Matching Items (99)
Description
Photocatalytic water splitting is a promising technique to produce H2 fuels from water using sustainable solar energy. To better design photocatalysts, the understanding of charge transfer at surfaces/interfaces and the corresponding structure change during the reaction is very important. Local structural and chemical information on nanoparticle surfaces or interfaces can be achieved through characterizations on transmission electron microscopy (TEM). Emphasis should be put on materials structure changes during the reactions in their “working conditions”. Environmental TEM with in situ light illumination system allows the photocatalysts to be studied under light irradiation when exposed to H2O vapor. A set of ex situ and in situ TEM characterizations are carried out on typical types of TiO2 based photocatalysts. The observed structure changes during the reaction are correlated with the H2 production rate for structure-property relationships.
A surface disordering was observed in situ when well-defined anatase TiO2 rhombohedral nanoparticles were exposed to 1 Torr H2O vapor and 10suns light inside the environmental TEM. The disordering is believed to be related to high density of hydroxyl groups formed on surface oxygen vacancies during water splitting reactions.
Pt co-catalyst on TiO2 is able to split pure water producing H2 and O2. The H2 production rate drops during the reaction. Particle size growth during reaction was discovered with Z-contrast images. The particle size growth is believed to be a photo-electro-chemical Ostwald ripening.
Characterizations were also carried out on a more complicated photocatalyst system: Ni/NiO core/shell co-catalyst on TiO2. A decrease of the H2 production rate resulting from photo-corrosion was observed. The Ni is believed to be oxidized to Ni2+ by OH• radicals which are intermediate products of H2O oxidation. The mechanism that the OH• radicals leak into the cores through cracks on NiO shells is more supported by experiments.
Overall this research has done a comprehensive ex situ and in situ TEM characterizations following some typical TiO2 based photocatalysts during reactions. This research has shown the technique availability to study photocatalyst inside TEM in photocatalytic conditions. It also demonstrates the importance to follow structure changes of materials during reactions in understanding deactivation mechanisms.
A surface disordering was observed in situ when well-defined anatase TiO2 rhombohedral nanoparticles were exposed to 1 Torr H2O vapor and 10suns light inside the environmental TEM. The disordering is believed to be related to high density of hydroxyl groups formed on surface oxygen vacancies during water splitting reactions.
Pt co-catalyst on TiO2 is able to split pure water producing H2 and O2. The H2 production rate drops during the reaction. Particle size growth during reaction was discovered with Z-contrast images. The particle size growth is believed to be a photo-electro-chemical Ostwald ripening.
Characterizations were also carried out on a more complicated photocatalyst system: Ni/NiO core/shell co-catalyst on TiO2. A decrease of the H2 production rate resulting from photo-corrosion was observed. The Ni is believed to be oxidized to Ni2+ by OH• radicals which are intermediate products of H2O oxidation. The mechanism that the OH• radicals leak into the cores through cracks on NiO shells is more supported by experiments.
Overall this research has done a comprehensive ex situ and in situ TEM characterizations following some typical TiO2 based photocatalysts during reactions. This research has shown the technique availability to study photocatalyst inside TEM in photocatalytic conditions. It also demonstrates the importance to follow structure changes of materials during reactions in understanding deactivation mechanisms.
ContributorsZhang, Liuxian (Author) / Crozier, Peter (Thesis advisor) / Smith, David (Committee member) / Chan, Candace (Committee member) / Liu, Jingyue (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purpose of information source detection problem (or called rumor source detection) is to identify the source of information diffusion in networks based on available observations like the states of the nodes and the timestamps at which nodes adopted the information (or called infected). The solution of the problem can be used to answer a wide range of important questions in epidemiology, computer network security, etc. This dissertation studies the fundamental theory and the design of efficient and robust algorithms for the information source detection problem.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
ContributorsZhu, Kai (Author) / Ying, Lei (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Liu, Huan (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2015
Description
Conductance fluctuations associated with quantum transport through quantumdot systems are currently understood to depend on the nature of the corresponding classical dynamics, i.e., integrable or chaotic. There are a couple of interesting phenomena about conductance fluctuation and quantum tunneling related to geometrical shapes of graphene systems. Firstly, in graphene quantum-dot systems, when a magnetic field is present, as the Fermi energy or the magnetic flux is varied, both regular oscillations and random fluctuations in the conductance can occur, with alternating transitions between the two. Secondly, a scheme based on geometrical rotation of rectangular devices to effectively modulate the conductance fluctuations is presented. Thirdly, when graphene is placed on a substrate of heavy metal, Rashba spin-orbit interaction of substantial strength can occur. In an open system such as a quantum dot, the interaction can induce spin polarization. Finally, a problem using graphene systems with electron-electron interactions described by the Hubbard Hamiltonian in the setting of resonant tunneling is investigated.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
ContributorsYing, Lei (Author) / Lai, Ying-Cheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Chen, Tingyong (Committee member) / Yao, Yu (Committee member) / Arizona State University (Publisher)
Created2016
Description
In this dissertation, the interface chemistry and electronic structure of plasma-enhanced atomic layer deposited (PEALD) dielectrics on GaN are investigated with x-ray and ultraviolet photoemission spectroscopy (XPS and UPS). Three interrelated issues are discussed in this study: (1) PEALD dielectric growth process optimization, (2) interface electronic structure of comparative PEALD dielectrics on GaN, and (3) interface electronic structure of PEALD dielectrics on Ga- and N-face GaN. The first study involved an in-depth case study of PEALD Al2O3 growth using dimethylaluminum isopropoxide, with a special focus on oxygen plasma effects. Saturated and self-limiting growth of Al2O3 films were obtained with an enhanced growth rate within the PEALD temperature window (25-220 ºC). The properties of Al2O3 deposited at various temperatures were characterized to better understand the relation between the growth parameters and film properties. In the second study, the interface electronic structures of PEALD dielectrics on Ga-face GaN films were measured. Five promising dielectrics (Al2O3, HfO2, SiO2, La2O3, and ZnO) with a range of band gap energies were chosen. Prior to dielectric growth, a combined wet chemical and in-situ H2/N2 plasma clean process was employed to remove the carbon contamination and prepare the surface for dielectric deposition. The surface band bending and band offsets were measured by XPS and UPS for dielectrics on GaN. The trends of the experimental band offsets on GaN were related to the dielectric band gap energies. In addition, the experimental band offsets were near the calculated values based on the charge neutrality level model. The third study focused on the effect of the polarization bound charge of the Ga- and N-face GaN on interface electronic structures. A surface pretreatment process consisting of a NH4OH wet chemical and an in-situ NH3 plasma treatment was applied to remove carbon contamination, retain monolayer oxygen coverage, and potentially passivate N-vacancy related defects. The surface band bending and polarization charge compensation of Ga- and N-face GaN were investigated. The surface band bending and band offsets were determined for Al2O3, HfO2, and SiO2 on Ga- and N-face GaN. Different dielectric thicknesses and post deposition processing were investigated to understand process related defect formation and/or reduction.
ContributorsYang, Jialing (Author) / Nemanich, Robert J (Thesis advisor) / Chen, Tingyong (Committee member) / Peng, Xihong (Committee member) / Ponce, Fernando (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation presents research findings on the three materials systems: lateral Si nanowires (SiNW), In2Se3/Bi2Se3 heterostructures and graphene. The first part of the thesis was focused on the growth and characterization of lateral SiNW. Lateral here refers to wires growing along the plane of substrate; vertical NW on the other hand grow out of the plane of substrate. It was found, using the Au-seeded vapor – liquid – solid technique, that epitaxial single-crystal SiNW can be grown laterally along Si(111) substrates that have been miscut toward [11− 2]. The ratio of lateral-to-vertical NW was found to increase as the miscut angle increased and as disilane pressure and substrate temperature decreased. Based on this observation, growth parameters were identified whereby all of the deposited Au seeds formed lateral NW. Furthermore, the nanofaceted substrate guided the growth via a mechanism that involved pinning of the trijunction at the liquid/solid interface of the growing nanowire.
Next, the growth of selenide heterostructures was explored. Specifically, molecular beam epitaxy was utilized to grow In2Se3 and Bi2Se3 films on h-BN, highly oriented pyrolytic graphite and Si(111) substrates. Growth optimizations of In2Se3 and Bi2Se3 films were carried out by systematically varying the growth parameters. While the growth of these films was demonstrated on h-BN and HOPG surface, the majority of the effort was focused on growth on Si(111). Atomically flat terraces that extended laterally for several hundred nm, which were separated by single quintuple layer high steps characterized surface of the best In2Se3 films grown on Si(111). These In2Se3 films were suitable for subsequent high quality epitaxy of Bi2Se3 .
The last part of this dissertation was focused on a recently initiated and ongoing study of graphene growth on liquid metal surfaces. The initial part of the study comprised a successful modification of an existing growth system to accommodate graphene synthesis and process development for reproducible graphene growth. Graphene was grown on Cu, Au and AuCu alloys at varioua conditions. Preliminary results showed triangular features on the liquid part of the Cu metal surface. For Au, and AuCu alloys, hexagonal features were noticed both on the solid and liquid parts.
Next, the growth of selenide heterostructures was explored. Specifically, molecular beam epitaxy was utilized to grow In2Se3 and Bi2Se3 films on h-BN, highly oriented pyrolytic graphite and Si(111) substrates. Growth optimizations of In2Se3 and Bi2Se3 films were carried out by systematically varying the growth parameters. While the growth of these films was demonstrated on h-BN and HOPG surface, the majority of the effort was focused on growth on Si(111). Atomically flat terraces that extended laterally for several hundred nm, which were separated by single quintuple layer high steps characterized surface of the best In2Se3 films grown on Si(111). These In2Se3 films were suitable for subsequent high quality epitaxy of Bi2Se3 .
The last part of this dissertation was focused on a recently initiated and ongoing study of graphene growth on liquid metal surfaces. The initial part of the study comprised a successful modification of an existing growth system to accommodate graphene synthesis and process development for reproducible graphene growth. Graphene was grown on Cu, Au and AuCu alloys at varioua conditions. Preliminary results showed triangular features on the liquid part of the Cu metal surface. For Au, and AuCu alloys, hexagonal features were noticed both on the solid and liquid parts.
ContributorsRathi, Somilkumar J (Author) / Drucker, Jeffery (Thesis advisor) / Smith, David (Committee member) / Chen, Tingyong (Committee member) / Arizona State University (Publisher)
Created2014
Description
GaN and AlGaN have shown great potential in next-generation power and RF electronics. However, these devices are limited by reliability issues such as leakage current and current collapse that result from surface and interface states on GaN and AlGaN. This dissertation, therefore, examined these electronic states, focusing on the following two points:
First, the surface electronic state configuration was examined with regards to the polarization bound 1013 charges/cm2 that increases with aluminum content. This large bound charge requires compensation either externally by surface states or internally by the space charge regions as relates to band bending. In this work, band bending was measured after different surface treatments of GaN and AlGaN to determine the effects of specific surface states on the electronic state configuration. Results showed oxygen-terminated N-face GaN, Ga-face GaN, and Ga-face Al0.25Ga0.75N surface were characterized by similar band bending regardless of the polarization bound charge, suggesting a Fermi level pinning state ~0.4-0.8 eV below the conduction band minimum. On oxygen-free Ga-face GaN, Al0.15Ga0.85N, Al0.25Ga0.75N, and Al0.35Ga0.65N, band bending increased slightly with aluminum content and thus did not exhibit the same pinning behavior; however, there was still significant compensating charge on these surfaces (~1013 charges/cm2). This charge is likely related to nitrogen vacancies and/or gallium dangling bonds.
In addition, this wozrk investigated the interface electronic state configuration of dielectric/GaN and AlGaN interfaces with regards to deposition conditions and aluminum content. Specifically, oxygen plasma-enhanced atomic layer deposited (PEALD) was used to deposit SiO2. Growth temperature was shown to influence the film quality, where room temperature deposition produced the highest quality films in terms of electrical breakdown. In addition, the valence band offsets (VBOs) appeared to decrease with the deposition temperature, which likely related to an electric field across the Ga2O3 interfacial layer. VBOs were also determined with respect to aluminum content at the PEALD-SiO2/AlxGa1-xN interface, giving 3.0, 2.9, 2.9, and 2.8 eV for 0%, 15%, 25%, and 35% aluminum content, respectively—with corresponding conduction band offsets of 2.5, 2.2, 1.9, and 1.8 eV. This suggests the largest difference manifests in the conduction band, which is in agreement with the charge neutrality level model.
First, the surface electronic state configuration was examined with regards to the polarization bound 1013 charges/cm2 that increases with aluminum content. This large bound charge requires compensation either externally by surface states or internally by the space charge regions as relates to band bending. In this work, band bending was measured after different surface treatments of GaN and AlGaN to determine the effects of specific surface states on the electronic state configuration. Results showed oxygen-terminated N-face GaN, Ga-face GaN, and Ga-face Al0.25Ga0.75N surface were characterized by similar band bending regardless of the polarization bound charge, suggesting a Fermi level pinning state ~0.4-0.8 eV below the conduction band minimum. On oxygen-free Ga-face GaN, Al0.15Ga0.85N, Al0.25Ga0.75N, and Al0.35Ga0.65N, band bending increased slightly with aluminum content and thus did not exhibit the same pinning behavior; however, there was still significant compensating charge on these surfaces (~1013 charges/cm2). This charge is likely related to nitrogen vacancies and/or gallium dangling bonds.
In addition, this wozrk investigated the interface electronic state configuration of dielectric/GaN and AlGaN interfaces with regards to deposition conditions and aluminum content. Specifically, oxygen plasma-enhanced atomic layer deposited (PEALD) was used to deposit SiO2. Growth temperature was shown to influence the film quality, where room temperature deposition produced the highest quality films in terms of electrical breakdown. In addition, the valence band offsets (VBOs) appeared to decrease with the deposition temperature, which likely related to an electric field across the Ga2O3 interfacial layer. VBOs were also determined with respect to aluminum content at the PEALD-SiO2/AlxGa1-xN interface, giving 3.0, 2.9, 2.9, and 2.8 eV for 0%, 15%, 25%, and 35% aluminum content, respectively—with corresponding conduction band offsets of 2.5, 2.2, 1.9, and 1.8 eV. This suggests the largest difference manifests in the conduction band, which is in agreement with the charge neutrality level model.
ContributorsEller, Brianna (Author) / Nemanich, Robert J (Thesis advisor) / Chowdhury, Srabanti (Committee member) / McCartney, Martha (Committee member) / Ponce, Fernando (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2015
Description
This dissertation treats a number of related problems in control and data analysis of complex networks.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
ContributorsWang, Lezhi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Papandreoou-Suppappola, Antonia (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
Online social media is popular due to its real-time nature, extensive connectivity and a large user base. This motivates users to employ social media for seeking information by reaching out to their large number of social connections. Information seeking can manifest in the form of requests for personal and time-critical information or gathering perspectives on important issues. Social media platforms are not designed for resource seeking and experience large volumes of messages, leading to requests not being fulfilled satisfactorily. Designing frameworks to facilitate efficient information seeking in social media will help users to obtain appropriate assistance for their needs
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
ContributorsRanganath, Suhas (Author) / Liu, Huan (Thesis advisor) / Lai, Ying-Cheng (Thesis advisor) / Tong, Hanghang (Committee member) / Vaculin, Roman (Committee member) / Arizona State University (Publisher)
Created2017
Description
Resilience is emerging as the preferred way to improve the protection of infrastructure systems beyond established risk management practices. Massive damages experienced during tragedies like Hurricane Katrina showed that risk analysis is incapable to prevent unforeseen infrastructure failures and shifted expert focus towards resilience to absorb and recover from adverse events. Recent, exponential growth in research is now producing consensus on how to think about infrastructure resilience centered on definitions and models from influential organizations like the US National Academy of Sciences. Despite widespread efforts, massive infrastructure failures in 2017 demonstrate that resilience is still not working, raising the question: Are the ways people think about resilience producing resilient infrastructure systems?
This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.
Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.
This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.
Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.
ContributorsEisenberg, Daniel Alexander (Author) / Seager, Thomas P. (Thesis advisor) / Park, Jeryang (Thesis advisor) / Alderson, David L. (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2018
Description
This dissertation aims to study and understand the effect of nonlinear dynamics and quantum chaos in graphene, optomechanics, photonics and spintronics systems.
First, in graphene quantum dot systems, conductance fluctuations are investigated from the respects of Fano resonances and quantum chaos. The conventional semi-classical theory of quantum chaotic scattering used in this field depends on an invariant classical phase-space structure. I show that for systems without an invariant classical phase-space structure, the quantum pointer states can still be used to explain the conductance fluctuations. Another finding is that the chaotic geometry is demonstrated to have similar effects as the disorders in transportations.
Second, in optomechanics systems, I find rich nonlinear dynamics. Using the semi-classical Langevin equations, I demonstrate a quasi-periodic motion is favorable for the quantum entanglement between the optical mode and mechanical mode. Then I use the quantum trajectory theory to provide a new resolution for the breakdown of the classical-quantum correspondences in the chaotic regions.
Third, I investigate the analogs of the electrical band structures and effects in the non-electrical systems. In the photonic systems, I use an array of waveguides to simulate the transport of the massive relativistic particle in a non-Hermitian scenario. A new form of Zitterbewegung is discovered as well as its analytical explanation. In mechanical systems, I use springs and mass points systems to achieve a three band degenerate band structure with a new pair of spatially separated edge states in the Dice lattice. A new semi-metal phase with the intrinsic valley-Hall effect is found.
At last, I investigate the nonlinear dynamics in the spintronics systems, in which the topological insulator couples with a magnetization. Rich nonlinear dynamics are discovered in this systems, especially the multi-stability states.
First, in graphene quantum dot systems, conductance fluctuations are investigated from the respects of Fano resonances and quantum chaos. The conventional semi-classical theory of quantum chaotic scattering used in this field depends on an invariant classical phase-space structure. I show that for systems without an invariant classical phase-space structure, the quantum pointer states can still be used to explain the conductance fluctuations. Another finding is that the chaotic geometry is demonstrated to have similar effects as the disorders in transportations.
Second, in optomechanics systems, I find rich nonlinear dynamics. Using the semi-classical Langevin equations, I demonstrate a quasi-periodic motion is favorable for the quantum entanglement between the optical mode and mechanical mode. Then I use the quantum trajectory theory to provide a new resolution for the breakdown of the classical-quantum correspondences in the chaotic regions.
Third, I investigate the analogs of the electrical band structures and effects in the non-electrical systems. In the photonic systems, I use an array of waveguides to simulate the transport of the massive relativistic particle in a non-Hermitian scenario. A new form of Zitterbewegung is discovered as well as its analytical explanation. In mechanical systems, I use springs and mass points systems to achieve a three band degenerate band structure with a new pair of spatially separated edge states in the Dice lattice. A new semi-metal phase with the intrinsic valley-Hall effect is found.
At last, I investigate the nonlinear dynamics in the spintronics systems, in which the topological insulator couples with a magnetization. Rich nonlinear dynamics are discovered in this systems, especially the multi-stability states.
ContributorsWang, Guanglei (Author) / Lai, Ying-Cheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Ning, Cun-Zheng (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2017