased by the utility. The utility currently purchases all of its energy through long term energy supply contracts and does not own any generation assets and so optimization was achieved by minimizing the overall cost of energy while adhering to specific constraints on how much energy the utility could purchase from the short term energy market. Scenarios were analyzed for a five percent and a ten percent penetration of renewable energy in the years 2015 and 2025. Demand Side Management measures (through thermal storage in the City's district cooling system, electric vehicles, and customers' air conditioning improvements) were evaluated to determine if they would mitigate some of the cost increases that resulted from the addition of renewable resources.
In the 2015 simulation, wind energy was less expensive than solar to integrate to the supply mix. When five percent of the utility's energy requirements in 2015 are met by wind, this caused a 3.59% increase in the overall cost of energy. When that five percent is met by solar in 2015, it is estimated to cause a 3.62% increase in the overall cost of energy. A mix of wind and solar in 2015 caused a lower increase in the overall cost of energy of 3.57%. At the ten percent implementation level in 2015, solar, wind, and a mix of solar and wind caused increases of 7.28%, 7.51% and 7.27% respectively in the overall cost of energy.
In 2025, at the five percent implementation level, wind and solar caused increases in the overall cost of energy of 3.07% and 2.22% respectively. In 2025, at the ten percent implementation level, wind and solar caused increases in the overall cost of energy of 6.23% and 4.67% respectively.
Demand Side Management reduced the overall cost of energy by approximately 0.6%, mitigating some of the cost increase from adding renewable resources.
In the 2015 simulation, wind energy was less expensive than solar to integrate to the supply mix. When five percent of the utility's energy requirements in 2015 are met by wind, this caused a 3.59% increase in the overall cost of energy. When that five percent is met by solar in 2015, it is estimated to cause a 3.62% increase in the overall cost of energy. A mix of wind and solar in 2015 caused a lower increase in the overall cost of energy of 3.57%. At the ten percent implementation level in 2015, solar, wind, and a mix of solar and wind caused increases of 7.28%, 7.51% and 7.27% respectively in the overall cost of energy.
In 2025, at the five percent implementation level, wind and solar caused increases in the overall cost of energy of 3.07% and 2.22% respectively. In 2025, at the ten percent implementation level, wind and solar caused increases in the overall cost of energy of 6.23% and 4.67% respectively.
Demand Side Management reduced the overall cost of energy by approximately 0.6%, mitigating some of the cost increase from adding renewable resources.
ContributorsCadorin, Anthony (Author) / Phelan, Patrick (Thesis advisor) / Calhoun, Ronald (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation presents my work on development of deformable electronics using microelectromechanical systems (MEMS) based fabrication technologies. In recent years, deformable electronics are coming to revolutionize the functionality of microelectronics seamlessly with their application environment, ranging from various consumer electronics to bio-medical applications. Many researchers have studied this area, and a wide variety of devices have been fabricated. One traditional way is to directly fabricate electronic devices on flexible substrate through low-temperature processes. These devices suffered from constrained functionality due to the temperature limit. Another transfer printing approach has been developed recently. The general idea is to fabricate functional devices on hard and planar substrates using standard processes then transferred by elastomeric stamps and printed on desired flexible and stretchable substrates. The main disadvantages are that the transfer printing step may limit the yield. The third method is "flexible skins" which silicon substrates are thinned down and structured into islands and sandwiched by two layers of polymer. The main advantage of this method is post CMOS compatible. Based on this technology, we successfully fabricated a 3-D flexible thermal sensor for intravascular flow monitoring. The final product of the 3-D sensor has three independent sensing elements equally distributed around the wall of catheter (1.2 mm in diameter) with 120° spacing. This structure introduces three independent information channels, and cross-comparisons among all readings were utilized to eliminate experimental error and provide better measurement results. The novel fabrication and assembly technology can also be applied to other catheter based biomedical devices. A step forward inspired by the ancient art of folding, origami, which creating three-dimensional (3-D) structures from two-dimensional (2-D) sheets through a high degree of folding along the creases. Based on this idea, we developed a novel method to enable better deformability. One example is origami-enabled silicon solar cells. The solar panel can reach up to 644% areal compactness while maintain reasonable good performance (less than 30% output power density drop) upon 40 times cyclic folding/unfolding. This approach can be readily applied to other functional devices, ranging from sensors, displays, antenna, to energy storage devices.
ContributorsTang, Rui (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Pan, George (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
Feature representations for raw data is one of the most important component in a machine learning system. Traditionally, features are \textit{hand crafted} by domain experts which can often be a time consuming process. Furthermore, they do not generalize well to unseen data and novel tasks. Recently, there have been many efforts to generate data-driven representations using clustering and sparse models. This dissertation focuses on building data-driven unsupervised models for analyzing raw data and developing efficient feature representations.
Simultaneous segmentation and feature extraction approaches for silicon-pores sensor data are considered. Aggregating data into a matrix and performing low rank and sparse matrix decompositions with additional smoothness constraints are proposed to solve this problem. Comparison of several variants of the approaches and results for signal de-noising and translocation/trapping event extraction are presented. Algorithms to improve transform-domain features for ion-channel time-series signals based on matrix completion are presented. The improved features achieve better performance in classification tasks and in reducing the false alarm rates when applied to analyte detection.
Developing representations for multimedia is an important and challenging problem with applications ranging from scene recognition, multi-media retrieval and personal life-logging systems to field robot navigation. In this dissertation, we present a new framework for feature extraction for challenging natural environment sounds. Proposed features outperform traditional spectral features on challenging environmental sound datasets. Several algorithms are proposed that perform supervised tasks such as recognition and tag annotation. Ensemble methods are proposed to improve the tag annotation process.
To facilitate the use of large datasets, fast implementations are developed for sparse coding, the key component in our algorithms. Several strategies to speed-up Orthogonal Matching Pursuit algorithm using CUDA kernel on a GPU are proposed. Implementations are also developed for a large scale image retrieval system. Image-based "exact search" and "visually similar search" using the image patch sparse codes are performed. Results demonstrate large speed-up over CPU implementations and good retrieval performance is also achieved.
Simultaneous segmentation and feature extraction approaches for silicon-pores sensor data are considered. Aggregating data into a matrix and performing low rank and sparse matrix decompositions with additional smoothness constraints are proposed to solve this problem. Comparison of several variants of the approaches and results for signal de-noising and translocation/trapping event extraction are presented. Algorithms to improve transform-domain features for ion-channel time-series signals based on matrix completion are presented. The improved features achieve better performance in classification tasks and in reducing the false alarm rates when applied to analyte detection.
Developing representations for multimedia is an important and challenging problem with applications ranging from scene recognition, multi-media retrieval and personal life-logging systems to field robot navigation. In this dissertation, we present a new framework for feature extraction for challenging natural environment sounds. Proposed features outperform traditional spectral features on challenging environmental sound datasets. Several algorithms are proposed that perform supervised tasks such as recognition and tag annotation. Ensemble methods are proposed to improve the tag annotation process.
To facilitate the use of large datasets, fast implementations are developed for sparse coding, the key component in our algorithms. Several strategies to speed-up Orthogonal Matching Pursuit algorithm using CUDA kernel on a GPU are proposed. Implementations are also developed for a large scale image retrieval system. Image-based "exact search" and "visually similar search" using the image patch sparse codes are performed. Results demonstrate large speed-up over CPU implementations and good retrieval performance is also achieved.
ContributorsSattigeri, Prasanna S (Author) / Spanias, Andreas (Thesis advisor) / Thornton, Trevor (Committee member) / Goryll, Michael (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2014