Matching Items (162)
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Description

A novel concept for integration of flame-assisted fuel cells (FFC) with a gas turbine is analyzed in this paper. Six different fuels (CH4, C3H8, JP-4, JP-5, JP-10(L), and H2) are investigated for the analytical model of the FFC integrated gas turbine hybrid system. As equivalence ratio increases, the efficiency of

A novel concept for integration of flame-assisted fuel cells (FFC) with a gas turbine is analyzed in this paper. Six different fuels (CH4, C3H8, JP-4, JP-5, JP-10(L), and H2) are investigated for the analytical model of the FFC integrated gas turbine hybrid system. As equivalence ratio increases, the efficiency of the hybrid system increases initially then decreases because the decreasing flow rate of air begins to outweigh the increasing hydrogen concentration. This occurs at an equivalence ratio of 2 for CH4. The thermodynamic cycle is analyzed using a temperature entropy diagram and a pressure volume diagram. These thermodynamic diagrams show as equivalence ratio increases, the power generated by the turbine in the hybrid setup decreases. Thermodynamic analysis was performed to verify that energy is conserved and the total chemical energy going into the system was equal to the heat rejected by the system plus the power generated by the system. Of the six fuels, the hybrid system performs best with H2 as the fuel. The electrical efficiency with H2 is predicted to be 27%, CH4 is 24%, C3H8 is 22%, JP-4 is 21%, JP-5 is 20%, and JP-10(L) is 20%. When H2 fuel is used, the overall integrated system is predicted to be 24.5% more efficient than the standard gas turbine system. The integrated system is predicted to be 23.0% more efficient with CH4, 21.9% more efficient with C3H8, 22.7% more efficient with JP-4, 21.3% more efficient with JP-5, and 20.8% more efficient with JP-10(L). The sensitivity of the model is investigated using various fuel utilizations. When CH4 fuel is used, the integrated system is predicted to be 22.7% more efficient with a fuel utilization efficiency of 90% compared to that of 30%.

ContributorsRupiper, Lauren Nicole (Author) / Milcarek, Ryan (Thesis director) / Wang, Liping (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School for Engineering of Matter,Transport & Enrgy (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Microfluidic devices represent a growing technology in the world of analytical chemistry. Serial femtosecond crystallography (SFX) utilizes microfluidic devices to generate droplets of an aqueous buffer containing protein crystals, which are then fired out as a jet in the beam of an X-ray free electron laser (XFEL). A crucial part

Microfluidic devices represent a growing technology in the world of analytical chemistry. Serial femtosecond crystallography (SFX) utilizes microfluidic devices to generate droplets of an aqueous buffer containing protein crystals, which are then fired out as a jet in the beam of an X-ray free electron laser (XFEL). A crucial part of the device is its method of droplet detection. This project presents a design for a capacitive sensor that uses a unique electrode configuration to detect the difference in capacitance between the aqueous and oil phases. This design was developed using MATLAB and COMSOL Multiphysics simulations and printed using high-resolution 3D printing. Results show that this design can successfully distinguish between the two immiscible liquids, confirming it as a possible detection method in future SFX experiments.

ContributorsCorder, Cameron Dean (Author) / Ros, Alexandra (Thesis director) / Williams, Peter (Committee member) / Hayes, Mark (Committee member) / School of Molecular Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
The repression of reproductive competition and the enforcement of altruism are key components to the success of animal societies. Eusocial insects are defined by having a reproductive division of labor, in which reproduction is relegated to one or few individuals while the rest of the group members maintain the colony

The repression of reproductive competition and the enforcement of altruism are key components to the success of animal societies. Eusocial insects are defined by having a reproductive division of labor, in which reproduction is relegated to one or few individuals while the rest of the group members maintain the colony and help raise offspring. However, workers have retained the ability to reproduce in most insect societies. In the social Hymenoptera, due to haplodiploidy, workers can lay unfertilized male destined eggs without mating. Potential conflict between workers and queens can arise over male production, and policing behaviors performed by nestmate workers and queens are a means of repressing worker reproduction. This work describes the means and results of the regulation of worker reproduction in the ant species Aphaenogaster cockerelli. Through manipulative laboratory studies on mature colonies, the lack of egg policing and the presence of physical policing by both workers and queens of this species are described. Through chemical analysis and artificial chemical treatments, the role of cuticular hydrocarbons as indicators of fertility status and the informational basis of policing in this species is demonstrated. An additional queen-specific chemical signal in the Dufour's gland is discovered to be used to direct nestmate aggression towards reproductive competitors. Finally, the level of actual worker-derived males in field colonies is measured. Together, these studies demonstrate the effectiveness of policing behaviors on the suppression of worker reproduction in a social insect species, and provide an example of how punishment and the threat of punishment is a powerful force in maintaining cooperative societies.
ContributorsSmith, Adrian A. (Author) / Liebig, Juergen (Thesis advisor) / Hoelldobler, Bert (Thesis advisor) / Gadau, Juergen (Committee member) / Johnson, Robert A. (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
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Description
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human

In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Obtaining local electrochemical (EC) information is extremely important for understanding basic surface reactions, and for many applications. Scanning electrochemical microscopy (SECM) can obtain local EC information by scanning a microelectrode across the surface. Although powerful, SECM is slow, the scanning microelectrode may perturb reaction and the measured signal decreases with

Obtaining local electrochemical (EC) information is extremely important for understanding basic surface reactions, and for many applications. Scanning electrochemical microscopy (SECM) can obtain local EC information by scanning a microelectrode across the surface. Although powerful, SECM is slow, the scanning microelectrode may perturb reaction and the measured signal decreases with the size of microelectrode. This thesis demonstrates a new imaging technique based on a principle that is completely different from the conventional EC detection technologies. The technique, referred to as plasmonic-based electrochemical imaging (PECI), images local EC current (both faradaic and non-faradaic) without using a scanning microelectrode. Because PECI response is an optical signal originated from surface plasmon resonance (SPR), PECI is fast and non-invasive and its signal is proportional to incident light intensity, thus does not decrease with the area of interest. A complete theory is developed in this thesis work to describe the relationship between EC current and PECI signal. EC current imaging at various fixed potentials and local cyclic voltammetry methods are developed and demonstrated with real samples. Fast imaging rate (up to 100,000 frames per second) with 0.2×3µm spatial resolution and 0.3 pA detection limit have been achieved. Several PECI applications have been developed to demonstrate the unique strengths of the new imaging technology. For example, trace particles in fingerprint is detected by PECI, a capability that cannot be achieved with the conventional EC technologies. Another example is PECI imaging of EC reaction and interfacial impedance of graphene of different thicknesses. In addition, local square wave voltammetry capability is demonstrated and applied to study local catalytic current of platinum nanoparticle microarray. This thesis also describes a related but different research project that develops a new method to measure surface charge densities of SPR sensor chips, and micro- and nano-particles. A third project of this thesis is to develop a method to expand the conventional SPR detection and imaging technology by including a waveguide mode. This innovation creates a sensitive detection of bulk index of refraction, which overcomes the limitation that the conventional SPR can probe only changes near the sensor surface within ~200 nm.
ContributorsShan, Xiaonan (Author) / Tao, Nongjian (Thesis advisor) / Chae, Junseok (Committee member) / Christen, Jennifer Blain (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2011
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X-ray diffraction is the technique of choice to determine the three-dimensional structures of proteins. In this study it has been applied to solve the structure of the survival motor neuron (SMN) proteins, the Fenna-Mathews-Olson (FMO) from Pelodictyon phaeum (Pld. phaeum) protein, and the synthetic ATP binding protein DX. Spinal muscular

X-ray diffraction is the technique of choice to determine the three-dimensional structures of proteins. In this study it has been applied to solve the structure of the survival motor neuron (SMN) proteins, the Fenna-Mathews-Olson (FMO) from Pelodictyon phaeum (Pld. phaeum) protein, and the synthetic ATP binding protein DX. Spinal muscular atrophy (SMA) is an autosomal recessive genetic disease resulting in muscle atrophy and paralysis via degeneration of motor neurons in the spinal cord. In this work, we used X-ray diffraction technique to solve the structures of the three variant of the of SMN protein, namely SMN 1-4, SMN-WT, and SMN-Δ7. The SMN 1-4, SMN-WT, and SMN-Δ7 crystals were diffracted to 2.7 Å, 5.5 Å and 3.0 Å, respectively. The three-dimensional structures of the three SMN proteins have been solved. The FMO protein from Pld. phaeum is a water soluble protein that is embedded in the cytoplasmic membrane and serves as an energy transfer funnel between the chlorosome and the reaction center. The FMO crystal diffracted to 1.99Å resolution and the three-dimensional structure has been solved. In previous studies, double mutant, DX, protein was purified and crystallized in the presence of ATP (Simmons et al., 2010; Smith et al. 2007). DX is a synthetic ATP binding protein which resulting from a random selection of DNA library. In this study, DX protein was purified and crystallized without the presence of ATP to investigate the conformational change in DX structure. The crystals of DX were diffracted to 2.5 Å and the three-dimensional structure of DX has been solved.
ContributorsSeng, Chenda O (Author) / Allen, James P. (Thesis advisor) / Wachter, Rebekka (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2013
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ABSTRACT 1. Aposematic signals advertise prey distastefulness or metabolic unprofitability to potential predators and have evolved independently in many prey groups over the course of evolutionary history as a means of protection from predation. Most aposematic signals investigated to date exhibit highly chromatic patterning; however, relatives in these toxic groups

ABSTRACT 1. Aposematic signals advertise prey distastefulness or metabolic unprofitability to potential predators and have evolved independently in many prey groups over the course of evolutionary history as a means of protection from predation. Most aposematic signals investigated to date exhibit highly chromatic patterning; however, relatives in these toxic groups with patterns of very low chroma have been largely overlooked. 2. We propose that bright displays with low chroma arose in toxic prey species because they were more effective at deterring predation than were their chromatic counterparts, especially when viewed in relatively low light environments such as forest understories. 3. We analyzed the reflectance and radiance of color patches on the wings of 90 tropical butterfly species that belong to groups with documented toxicity that vary in their habitat preferences to test this prediction: Warning signal chroma and perceived chromaticity are expected to be higher and brightness lower in species that fly in open environments when compared to those that fly in forested environments. 4. Analyses of the reflectance and radiance of warning color patches and predator visual modeling support this prediction. Moreover, phylogenetic tests, which correct for statistical non-independence due to phylogenetic relatedness of test species, also support the hypothesis of an evolutionary correlation between perceived chromaticity of aposematic signals and the flight habits of the butterflies that exhibit these signals.
ContributorsDouglas, Jonathan Marion (Author) / Rutowski, Ronald L (Thesis advisor) / Gadau, Juergen (Committee member) / McGraw, Kevin J. (Committee member) / Arizona State University (Publisher)
Created2013
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Production from a high pressure gas well at a high production-rate encounters the risk of operating near the choking condition for a compressible flow in porous media. The unbounded gas pressure gradient near the point of choking, which is located near the wellbore, generates an effective tensile stress on the

Production from a high pressure gas well at a high production-rate encounters the risk of operating near the choking condition for a compressible flow in porous media. The unbounded gas pressure gradient near the point of choking, which is located near the wellbore, generates an effective tensile stress on the porous rock frame. This tensile stress almost always exceeds the tensile strength of the rock and it causes a tensile failure of the rock, leading to wellbore instability. In a porous rock, not all pores are choked at the same flow rate, and when just one pore is choked, the flow through the entire porous medium should be considered choked as the gas pressure gradient at the point of choking becomes singular. This thesis investigates the choking condition for compressible gas flow in a single microscopic pore. Quasi-one-dimensional analysis and axisymmetric numerical simulations of compressible gas flow in a pore scale varicose tube with a number of bumps are carried out, and the local Mach number and pressure along the tube are computed for the flow near choking condition. The effects of tube length, inlet-to-outlet pressure ratio, the number of bumps and the amplitude of the bumps on the choking condition are obtained. These critical values provide guidance for avoiding the choking condition in practice.
ContributorsYuan, Jing (Author) / Chen, Kangping (Thesis advisor) / Wang, Liping (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay

Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier.
ContributorsBuddi, Sai (Author) / Taylor, Thomas (Thesis advisor) / Cochran, Douglas (Thesis advisor) / Nelson, Randall (Committee member) / Duman, Tolga (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various

Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various working fluids. Theoretical and experimental analyses of a turbine-generator assembly utilizing compressed air, saturated steam and water as the working fluids were performed and are presented in this work. A brief background and explanation of the technology is provided along with potential applications. A theoretical thermodynamic analysis is outlined, resulting in turbine and rotor efficiencies, power outputs and Reynolds numbers calculated for the turbine for various combinations of working fluids and inlet nozzles. The results indicate the turbine is capable of achieving a turbine efficiency of 31.17 ± 3.61% and an estimated rotor efficiency 95 ± 9.32%. These efficiencies are promising considering the numerous losses still present in the current design. Calculation of the Reynolds number provided some capability to determine the flow behavior and how that behavior impacts the performance and efficiency of the Tesla turbine. It was determined that turbulence in the flow is essential to achieving high power outputs and high efficiency. Although the efficiency, after peaking, begins to slightly taper off as the flow becomes increasingly turbulent, the power output maintains a steady linear increase.
ContributorsPeshlakai, Aaron (Author) / Phelan, Patrick (Thesis advisor) / Trimble, Steve (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2012