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- Creators: Crozier, Peter
- Creators: Barrett, The Honors College
Description
There has been much interest in photoelectrochemical conversion of solar energy in recent years due to its potential for low-–cost, sustainable and renewable production of fuels. Despite the huge potential, there are still a number of technical barriers due to the many constraints needed in order to drive photoelectrochemical reactions such as overall water splitting and the identification of efficient and effective semiconductor materials. To this end, the search for novel semiconductors that can act as light absorbers is still needed. The copper hydroxyphosphate mineral libethenite (CHP), which has a chemical formula of Cu2(OH)PO4, has been recently shown to be active for photocatalytic degradation of methylene blue under UV-–irradiation, indicating that photo-excited electrons and holes can effectively be generated and separated in this material. However, CHP has not been well studied and many of its fundamental electrochemical and photoelectrochemical properties are still unknown. In this work, the synthesis of different morphologies of CHP using hydrothermal synthesis and precipitation methods were explored. Additionally, a preliminary investigation of the relevant fundamental characteristics such as the bandgap, flatband potential, band diagram, electrochemical and photoelectrochemical properties for CHP was performed. Better understanding of the properties of this material may lead to the development of improved catalysts and photocatalysts from natural sources.
ContributorsLi, Man (Author) / Chan, Candace K. (Thesis advisor) / O'Connell, Michael (Committee member) / Crozier, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
Novel materials for Li-ion batteries is one of the principle thrust areas for current research in energy storage, more so than most, considering its widespread use in portable electronic gadgets and plug-in electric and hybrid cars. One of the major limiting factors in a Li-ion battery's energy density is the low specific capacities of the active materials in the electrodes. In the search for high-performance anode materials for Li-ion batteries, many alternatives to carbonaceous materials have been studied. Both cubic and amorphous silicon can reversibly alloy with lithium and have a theoretical capacity of 3500 mAh/g, making silicon a potential high density anode material. However, a large volume expansion of 300% occurs due to changes in the structure during lithium insertion, often leading to pulverization of the silicon. To this end, a class of silicon based cage compounds called clathrates are studied for electrochemical reactivity with lithium. Silicon-clathrates consist of silicon covalently bonded in cage structures comprised of face sharing Si20, Si24 and/or Si28 clusters with guest ions occupying the interstitial positions in the polyhedra. Prior to this, silicon clathrates have been studied primarily for their superconducting and thermoelectric properties. In this work, the synthesis and electrochemical characterization of two categories of silicon clathrates - Type-I silicon clathrate with aluminum framework substitution and barium guest ions (Ba8AlxSi46-x) and Type-II silicon clathrate with sodium guest ions (Nax Si136), are explored. The Type-I clathrate, Ba8AlxSi46-x consists of an open framework of aluminium and silicon, with barium (guest) atoms occupying the interstitial positions. X-ray diffraction studies have shown that a crystalline phase of clathrate is obtained from synthesis, which is powdered to a fine particle size to be used as the anode material in a Li-ion battery. Electrochemical measurements of these type of clathrates have shown that capacities comparable to graphite can be obtained for up to 10 cycles and lower capacities can be obtained for up to 20 cycles. Unlike bulk silicon, the clathrate structure does not undergo excessive volume change upon lithium intercalation, and therefore, the crystal structure is morphologically stable over many cycles. X-ray diffraction of the clathrate after cycling showed that crystallinity is intact, indicating that the clathrate does not collapse during reversible intercalation with lithium ions. Electrochemical potential spectroscopy obtained from the cycling data showed that there is an absence of formation of lithium-silicide, which is the product of lithium alloying with diamond cubic silicon. Type II silicon clathrate, NaxSi136, consists of silicon making up the framework structure and sodium (guest) atoms occupying the interstitial spaces. These clathrates showed very high capacities during their first intercalation cycle, in the range of 3,500 mAh/g, but then deteriorated during subsequent cycles. X-ray diffraction after one cycle showed the absence of clathrate phase and the presence of lithium-silicide, indicating the disintegration of clathrate structure. This could explain the silicon-like cycling behavior of Type II clathrates.
ContributorsRaghavan, Rahul (Author) / Chan, Candace K. (Thesis advisor) / Crozier, Peter (Committee member) / Petuskey, William T (Committee member) / Arizona State University (Publisher)
Created2013
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
Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.
ContributorsZou, Jin (Author) / Dai, Lenore L (Thesis advisor) / Chattopadhyay, Aditi (Thesis advisor) / Lind, Mary L (Committee member) / Mu, Bin (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
Description
Advanced composites are being widely used in aerospace applications due to their high stiffness, strength and energy absorption capabilities. However, the assurance of structural reliability is a critical issue because a damage event will compromise the integrity of composite structures and lead to ultimate failure. In this dissertation a novel homogenization based multiscale modeling framework using semi-analytical micromechanics is presented to simulate the response of textile composites. The novelty of this approach lies in the three scale homogenization/localization framework bridging between the constituent (micro), the fiber tow scale (meso), weave scale (macro), and the global response. The multiscale framework, named Multiscale Generalized Method of Cells (MSGMC), continuously bridges between the micro to the global scale as opposed to approaches that are top-down and bottom-up. This framework is fully generalized and capable of modeling several different weave and braids without reformulation. Particular emphasis in this dissertation is placed on modeling the nonlinearity and failure of both polymer matrix and ceramic matrix composites.
ContributorsLiu, Guang (Author) / Chattopadhyay, Aditi (Thesis advisor) / Mignolet, Marc (Committee member) / Jiang, Hanqing (Committee member) / Li, Jian (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
There is an inexorable link between structure and stress, both of which require study in order to truly understand the physics of thin films. To further our knowledge of thin films, the relationship between structure and stress development was examined in three separate systems in vacuum. The first was continued copper thin film growth in ultra-high vacuum after adsorption of a sub-monolayer quantity of oxygen. Results showed an increase in compressive stress generation, and theory was proposed to explain the additional compressive stress within the films. The second system explored was the adsorption of carbon monoxide on the platinum {111} surface in vacuum. The experiments displayed a correlation between known structural developments in the adsorbed carbon monoxide adlayer and the surface stress state of the system. The third system consisted of the growth and annealing stresses of ice thin films at cryogenic temperatures in vacuum. It was shown that the growth stresses are clearly linked to known morphology development from literature, with crystalline ice developing compressive and amorphous ice developing tensile stresses respectively, and that amorphous ice films develop additional tensile stresses upon annealing.
ContributorsKennedy, Jordan (Author) / Friesen, Cody (Thesis advisor) / Sieradzki, Karl (Committee member) / Crozier, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Fuel cells, particularly solid oxide fuel cells (SOFC), are important for the future of greener and more efficient energy sources. Although SOFCs have been in existence for over fifty years, they have not been deployed extensively because they need to be operated at a high temperature (∼1000 °C), are expensive, and have slow response to changes in energy demands. One important need for commercialization of SOFCs is a lowering of their operating temperature, which requires an electrolyte that can operate at lower temperatures. Doped ceria is one such candidate. For this dissertation work I have studied different types of doped ceria to understand the mechanism of oxygen vacancy diffusion through the bulk. Doped ceria is important because they have high ionic conductivities thus making them attractive candidates for the electrolytes of solid oxide fuel cells. In particular, I have studied how the ionic conductivities are improved in these doped materials by studying the oxygen-vacancy formations and migrations. In this dissertation I describe the application of density functional theory (DFT) and Kinetic Lattice Monte Carlo (KLMC) simulations to calculate the vacancy diffusion and ionic conductivities in doped ceria. The dopants used are praseodymium (Pr), gadolinium (Gd), and neodymium (Nd), all belonging to the lanthanide series. The activation energies for vacancy migration between different nearest neighbor (relative to the dopant) positions were calculated using the commercial DFT code VASP (Vienna Ab-initio Simulation Package). These activation energies were then used as inputs to the KLMC code that I co-developed. The KLMC code was run for different temperatures (673 K to 1073 K) and for different dopant concentrations (0 to 40%). These simulations have resulted in the prediction of dopant concentrations for maximum ionic conductivity at a given temperature.
ContributorsAnwar, Shahriar (Author) / Adams, James B (Thesis advisor) / Crozier, Peter (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
This work focuses on simulation of electrical resistivity and optical behaviors of thin films, where an Ag or Au thin layer is embedded in zinc oxide. Enhanced conductivity and transparency were earlier achieved with multilayer structured transparent conducting oxide (TCO) sandwich layer with metal (TCO/metal/TCO). Sputtering pattern of metal layer is simulated to obtain the morphology, covered area fraction, and the percolation strength. The resistivity as a function of the metal layer thickness fits the modeled trend of covered area fraction beyond the percolation threshold. This result not only presents the robustness of the simulation, but also demonstrates the influence of metal morphology in multilayer structure. Effective medium coefficients are defined from the coverage and percolation strength to obtain simulated optical transmittance which matches experimental observation. The coherence of resistivity and optical transmittance validates the simulation of the sputtered pattern and the incorporation of percolation theory in the model.
ContributorsFang, Chia-Ling (Author) / Alford, Terry L. (Thesis advisor) / Crozier, Peter (Committee member) / Theodore, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Composite materials are increasingly being used in aircraft, automobiles, and other applications due to their high strength to weight and stiffness to weight ratios. However, the presence of damage, such as delamination or matrix cracks, can significantly compromise the performance of these materials and result in premature failure. Structural components are often manually inspected to detect the presence of damage. This technique, known as schedule based maintenance, however, is expensive, time-consuming, and often limited to easily accessible structural elements. Therefore, there is an increased demand for robust and efficient Structural Health Monitoring (SHM) techniques that can be used for Condition Based Monitoring, which is the method in which structural components are inspected based upon damage metrics as opposed to flight hours. SHM relies on in situ frameworks for detecting early signs of damage in exposed and unexposed structural elements, offering not only reduced number of schedule based inspections, but also providing better useful life estimates. SHM frameworks require the development of different sensing technologies, algorithms, and procedures to detect, localize, quantify, characterize, as well as assess overall damage in aerospace structures so that strong estimations in the remaining useful life can be determined. The use of piezoelectric transducers along with guided Lamb waves is a method that has received considerable attention due to the weight, cost, and function of the systems based on these elements. The research in this thesis investigates the ability of Lamb waves to detect damage in feature dense anisotropic composite panels. Most current research negates the effects of experimental variability by performing tests on structurally simple isotropic plates that are used as a baseline and damaged specimen. However, in actual applications, variability cannot be negated, and therefore there is a need to research the effects of complex sample geometries, environmental operating conditions, and the effects of variability in material properties. This research is based on experiments conducted on a single blade-stiffened anisotropic composite panel that localizes delamination damage caused by impact. The overall goal was to utilize a correlative approach that used only the damage feature produced by the delamination as the damage index. This approach was adopted because it offered a simplistic way to determine the existence and location of damage without having to conduct a more complex wave propagation analysis or having to take into account the geometric complexities of the test specimen. Results showed that even in a complex structure, if the damage feature can be extracted and measured, then an appropriate damage index can be associated to it and the location of the damage can be inferred using a dense sensor array. The second experiment presented in this research studies the effects of temperature on damage detection when using one test specimen for a benchmark data set and another for damage data collection. This expands the previous experiment into exploring not only the effects of variable temperature, but also the effects of high experimental variability. Results from this work show that the damage feature in the data is not only extractable at higher temperatures, but that the data from one panel at one temperature can be directly compared to another panel at another temperature for baseline comparison due to linearity of the collected data.
ContributorsVizzini, Anthony James, II (Author) / Chattopadhyay, Aditi (Thesis advisor) / Fard, Masoud (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2012
Description
The electrochemical behavior of nanoscale solids has become an important topic to applications, such as catalysis, sensing, and nano–electronic devices. The electrochemical behavior of elemental metal and alloy particles was studied in this work both theoretically and experimentally. A systematic thermodynamic derivation for the size–dependent Pourbaix Diagram for elemental metal particles is presented. The stability of Pt particles was studied by in situ electrochemical scanning tunneling microscopy (ECSTM). It is shown that small Pt particles dissolve at a lower potential than the corresponding bulk material. For the alloy particles, two size ranges of AuAg particles, ∼4 nm and ∼45 nm in diameter, were synthesized by co–reduction of the salts of Au and Ag from an aqueous phase. The alloy particles were dealloyed at a series of potential by chronoamperometry in acid, and the resulting morphology and composition were characterized by electron microscopy, energy dispersive X–ray spectroscopy (EDX). In the case of the smaller particles, only surface dealloying occurred yielding a core–shell structure. A porous structure was observed for the larger particles when the potential was larger than a critical value that was within 50 mV of the thermodynamic prediction.
ContributorsLi, Xiaoqian (Author) / Sieradzki, Karl (Thesis advisor) / Crozier, Peter (Committee member) / Buttry, Daniel (Committee member) / Friesen, Cody (Committee member) / Arizona State University (Publisher)
Created2012