Matching Items (281)
Filtering by
- Status: Published
Description
As world energy demands increase, research into more efficient energy production methods has become imperative. Heterogeneous catalysis and nanoscience are used to promote chemical transformations important for energy production. These concepts are important in solid oxide fuel cells (SOFCs) which have attracted attention because of their potential to provide an efficient and environmentally favorable power generation system. The SOFC is also fuel-flexible with the ability to run directly on many fuels other than hydrogen. Internal fuel reforming directly in the anode of the SOFC would greatly reduce the cost and complexity of the device. Methane is the simplest hydrocarbon and a main component in natural gas, making it useful when testing catalysts on the laboratory scale. Nickel (Ni) and gadolinium (Gd) doped ceria (CeO2) catalysts for potential use in the SOFC anode were synthesized with a spray drying method and tested for catalytic performance using partial oxidation of methane and steam reforming. The relationships between catalytic performance and structure were then investigated using X-ray diffraction, transmission electron microscopy, and environmental transmission electron microscopy. The possibility of solid solutions, segregated phases, and surface layers of Ni were explored. Results for a 10 at.% Ni in CeO2 catalyst reveal a poor catalytic behavior while a 20 at.% Ni in CeO2 catalyst is shown to have superior activity. The inclusion of both 10 at.% Gd and 10 at.% Ni in CeO2 enhances the catalytic performance. Analysis of the presence of Ni in all 3 samples reveals Ni heterogeneity and little evidence for extensive solid solution doping. Ni is found in small domains throughout CeO2 particles. In the 20 at.% Ni sample a segregated, catalytically active NiO phase is observed. Overall, it is found that significant interaction between Ni and CeO2 occurs that could affect the synthesis and functionality of the SOFC anode.
ContributorsCavendish, Rio (Author) / Crozier, Peter (Thesis advisor) / Adams, James (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Cancer claims hundreds of thousands of lives every year in US alone. Finding ways for early detection of cancer onset is crucial for better management and treatment of cancer. Thus, biomarkers especially protein biomarkers, being the functional units which reflect dynamic physiological changes, need to be discovered. Though important, there are only a few approved protein cancer biomarkers till date. To accelerate this process, fast, comprehensive and affordable assays are required which can be applied to large population studies. For this, these assays should be able to comprehensively characterize and explore the molecular diversity of nominally "single" proteins across populations. This information is usually unavailable with commonly used immunoassays such as ELISA (enzyme linked immunosorbent assay) which either ignore protein microheterogeneity, or are confounded by it. To this end, mass spectrometric immuno assays (MSIA) for three different human plasma proteins have been developed. These proteins viz. IGF-1, hemopexin and tetranectin have been found in reported literature to show correlations with many diseases along with several carcinomas. Developed assays were used to extract entire proteins from plasma samples and subsequently analyzed on mass spectrometric platforms. Matrix assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) mass spectrometric techniques where used due to their availability and suitability for the analysis. This resulted in visibility of different structural forms of these proteins showing their structural micro-heterogeneity which is invisible to commonly used immunoassays. These assays are fast, comprehensive and can be applied in large sample studies to analyze proteins for biomarker discovery.
ContributorsRai, Samita (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Borges, Chad (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
There is a growing interest for improved high-accuracy camera calibration methods due to the increasing demand for 3D visual media in commercial markets. Camera calibration is used widely in the fields of computer vision, robotics and 3D reconstruction. Camera calibration is the first step for extracting 3D data from a 2D image. It plays a crucial role in computer vision and 3D reconstruction due to the fact that the accuracy of the reconstruction and 3D coordinate determination relies on the accuracy of the camera calibration to a great extent. This thesis presents a novel camera calibration method using a circular calibration pattern. The disadvantages and issues with existing state-of-the-art methods are discussed and are overcome in this work. The implemented system consists of techniques of local adaptive segmentation, ellipse fitting, projection and optimization. Simulation results are presented to illustrate the performance of the proposed scheme. These results show that the proposed method reduces the error as compared to the state-of-the-art for high-resolution images, and that the proposed scheme is more robust to blur in the imaged calibration pattern.
ContributorsPrakash, Charan Dudda (Author) / Karam, Lina J (Thesis advisor) / Frakes, David (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2012
Description
Single cell analysis has become increasingly important in understanding disease onset, progression, treatment and prognosis, especially when applied to cancer where cellular responses are highly heterogeneous. Through the advent of single cell computerized tomography (Cell-CT), researchers and clinicians now have the ability to obtain high resolution three-dimensional (3D) reconstructions of single cells. Yet to date, no live-cell compatible version of the technology exists. In this thesis, a microfluidic chip with the ability to rotate live single cells in hydrodynamic microvortices about an axis parallel to the optical focal plane has been demonstrated. The chip utilizes a novel 3D microchamber design arranged beneath a main channel creating flow detachment into the chamber, producing recirculating flow conditions. Single cells are flowed through the main channel, held in the center of the microvortex by an optical trap, and rotated by the forces induced by the recirculating fluid flow. Computational fluid dynamics (CFD) was employed to optimize the geometry of the microchamber. Two methods for the fabrication of the 3D microchamber were devised: anisotropic etching of silicon and backside diffuser photolithography (BDPL). First, the optimization of the silicon etching conditions was demonstrated through design of experiment (DOE). In addition, a non-conventional method of soft-lithography was demonstrated which incorporates the use of two positive molds, one of the main channel and the other of the microchambers, compressed together during replication to produce a single ultra-thin (<200 µm) negative used for device assembly. Second, methods for using thick negative photoresists such as SU-8 with BDPL have been developed which include a new simple and effective method for promoting the adhesion of SU-8 to glass. An assembly method that bonds two individual ultra-thin (<100 µm) replications of the channel and the microfeatures has also been demonstrated. Finally, a pressure driven pumping system with nanoliter per minute flow rate regulation, sub-second response times, and < 3% flow variability has been designed and characterized. The fabrication and assembly of this device is inexpensive and utilizes simple variants of conventional microfluidic fabrication techniques, making it easily accessible to the single cell analysis community.
ContributorsMyers, Jakrey R (Author) / Meldrum, Deirdre (Thesis advisor) / Johnson, Roger (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Diabetic retinopathy (DR) is a common cause of blindness occurring due to prolonged presence of diabetes. The risk of developing DR or having the disease progress is increasing over time. Despite advances in diabetes care over the years, DR remains a vision-threatening complication and one of the leading causes of blindness among American adults. Recent studies have shown that diagnosis based on digital retinal imaging has potential benefits over traditional face-to-face evaluation. Yet there is a dearth of computer-based systems that can match the level of performance achieved by ophthalmologists. This thesis takes a fresh perspective in developing a computer-based system aimed at improving diagnosis of DR images. These images are categorized into three classes according to their severity level. The proposed approach explores effective methods to classify new images and retrieve clinically-relevant images from a database with prior diagnosis information associated with them. Retrieval provides a novel way to utilize the vast knowledge in the archives of previously-diagnosed DR images and thereby improve a clinician's performance while classification can safely reduce the burden on DR screening programs and possibly achieve higher detection accuracy than human experts. To solve the three-class retrieval and classification problem, the approach uses a multi-class multiple-instance medical image retrieval framework that makes use of spectrally tuned color correlogram and steerable Gaussian filter response features. The results show better retrieval and classification performances than prior-art methods and are also observed to be of clinical and visual relevance.
ContributorsChandakkar, Parag Shridhar (Author) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Recent advances in camera architectures and associated mathematical representations now enable compressive acquisition of images and videos at low data-rates. While most computer vision applications of today are composed of conventional cameras, which collect a large amount redundant data and power hungry embedded systems, which compress the collected data for further processing, compressive cameras offer the advantage of direct acquisition of data in compressed domain and hence readily promise to find applicability in computer vision, particularly in environments hampered by limited communication bandwidths. However, despite the significant progress in theory and methods of compressive sensing, little headway has been made in developing systems for such applications by exploiting the merits of compressive sensing. In such a setting, we consider the problem of activity recognition, which is an important inference problem in many security and surveillance applications. Since all successful activity recognition systems involve detection of human, followed by recognition, a potential fully functioning system motivated by compressive camera would involve the tracking of human, which requires the reconstruction of atleast the initial few frames to detect the human. Once the human is tracked, the recognition part of the system requires only the features to be extracted from the tracked sequences, which can be the reconstructed images or the compressed measurements of such sequences. However, it is desirable in resource constrained environments that these features be extracted from the compressive measurements without reconstruction. Motivated by this, in this thesis, we propose a framework for understanding activities as a non-linear dynamical system, and propose a robust, generalizable feature that can be extracted directly from the compressed measurements without reconstructing the original video frames. The proposed feature is termed recurrence texture and is motivated from recurrence analysis of non-linear dynamical systems. We show that it is possible to obtain discriminative features directly from the compressed stream and show its utility in recognition of activities at very low data rates.
ContributorsKulkarni, Kuldeep Sharad (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
In this study, the specific goal was to evaluate the effectiveness of utilizing a novel virtual reality software package with a haptic device to practice spine surgery. This spine surgery simulator was commissioned by Barrow Neurological Institute (BNI) and is as yet untested. To test the simulator, an experiment was run in which resident neurosurgeons at Barrow Neurological Institute were asked to perform two “virtual surgeries” with the spine surgical simulator, provide observations on the simulator, and then complete a questionnaire evaluating different aspects of the simulator. The mean questionnaire score across all the neurosurgical residents was found to be 65.5 % ± 9.4 % of the maximum score which suggests that certain aspects of the virtual spine surgical simulator were deemed to be effective by the resident neurosurgeons but that improvements need to be made for the simulator to be fully ready as a teaching and planning tool. As of right now, the simulator is more suited as a training tool instead of a planning tool. Improvements that should be implemented include changing the hardware placement of the haptic device and the computer, minimizing aberrant tactile feedback, and adding anatomical and planning detail to the software to provide a more accurate reflection of spine surgery. It was also suggested that future experiments that evaluate an improved simulator should ensure that participants are trained adequately and have enough time to complete surgical operations to get a fair assessment of the tool.
ContributorsIyer, Sudarshan Rajan (Author) / Frakes, David (Thesis director) / Crawford, Neil (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description
A specific type of Congenital Heart Defect (CHD) known as Coarctation (narrowing) of the Aorta (CoA) prevails in 10% of all CHD patients resulting in life-threatening conditions. Treatments involve limited medical therapy (i.e PGE1 therapy), but in majority of CoA cases, planned surgical treatments are very common. The surgical approach is dictated by the severity of the coarctation, by which the method of treatments is divided between minimally invasive and extensive invasive procedures. Modern diagnostic procedures allude to many disadvantages making it difficult for clinical practices to properly deliver an optimal form of care. Computational Fluid Dynamics (CFD) technique addresses these issues by providing new forms of diagnostic measures that is non-invasive, inexpensive, and more accurate compared to other evaluative devices. To explore further using the CFD based alternative diagnostic measure, this project aims to validate CFD techniques through in vitro studies that capture the fluid flow in anatomically accurate aortic structures. These studies combine particle image velocimetry and catheterization experimental techniques in order to provide a significant knowledge towards validation of fluid flow simulations.
ContributorsPathangey, Girish (Co-author) / Matheny, Chris (Co-author) / Frakes, David (Thesis director) / Pophal, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description
The transition to lead-free solder in the electronics industry has benefitted the environment in many ways. However, with new materials systems comes new materials issues. During the processing of copper pads, a protective surface treatment is needed to prevent the copper from oxidizing. Characterizing the copper oxidation underneath the surface treatment is challenging but necessary for product reliability and failure analysis. Currently, FIB-SEM, which is time-consuming and expensive, is what is used to understand and analyze the surface treatment-copper oxide(s)-copper system. This project's goals were to determine a characterization methodology that cuts both characterization time and cost in half for characterizing copper oxidation beneath a surface treatment and to determine which protective surface treatment is the best as defined by multiple criterion such as cost, sustainability, and reliability. Two protective surface treatments, organic solderability preservative (OSP) and chromium zincate, were investigated, and multiple characterization techniques were researched. Six techniques were tested, and three were deemed promising. Through our studies, it was determined that the best surface treatment was organic solderability preservative (OSP) and the ideal characterization methodology would be using FIB-SEM to calibrate a QCM model, along with using SERA to confirm the QCM model results. The methodology we propose would result in a 91% reduction in characterization cost and a 92% reduction in characterization time. Future work includes further calibration of the QCM model using more FIB/SEM data points and eventually creating a model for oxide layer thickness as a function of exposure time and processing temperature using QCM as the primary data source. In doing my Capstone project for Intel, a large electronics manufacturing company, I feel it is important to remember the effects of our tools and industry on the environment and to consider the product life cycle in terms other than monetary gain and raw material recycling. To this end I will be discussing how lead is and was used in manufacturing, how it is disposed of, and how this effects the environment including plant, animal, and insect life, as well as ground water contamination. Since the ban was enacted several years ago, I will compare how lead-free alternatives currently in use compare in environmental impact and possibly raise the question of whether we have simply traded one evil for another.
ContributorsBranch Kelly, Marion Zoe (Author) / Adams, James (Thesis director) / Krause, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Materials Science and Engineering Program (Contributor)
Created2015-05
Description
Bacteria play a vital role in the world ecosystem, more importantly human health and disease. The capability to differentiate and identify these microorganisms serves as an important research objective. In past years, separations-based approaches have served as a way to observe and identify bacteria based on their characteristics. Gradient insulator dielectrophoresis (g-iDEP) provides benefits in identifying serotypes of a single species with precise separation. Separation of Staphylococcus epidermidis in a single g-iDEP microchannel is conducted exploiting their electrophoretic and electrokinetic properties. The cells were captured and concentrated at gates with interacting forces within the microchannel to clearly distinguish between the two strains. These results provide support for g-iDEP serving as a separating method and, furthermore, future clinical applications.
ContributorsDavis, Paige Elizabeth (Author) / Hayes, Mark (Thesis director) / Borges, Chad (Committee member) / Jones, Paul (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor)
Created2015-05