Matching Items (98)
Filtering by
Description
The vastly growing field of supercomputing is in dire need of a new measurement system to optimize JMRAM (Josephson junction magnetoresistive random access memory) devices. To effectively measure these devices, an ultra-low-noise, low cost cryogenic dipping probe with a dynamic voltage range is required. This dipping probe has been designed by ASU with <100 nVp-p noise, <10 nV offsets, 10 pV to 16 mV voltage range, and negligible thermoelectric drift. There is currently no other research group or company that can currently match both these low noise levels and wide voltage range. Two different dipping probes can be created with these specifications: one for high-use applications and one for low-use applications. The only difference between these probes is the outer shell; the high-use application probe has a shell made of G-10 fiberglass for a higher price, and the low-use application probe has a shell made of AISI 310 steel for a lower price. Both types of probes can be assembled in less than 8 hours for less than $2,500, requiring only soldering expertise. The low cost and short time to create these probes makes wide profit margins possible. The market for these cryogenic dipping probes is currently untapped, as most research groups and companies that use these probes build their own, which allows for rapid business growth. These potential consumers can be easily reached by marketing these probes at superconducting conferences. After several years of selling >50 probes, mass production can easily become possible by hiring several technicians, and still maintaining wide profit margins.
ContributorsHudson, Brooke Ashley (Author) / Adams, James (Thesis director) / Anwar, Shahriar (Committee member) / Materials Science and Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
How can we change what it means to be a human? Products can be used that will allow for near-instantaneous communication with one’s friends and family wherever they are: and the newest devices do not have to be even carried around, as they can be worn instead. Wearable electronics are quickly becoming very popular, with 232.0 million wearable devices sold in 2015. This report provides an overview of current and developing wearable devices, investigates the characteristics of the average buyer for these different types of devices. Finally, marketing strategies are suggested. This work was completed in conjunction with a capstone project with Intel, where three objectives were achieved: First, a universal strain tester that could strain samples cyclically in a manner similar to the body was designed. This equipment was especially designed to be flexible in the testing conditions it could be exposed to, so samples could be tested at elevated temperatures or even underwater. Next, dogbone shaped samples for the testing of Young’s Modulus and elongation to failure were produced, and the cut quality of laser, water-jet, and die-cutting was compared in order to select the most defect-free method for reliable testing. Polydimethylsiloxane (PDMS) is a fantastic candidate material for wearable electronics, however there is some discrepancies in the literature—such as from Eleni et. al—about the impact of ultraviolet radiation on the mechanical properties. By conducting accelerated aging tests simulating up to five years exposure to the sun, it was determined that ultraviolet-induced cross-linking of the polymer chains does occur, leading to severe embrittlement (strain to failure reduced from 3.27 to 0.06 in some cases, reduction to approximately 0.21 on average). As simulated tests of possible usage conditions required strains of at least 0.50-0.70, a variety of solutions were suggested to reduce this embrittlement. This project can lead to standardization of wearables electronics testing methods for more reliable predictions about the device behavior, whether that device is a simple pedometer or something that allows the visually impaired to “see”, such as Toyota’s Blaid.
ContributorsNiebroski, Alexander Wayne (Author) / Adams, James (Thesis director) / Anwar, Shahriar (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The work for this thesis was done in conjunction to that of my capstone project, which focused on understanding the effects of powder re-use on products built via Direct Metal Laser Sintering (DMLS), a specific additive manufacturing (AM) technique where powder particles are sintered together to form final parts. Honeywell Aerospace helped support this research by providing materials and mentorship; this work will play a key role in their decision to implement DMLS and other AM methods on a larger scale. Whereas the capstone focuses on the technical details of constructing characterization equipment, analyzing data, and formulating a concluding recommendation on whether the powder can be re-used, the thesis attempts to put this body of work in its greater context, surveying the economic and environmental effects of additive manufacturing technologies with a slant towards the aerospace industry. Shifts in the supply chain with aircraft parts and how this affects costs are explored, as well as how the quality and reliability of additively manufactured parts differs from their traditionally manufactured counterparts and the effects of this on related industries and purchasers.
ContributorsMurella, Anoosha Sainagaki (Author) / Adams, James (Thesis director) / Tasooji, Amaneh (Committee member) / Materials Science and Engineering Program (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the abovementioned techniques were optimized. In addition, MALDI mass spectrometry based peptide synthesis characterization on semiconductor microchips was developed and novel applications of a CombiMatrix (CBMX) platform for electrochemically controlled synthesis were explored. We have investigated performance of 2-(2-nitrophenyl)propoxycarbonyl (NPPOC) derivatives as photo-labile protecting group. Specifically, influence of substituents on 4 and 5 positions of phenyl ring of NPPOC group on the rate of photolysis and the yield of the amine was investigated. The results indicated that substituents capable of forming a π-network with the nitro group enhanced the rate of photolysis and yield. Once such properly substituted NPPOC groups were used, the rate of photolysis/yield depended on the nature of protected amino group indicating that a different chemical step during the photo-cleavage process became the rate limiting step. We also focused on electrochemically-directed parallel synthesis of high-density peptide microarrays using the CBMX technology referred to above which uses electrochemically generated acids to perform patterned chemistry. Several issues related to peptide synthesis on the CBMX platform were studied and optimized, with emphasis placed on the reactions of electro-generated acids during the deprotection step of peptide synthesis. We have developed a MALDI mass spectrometry based method to determine the chemical composition of microarray synthesis, directly on the feature. This method utilizes non-diffusional chemical cleavage from the surface, thereby making the chemical characterization of high-density microarray features simple, accurate, and amenable to high-throughput. CBMX Corp. has developed a microarray reader which is based on electro-chemical detection of redox chemical species. Several parameters of the instrument were studied and optimized and novel redox applications of peptide microarrays on CBMX platform were also investigated using the instrument. These include (i) a search of metal binding catalytic peptides to reduce overpotential associated with water oxidation reaction and (ii) an immobilization of peptide microarrays using electro-polymerized polypyrrole.
ContributorsKumar, Pallav (Author) / Woodbury, Neal (Thesis advisor) / Allen, James (Committee member) / Johnston, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Organic light-emitting diodes (OLEDs) have been successfully implemented in various display applications owing to rapid advancements in material design and device architecture. Their success in the display industry has ignited a rising interest in applying OLEDs for solid-state lighting applications through the development of white OLEDs (WOLEDs). However, to enter the market as a serious competitor, WOLEDs must achieve excellent color quality, high external quantum efficiency (EQE) as well as a long operational lifetime. In this research, novel materials and device architectures were explored to improve the performance of single-stack WOLEDs. A new Pt-based phosphorescent emitter, Pt2O2-p2m, was examined as a single emissive emitter for the development of a stable and efficient single-doped WOLED. A bilayer structure was employed to balance the charges carriers within the emissive layer resulting in low efficiency roll-off at high brightness, realizing a peak EQE of 21.5% and EQEs of 20% at 1000 cd m-2 and 15.3% at 7592 cd m-2. A novel phosphorescent/fluorescent, or hybrid, WOLED device architecture was also proposed. To gather a thorough understanding of blue fluorescent OLEDs prior to its use in a WOLED, a study was conducted to investigate the impact of the material selection on the device performance. The use of an anthracene type host demonstrated an improvement to the operational stability of the blue OLED by reducing the occurrence of degradation events. Additionally, various dopant concentrations and blocking materials revealed vastly different efficiency and lifetime results. Finally, a Pd (II) complex, Pd3O8-Py5, with efficient amber-colored aggregate emission was employed to produce a WOLED. Various host materials were investigated to achieve balanced white emission and the addition of an interlayer composed of a high triplet energy material was used to reduce quenching effects. Through this strategy, a color stable WOLED device with a peak EQE of 45% and an estimated LT95 over 50,000 hours at 1000 cd m-2 was realized. The comprehensive performance of the proposed device architecture competes with WOLED devices that are commercially available and reported within the literature domain, providing a strong foundation to further advance the development of highly efficient and stable single-stack WOLEDs.
ContributorsAmeri, Lydia (Author) / Li, Jian (Thesis advisor) / Adams, James (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2022
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
Description
Sulfate deficiency is seen in children with autism through increased urinary excretion of sulfate and low plasma sulfate levels. Potential factors impacting reduced sulfation include phenosulfotransferase activity, sulfate availability, and the presence of the gut toxin p-cresol. Epsom salt baths, vitamin supplementation, and fecal microbiota transplant therapy are all potential treatments with promising results. Sulfate levels have potential for use as a diagnostic biomarker, allowing for earlier diagnosis and intervention.
ContributorsErickson, Payton (Author) / Adams, James (Thesis director) / Krajmalnik-Brown, Rosa (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2023-05
Description
The Healthy Pregnancy Summit is a collection of videos from a variety of specialists detailing how to have a healthy pregnancy and healthy child, based on the latest scientific and medical information. This project summarizes each presentation, and compares to the Healthy Child Guide, a document supplementary to the summit. Finally, this project analyzes the overall usefulness of the summit and each presentation, and suggests areas for improvement.
ContributorsKragenbring, Kylee (Author) / Adams, James (Thesis director) / Matthews, Julie (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2023-05
Description
Organic materials have emerged as an attractive component of electronics over the past few decades, particularly in the development of efficient and stable organic light-emitting diodes (OLEDs) and organic neuromorphic devices. The electrical, chemical, physical, and optical studies of organic materials and their corresponding devices have been conducted for efficient and stable electronics. The development of efficient and stable deep blue OLED devices remains a challenge that has obstructed the progress of large-scale OLED commercialization. One approach was taken to achieve a deep blue emitter through a color tuning strategy. A new complex, PtNONS56-dtb, was designed and synthesized by controlling the energy gap between T1 and T2 energy states to achieve narrowed and blueshifted emission spectra. This emitter material showed an emission spectrum at 460 nm with a FWHM of 59 nm at room temperature in PMMA, and the PtNONS56-dtb-based device exhibited a peak EQE of 8.5% with CIE coordinates of (0.14, 0.27).
A newly developed host and electron blocking materials were demonstrated to achieve efficient and stable OLED devices. The indolocarbazole-based materials were designed to have good hole mobility and high triplet energy. BCN34 as an electron blocking material achieved the estimated LT80 of 12509 h at 1000 cd m-2 with a peak EQE of 30.3% in devices employing Pd3O3 emitter. Additionally, a device with bi-layer emissive layer structure, using BCN34 and CBP as host materials doped with PtN3N emitter, achieved a peak EQE of 16.5% with the LT97 of 351 h at 1000 cd m-2. A new neuromorphic device using Ru(bpy)3(PF6)2 as an active layer was designed to emulate the short-term characteristics of a biological synapse. This memristive device showed a similar operational mechanism with biological synapse through the movement of ions and electronic charges. Furthermore, the performance of the device showed tunability by adding salt. Ultimately, the device with 2% LiClO4 salt shows similar timescales to short-term plasticity characteristics of biological synapses.
ContributorsShin, Samuel (Author) / Li, Jian (Thesis advisor) / Adams, James (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2021