Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 10 of 89
Description
Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal in both men and women. Developing new drugs for the treatment of cancer is both a slow and expensive process. It is estimated that it takes an average of 15 years and an expense of $800 million to bring a single new drug to the market. However, it is also estimated that nearly 40% of that cost could be avoided by finding alternative uses for drugs that have already been approved by the Food and Drug Administration (FDA). The research presented in this document describes the testing, identification, and mechanistic evaluation of novel methods for treating many human carcinomas using drugs previously approved by the FDA. A tissue culture plate-based screening of FDA approved drugs will identify compounds that can be used in combination with the protein TRAIL to induce apoptosis selectively in cancer cells. Identified leads will next be optimized using high-throughput microfluidic devices to determine the most effective treatment conditions. Finally, a rigorous mechanistic analysis will be conducted to understand how the FDA-approved drug mitoxantrone, sensitizes cancer cells to TRAIL-mediated apoptosis.
ContributorsTaylor, David (Author) / Rege, Kaushal (Thesis advisor) / Jayaraman, Arul (Committee member) / Nielsen, David (Committee member) / Kodibagkar, Vikram (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2013
Description
Although high performance, light-weight composites are increasingly being used in applications ranging from aircraft, rotorcraft, weapon systems and ground vehicles, the assurance of structural reliability remains a critical issue. In composites, damage is absorbed through various fracture processes, including fiber failure, matrix cracking and delamination. An important element in achieving reliable composite systems is a strong capability of assessing and inspecting physical damage of critical structural components. Installation of a robust Structural Health Monitoring (SHM) system would be very valuable in detecting the onset of composite failure. A number of major issues still require serious attention in connection with the research and development aspects of sensor-integrated reliable SHM systems for composite structures. In particular, the sensitivity of currently available sensor systems does not allow detection of micro level damage; this limits the capability of data driven SHM systems. As a fundamental layer in SHM, modeling can provide in-depth information on material and structural behavior for sensing and detection, as well as data for learning algorithms. This dissertation focusses on the development of a multiscale analysis framework, which is used to detect various forms of damage in complex composite structures. A generalized method of cells based micromechanics analysis, as implemented in NASA's MAC/GMC code, is used for the micro-level analysis. First, a baseline study of MAC/GMC is performed to determine the governing failure theories that best capture the damage progression. The deficiencies associated with various layups and loading conditions are addressed. In most micromechanics analysis, a representative unit cell (RUC) with a common fiber packing arrangement is used. The effect of variation in this arrangement within the RUC has been studied and results indicate this variation influences the macro-scale effective material properties and failure stresses. The developed model has been used to simulate impact damage in a composite beam and an airfoil structure. The model data was verified through active interrogation using piezoelectric sensors. The multiscale model was further extended to develop a coupled damage and wave attenuation model, which was used to study different damage states such as fiber-matrix debonding in composite structures with surface bonded piezoelectric sensors.
ContributorsMoncada, Albert (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Yekani Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2012
Description
This thesis presents approaches to develop micro seismometers and accelerometers based on molecular electronic transducers (MET) technology using MicroElectroMechanical Systems (MEMS) techniques. MET is a technology applied in seismic instrumentation that proves highly beneficial to planetary seismology. It consists of an electrochemical cell that senses the movement of liquid electrolyte between electrodes by converting it to the output current. MET seismometers have advantages of high sensitivity, low noise floor, small size, absence of fragile mechanical moving parts and independence on the direction of sensitivity axis. By using MEMS techniques, a micro MET seismometer is developed with inter-electrode spacing close to 1μm, which improves the sensitivity of fabricated device to above 3000 V/(m/s^2) under operating bias of 600 mV and input acceleration of 400 μG (G=9.81m/s^2) at 0.32 Hz. The lowered hydrodynamic resistance by increasing the number of channels improves the self-noise to -127 dB equivalent to 44 nG/√Hz at 1 Hz. An alternative approach to build the sensing element of MEMS MET seismometer using SOI process is also presented in this thesis. The significantly increased number of channels is expected to improve the noise performance. Inspired by the advantages of combining MET and MEMS technologies on the development of seismometer, a low frequency accelerometer utilizing MET technology with post-CMOS-compatible fabrication processes is developed. In the fabricated accelerometer, the complicated fabrication of mass-spring system in solid-state MEMS accelerometer is replaced with a much simpler post-CMOS-compatible process containing only deposition of a four-electrode MET structure on a planar substrate, and a liquid inertia mass of an electrolyte droplet encapsulated by oil film. The fabrication process does not involve focused ion beam milling which is used in the micro MET seismometer fabrication, thus the cost is lowered. Furthermore, the planar structure and the novel idea of using an oil film as the sealing diaphragm eliminate the complicated three-dimensional packaging of the seismometer. The fabricated device achieves 10.8 V/G sensitivity at 20 Hz with nearly flat response over the frequency range from 1 Hz to 50 Hz, and a low noise floor of 75 μG/√Hz at 20 Hz.
ContributorsHuang, Hai (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014
Description
Alzheimer's disease (AD) is the most common type of dementia, affecting one in nine people age 65 and older. One of the most important neuropathological characteristics of Alzheimer's disease is the aggregation and deposition of the protein beta-amyloid. Beta-amyloid is produced by proteolytic processing of the Amyloid Precursor Protein (APP). Production of beta-amyloid from APP is increased when cells are subject to stress since both APP and beta-secretase are upregulated by stress. An increased beta-amyloid level promotes aggregation of beta-amyloid into toxic species which cause an increase in reactive oxygen species (ROS) and a decrease in cell viability. Therefore reducing beta-amyloid generation is a promising method to control cell damage following stress. The goal of this thesis was to test the effect of inhibiting beta-amyloid production inside stressed AD cell model. Hydrogen peroxide was used as stressing agent. Two treatments were used to inhibit beta-amyloid production, including iBSec1, an scFv designed to block beta-secretase site of APP, and DIA10D, a bispecific tandem scFv engineered to cleave alpha-secretase site of APP and block beta-secretase site of APP. iBSec1 treatment was added extracellularly while DIA10D was stably expressed inside cell using PSECTAG vector. Increase in reactive oxygen species and decrease in cell viability were observed after addition of hydrogen peroxide to AD cell model. The increase in stress induced toxicity caused by addition of hydrogen peroxide was dramatically decreased by simultaneously treating the cells with iBSec1 or DIA10D to block the increase in beta-amyloid levels resulting from the upregulation of APP and beta-secretase.
ContributorsSuryadi, Vicky (Author) / Sierks, Michael (Thesis advisor) / Nielsen, David (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2014
Description
This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
ContributorsHasan, Zeaid (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
Membrane proteins are a vital part of cellular structure. They are directly involved in many important cellular functions, such as uptake, signaling, respiration, and photosynthesis, among others. Despite their importance, however, less than 500 unique membrane protein structures have been determined to date. This is due to several difficulties with macromolecular crystallography, primarily the difficulty of growing large, well-ordered protein crystals. Since the first proof of concept for femtosecond nanocrystallography showing that diffraction patterns can be collected on extremely small crystals, thus negating the need to grow larger crystals, there have been many exciting advancements in the field. The technique has been proven to show high spatial resolution, thus making it a viable method for structural biology. However, due to the ultrafast nature of the technique, which allows for a lack of radiation damage in imaging, even more interesting experiments are possible, and the first temporal and spatial images of an undamaged structure could be acquired. This concept was denoted as time-resolved femtosecond nanocrystallography.
This dissertation presents on the first time-resolved data set of Photosystem II where structural changes can actually be seen without radiation damage. In order to accomplish this, new crystallization techniques had to be developed so that enough crystals could be made for the liquid jet to deliver a fully hydrated stream of crystals to the high-powered X-ray source. These changes are still in the preliminary stages due to the slightly lower resolution data obtained, but they are still a promising show of the power of this new technique. With further optimization of crystal growth methods and quality, injection technique, and continued development of data analysis software, it is only a matter of time before the ability to make movies of molecules in motion from X-ray diffraction snapshots in time exists. The work presented here is the first step in that process.
This dissertation presents on the first time-resolved data set of Photosystem II where structural changes can actually be seen without radiation damage. In order to accomplish this, new crystallization techniques had to be developed so that enough crystals could be made for the liquid jet to deliver a fully hydrated stream of crystals to the high-powered X-ray source. These changes are still in the preliminary stages due to the slightly lower resolution data obtained, but they are still a promising show of the power of this new technique. With further optimization of crystal growth methods and quality, injection technique, and continued development of data analysis software, it is only a matter of time before the ability to make movies of molecules in motion from X-ray diffraction snapshots in time exists. The work presented here is the first step in that process.
ContributorsKupitz, Christopher (Author) / Fromme, Petra (Thesis advisor) / Spence, John C. (Thesis advisor) / Redding, Kevin (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2014
Description
The utilization of solar energy requires an efficient means of its storage as fuel. In bio-inspired artificial photosynthesis, light energy can be used to drive water oxidation, but catalysts that produce molecular oxygen from water are required. This dissertation demonstrates a novel complex utilizing earth-abundant Ni in combination with glycine as an efficient catalyst with a modest overpotential of 0.475 ± 0.005 V for a current density of 1 mA/cm2 at pH 11. The production of molecular oxygen at a high potential was verified by measurement of the change in oxygen concentration, yielding a Faradaic efficiency of 60 ± 5%. This Ni species can achieve a current density of 4 mA/cm2 that persists for at least 10 hours. Based upon the observed pH dependence of the current amplitude and oxidation/reduction peaks, the catalysis is an electron-proton coupled process. In addition, to investigate the binding of divalent metals to proteins, four peptides were designed and synthesized with carboxylate and histidine ligands. The binding of the metals was characterized by monitoring the metal-induced changes in circular dichroism spectra. Cyclic voltammetry demonstrated that bound copper underwent a Cu(I)/Cu(II) oxidation/reduction change at a potential of approximately 0.32 V in a quasi-reversible process. The relative binding affinity of Mn(II), Fe(II), Co(II), Ni(II) and Cu(II) to the peptides is correlated with the stability constants of the Irving-Williams series for divalent metal ions. A potential application of these complexes of transition metals with amino acids or peptides is in the development of artificial photosynthetic cells.
ContributorsWang, Dong (Author) / Allen, James P. (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Redding, Kevin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Cyanovirin-N (CVN) is a cyanobacterial lectin with potent anti-HIV activity, mediated by binding to the N-linked oligosaccharide moiety of the envelope protein gp120. CVN offers a scaffold to develop multivalent carbohydrate-binding proteins with tunable specificities and affinities. I present here biophysical calculations completed on a monomeric-stabilized mutant of cyanovirin-N, P51G-m4-CVN, in which domain A binding activity is abolished by four mutations; with comparisons made to CVNmutDB, in which domain B binding activity is abolished. Using Monte Carlo calculations and docking simulations, mutations in CVNmutDB were considered singularly, and the mutations E41A/G and T57A were found to impact the affinity towards dimannose the greatest. 15N-labeled proteins were titrated with Manα(1-2)Manα, while following chemical shift perturbations in NMR spectra. The mutants, E41A/G and T57A, had a larger Kd than P51G-m4-CVN, matching the trends predicted by the calculations. We also observed that the N42A mutation affects the local fold of the binding pocket, thus removing all binding to dimannose. Characterization of the mutant N53S showed similar binding affinity to P51G-m4-CVN. Using biophysical calculations allows us to study future iterations of models to explore affinities and specificities. In order to further elucidate the role of multivalency, I report here a designed covalent dimer of CVN, Nested cyanovirin-N (Nested CVN), which has four binding sites. Nested CVN was found to have comparable binding affinity to gp120 and antiviral activity to wt CVN. These results demonstrate the ability to create a multivalent, covalent dimer that has comparable results to that of wt CVN.
WW domains are small modules consisting of 32-40 amino acids that recognize proline-rich peptides and are found in many signaling pathways. We use WW domain sequences to explore protein folding by simulations using Zipping and Assembly Method. We identified five crucial contacts that enabled us to predict the folding of WW domain sequences based on those contacts. We then designed a folded WW domain peptide from an unfolded WW domain sequence by introducing native contacts at those critical positions.
WW domains are small modules consisting of 32-40 amino acids that recognize proline-rich peptides and are found in many signaling pathways. We use WW domain sequences to explore protein folding by simulations using Zipping and Assembly Method. We identified five crucial contacts that enabled us to predict the folding of WW domain sequences based on those contacts. We then designed a folded WW domain peptide from an unfolded WW domain sequence by introducing native contacts at those critical positions.
ContributorsWoodrum, Brian William (Author) / Ghirlanda, Giovanna (Thesis advisor) / Redding, Kevin (Committee member) / Wang, Xu (Committee member) / Arizona State University (Publisher)
Created2014
Description
Damage detection in heterogeneous material systems is a complex problem and requires an in-depth understanding of the material characteristics and response under varying load and environmental conditions. A significant amount of research has been conducted in this field to enhance the fidelity of damage assessment methodologies, using a wide range of sensors and detection techniques, for both metallic materials and composites. However, detecting damage at the microscale is not possible with commercially available sensors. A probable way to approach this problem is through accurate and efficient multiscale modeling techniques, which are capable of tracking damage initiation at the microscale and propagation across the length scales. The output from these models will provide an improved understanding of damage initiation; the knowledge can be used in conjunction with information from physical sensors to improve the size of detectable damage. In this research, effort has been dedicated to develop multiscale modeling approaches and associated damage criteria for the estimation of damage evolution across the relevant length scales. Important issues such as length and time scales, anisotropy and variability in material properties at the microscale, and response under mechanical and thermal loading are addressed. Two different material systems have been studied: metallic material and a novel stress-sensitive epoxy polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
ContributorsZhang, Jinjun (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
A vast amount of energy emanates from the sun, and at the distance of Earth, approximately 172,500 TW reaches the atmosphere. Of that, 80,600 TW reaches the surface with 15,600 TW falling on land. Photosynthesis converts 156 TW in the form of biomass, which represents all food/fuel for the biosphere with about 20 TW of the total product used by humans. Additionally, our society uses approximately 20 more TW of energy from ancient photosynthetic products i.e. fossil fuels. In order to mitigate climate problems, the carbon dioxide must be removed from the human energy usage by replacement or recycling as an energy carrier. Proposals have been made to process biomass into biofuels; this work demonstrates that current efficiencies of natural photosynthesis are inadequate for this purpose, the effects of fossil fuel replacement with biofuels is ecologically irresponsible, and new technologies are required to operate at sufficient efficiencies to utilize artificial solar-to-fuels systems. Herein a hybrid bioderived self-assembling hydrogen-evolving nanoparticle consisting of photosystem I (PSI) and platinum nanoclusters is demonstrated to operate with an overall efficiency of 6%, which exceeds that of land plants by more than an order of magnitude. The system was limited by the rate of electron donation to photooxidized PSI. Further work investigated the interactions of natural donor acceptor pairs of cytochrome c6 and PSI for the thermophilic cyanobacteria Thermosynechococcus elogantus BP1 and the red alga Galderia sulphuraria. The cyanobacterial system is typified by collisional control while the algal system demonstrates a population of prebound PSI-cytochrome c6 complexes with faster electron transfer rates. Combining the stability of cyanobacterial PSI and kinetics of the algal PSI:cytochrome would result in more efficient solar-to-fuel conversion. A second priority is the replacement of platinum with chemically abundant catalysts. In this work, protein scaffolds are employed using host-guest strategies to increase the stability of proton reduction catalysts and enhance the turnover number without the oxygen sensitivity of hydrogenases. Finally, design of unnatural electron transfer proteins are explored and may introduce a bioorthogonal method of introducing alternative electron transfer pathways in vitro or in vivo in the case of engineered photosynthetic organisms.
ContributorsVaughn, Michael David (Author) / Moore, Thomas (Thesis advisor) / Fromme, Petra (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Redding, Kevin (Committee member) / Arizona State University (Publisher)
Created2014