Matching Items (99)
Description
In this dissertation, the surface interactions of fluorine were studied during atomic layer deposition (ALD) and atomic layer etching (ALE) of wide band gap materials. To enable this research two high vacuum reactors were designed and constructed for thermal and plasma enhanced ALD and ALE, and they were equipped for in-situ process monitoring. Fluorine surface interactions were first studied in a comparison of thermal and plasma enhanced ALD (TALD and PEALD) of AlF3 thin films prepared using hydrogen fluoride (HF), trimethylaluminum (TMA), and H2-plasma. The ALD AlF3 films were compared ¬in-situ using ellipsometry and X-ray photoelectron spectroscopy (XPS). Ellipsometry showed a growth rate of 1.1 Å/ cycle and 0.7 Å/ cycle, at 100°C, for the TALD and PEALD AlF3 processes, respectively. XPS indicated the presence of Al-rich clusters within the PEALD film. The formation of the Al-rich clusters is thought to originate during the H2-plasma step of the PEALD process. The Al-rich clusters were not detected in the TALD AlF3 films. This study provided valuable insight on the role of fluorine in an ALD process.
Reactive ion etching is a common dry chemical etch process for fabricating GaN devices. However, the use of ions can induce various defects, which can degrade device performance. The development of low-damage post etch processes are essential for mitigating plasma induced damage. As such, two multistep ALE methods were implemented for GaN based on oxidation, fluorination, and ligand exchange. First, GaN surfaces were oxidized using either water vapor or O2-plasma exposures to produce a thin oxide layer. The oxide layer was addressed using alternating exposures of HF and TMG, which etch Ga2O3 films. Each ALE process was characterized using in-situ using ellipsometry and XPS and ex-situ transmission electron microscopy (TEM). XPS indicated F and O impurities remained on the etched surfaces. Ellipsometry and TEM showed a slight reduction in thickness. The very low ALE rate was interpreted as the inability of the Ga2O3 ALE process to fluorinate the ordered surface oxide on GaN (0001).
Overall, these results indicate HF is effective for the ALD of metal fluorides and the ALE of metal oxides.
ContributorsMessina, Daniel C (Author) / Nemanich, Robert J (Thesis advisor) / Goodnick, Stephen (Committee member) / Ponce, Fernando A (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2021
Description
In this research, I surveyed existing methods of characterizing Epilepsy from Electroencephalogram (EEG) data, including the Random Forest algorithm, which was claimed by many researchers to be the most effective at detecting epileptic seizures [7]. I observed that although many papers claimed a detection of >99% using Random Forest, it was not specified “when” the detection was declared within the 23.6 second interval of the seizure event. In this research, I created a time-series procedure to detect the seizure as early as possible within the 23.6 second epileptic seizure window and found that the detection is effective (> 92%) as early as the first few seconds of the epileptic episode. I intend to use this research as a stepping stone towards my upcoming Masters thesis research where I plan to expand the time-series detection mechanism to the pre-ictal stage, which will require a different dataset.
ContributorsBou-Ghazale, Carine (Author) / Lai, Ying-Cheng (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2022-05
Description
Predicting nonlinear dynamical systems has been a long-standing challenge in science. This field is currently witnessing a revolution with the advent of machine learning methods. Concurrently, the analysis of dynamics in various nonlinear complex systems continues to be crucial. Guided by these directions, I conduct the following studies. Predicting critical transitions and transient states in nonlinear dynamics is a complex problem. I developed a solution called parameter-aware reservoir computing, which uses machine learning to track how system dynamics change with a driving parameter. I show that the transition point can be accurately predicted while trained in a sustained functioning regime before the transition. Notably, it can also predict if the system will enter a transient state, the distribution of transient lifetimes, and their average before a final collapse, which are crucial for management. I introduce a machine-learning-based digital twin for monitoring and predicting the evolution of externally driven nonlinear dynamical systems, where reservoir computing is exploited. Extensive tests on various models, encompassing optics, ecology, and climate, verify the approach’s effectiveness. The digital twins can extrapolate unknown system dynamics, continually forecast and monitor under non-stationary external driving, infer hidden variables, adapt to different driving waveforms, and extrapolate bifurcation behaviors across varying system sizes. Integrating engineered gene circuits into host cells poses a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback. I conducted systematic studies on hundreds of circuit structures exhibiting various functionalities, and identified a comprehensive categorization of growth-induced failures. I discerned three dynamical mechanisms behind these circuit failures. Moreover, my comprehensive computations reveal a scaling law between the circuit robustness and the intensity of growth feedback. A class of circuits with optimal robustness is also identified. Chimera states, a phenomenon of symmetry-breaking in oscillator networks, traditionally have transient lifetimes that grow exponentially with system size. However, my research on high-dimensional oscillators leads to the discovery of ’short-lived’ chimera states. Their lifetime increases logarithmically with system size and decreases logarithmically with random perturbations, indicating a unique fragility. To understand these states, I use a transverse stability analysis supported by simulations.
ContributorsKong, Lingwei (Author) / Lai, Ying-Cheng (Thesis advisor) / Tian, Xiaojun (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Alkhateeb, Ahmed (Committee member) / Arizona State University (Publisher)
Created2023
Description
A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve successive cell fate transitions, nonlinear resource competition within synthetic gene circuits is unveiled. However, in vivo it can be seen that the transition path was redirected with the activation of one switch always prevailing over that of the other, contradictory to coactivation theoretically expected. This behavior is a result of resource competition between genes and follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the two modules. Despite investigation demonstrating that resource competition between gene modules can significantly alter circuit deterministic behaviors, how resource competition contributes to gene expression noise and how this noise can be controlled is still an open issue of fundamental importance in systems biology and biological physics. By utilizing a two-gene circuit, the effects of resource competition on protein expression noise levels can be closely studied. A surprising double-edged role is discovered: the competition for these resources decreases noise while the constraint on resource availability adds its own term of noise into the system, denoted “resource competitive” noise. Noise reduction effects are then studied using orthogonal resources. Results indicate that orthogonal resources are a good strategy for eliminating the contribution of resource competition to gene expression noise.
Noise propagation through a cascading circuit has been considered without resource competition. It has been noted that the noise from upstream genes can be transmitted downstream. However, resource competition’s effects on this cascading noise have yet to be studied. When studied, it is found that resource competition can induce stochastic state
switching and perturb noise propagation. Orthogonal resources can remove some of the resource competitive behavior and allow for a system with less noise.
ContributorsGoetz, Hanah Elizabeth (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2022
ContributorsForgey, Sydney (Performer) / Hickman, Miriam, 1955- (Performer) / Smith, David (Performer) / ASU Library. Music Library (Publisher)
Created2020-03-25
Description
A piezoelectric transducer, comprised of electroded and active pad PZT layer atop a backing PZT layer and protected with an acoustic matching layer, and operating under a pulse-echo technique for longitudinal ultrasonic imaging, acts as both source and detector.
Ultrasonic transducer stacks (modules), which had failed or passed during pulse-echo sensitivity testing, were received from Consortium X. With limited background information on these stacks, the central theme was to determine the origin(s) of failure via the use of thermal and physicochemical characterization techniques.
The optical and scanning electron microscopy revealed that contact electrode layers are discontinuous in all samples, while delaminations between electrodes and pad layer were observed in failed samples. The X-ray diffraction data on the pad PZT revealed an overall c/a ratio of 1.022 ratio and morphotropic boundary composition, with significant variations of the Zr to Ti ratio within a sample and between samples. Electron probe microanalysis confirmed that the overall Zr to Ti ratio of the pad PZT was 52/48, and higher amounts of excess PbO in failed samples, whereas, inductively coupled plasma mass spectrometry revealed the presence of Mn, Al, and Sb (dopants) and presence of Cu (sintering aid) in in this hard (pad) PZT. Additionally, three exothermic peaks during thermal analysis was indicative of incomplete calcination of pad PZT. Moreover, transmission electron microscopy and scanning transmission electron microscopy revealed the presence of parylene at the Ag-pad PZT interface and within the pores of pad PZT (in failed samples subjected to electric fields). This further dilutes the electrical, mechanical, and electromechanical properties of the pad PZT, which in turn detrimentally influences the pulse echo sensitivity.
Ultrasonic transducer stacks (modules), which had failed or passed during pulse-echo sensitivity testing, were received from Consortium X. With limited background information on these stacks, the central theme was to determine the origin(s) of failure via the use of thermal and physicochemical characterization techniques.
The optical and scanning electron microscopy revealed that contact electrode layers are discontinuous in all samples, while delaminations between electrodes and pad layer were observed in failed samples. The X-ray diffraction data on the pad PZT revealed an overall c/a ratio of 1.022 ratio and morphotropic boundary composition, with significant variations of the Zr to Ti ratio within a sample and between samples. Electron probe microanalysis confirmed that the overall Zr to Ti ratio of the pad PZT was 52/48, and higher amounts of excess PbO in failed samples, whereas, inductively coupled plasma mass spectrometry revealed the presence of Mn, Al, and Sb (dopants) and presence of Cu (sintering aid) in in this hard (pad) PZT. Additionally, three exothermic peaks during thermal analysis was indicative of incomplete calcination of pad PZT. Moreover, transmission electron microscopy and scanning transmission electron microscopy revealed the presence of parylene at the Ag-pad PZT interface and within the pores of pad PZT (in failed samples subjected to electric fields). This further dilutes the electrical, mechanical, and electromechanical properties of the pad PZT, which in turn detrimentally influences the pulse echo sensitivity.
ContributorsPeri, Prudhvi Ram (Author) / Dey, Sandwip (Thesis advisor) / Smith, David (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2018
Description
Computer assisted language learning (CALL) has become increasingly common as a means of helping learners develop essential skills in a second or foreign language. However, while many CALL programs claim to be based on principles of second language acquisition (SLA) theory and research, evaluation of design and learning outcomes at the level of individual CALL exercises is lacking in the existing literature. The following proposed study will explore the design of computer-based vocabulary matching exercises using both written text and images and the effects of various design manipulations on learning outcomes. The study will use eye-tracking to investigate what users attend to on screen as they work through a series of exercises with different configurations of written words and images. It will ask whether manipulation of text and image features and combinations can have an effect on learners’ attention to the various elements, and if so, whether differences in levels of attention results in higher or lower scores for measures of learning. Specifically, eye-tracking data will be compared to post-test scores for recall and recognition of target vocabulary items to look for a correlation between levels of attention to written forms in-task and post-test gains in scores for vocabulary learning.
ContributorsPatchin, Colleen (Author) / Smith, David (Thesis advisor) / Ross, Andrew (Committee member) / James, Mark (Committee member) / Arizona State University (Publisher)
Created2019
Description
The research on the topology and dynamics of complex networks is one of the most focused area in complex system science. The goals are to structure our understanding of the real-world social, economical, technological, and biological systems in the aspect of networks consisting a large number of interacting units and to develop corresponding detection, prediction, and control strategies. In this highly interdisciplinary field, my research mainly concentrates on universal estimation schemes, physical controllability, as well as mechanisms behind extreme events and cascading failure for complex networked systems.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
ContributorsChen, Yuzhong (Author) / Lai, Ying-Cheng (Thesis advisor) / Spanias, Andreas (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2016
Description
This dissertation describes fundamental studies of hollow carbon nanostructures, which may be used as electrodes for practical energy storage applications such as batteries or supercapacitors. Electron microscopy is heavily utilized for the nanoscale characterization. To control the morphology of hollow carbon nanostructures, ZnO nanowires serve as sacrificial templates. The first part of this dissertation focuses on the optimization of synthesis parameters and the scale-up production of ZnO nanowires by vapor transport method. Uniform ZnO nanowires with 40 nm width can be produced by using 1100 °C reaction temperature and 20 sccm oxygen flow rate, which are the two most important parameters.
The use of ethanol as carbon source with or without water steam provides uniform carbonaceous deposition on ZnO nanowire templates. The amount of as-deposited carbonaceous material can be controlled by reaction temperature and reaction time. Due to the catalytic property of ZnO surface, the thicknesses of carbonaceous layers are typically in nanometers. Different methods to remove the ZnO templates are explored, of which hydrogen reduction at temperatures higher than 700 °C is most efficient. The ZnO templates can also be removed under ethanol environment, but the temperatures need to be higher than 850 °C for practical use.
Characterizations of hollow carbon nanofibers show that the hollow carbon nanostructures have a high specific surface area (>1100 m2/g) with the presence of mesopores (~3.5 nm). The initial data on energy storage as electrodes of electrochemical double layer capacitors show that high specific capacitance (> 220 F/g) can be obtained, which is related to the high surface area and unique porous hollow structure with a thin wall.
The use of ethanol as carbon source with or without water steam provides uniform carbonaceous deposition on ZnO nanowire templates. The amount of as-deposited carbonaceous material can be controlled by reaction temperature and reaction time. Due to the catalytic property of ZnO surface, the thicknesses of carbonaceous layers are typically in nanometers. Different methods to remove the ZnO templates are explored, of which hydrogen reduction at temperatures higher than 700 °C is most efficient. The ZnO templates can also be removed under ethanol environment, but the temperatures need to be higher than 850 °C for practical use.
Characterizations of hollow carbon nanofibers show that the hollow carbon nanostructures have a high specific surface area (>1100 m2/g) with the presence of mesopores (~3.5 nm). The initial data on energy storage as electrodes of electrochemical double layer capacitors show that high specific capacitance (> 220 F/g) can be obtained, which is related to the high surface area and unique porous hollow structure with a thin wall.
ContributorsSong, Yian (Author) / Liu, Jingyue (Committee member) / Smith, David (Committee member) / McCartney, Martha (Committee member) / Chen, Tingyong (Committee member) / Arizona State University (Publisher)
Created2016
Description
This dissertation presents research findings regarding the exploitation of localized surface plasmon (LSP) of epitaxial Ag islands as a means to enhance the photoluminescence (PL) of Germanium (Ge) quantum dots (QDs). The first step of this project was to investigate the growth of Ag islands on Si(100). Two distinct families of Ag islands have been observed. “Big islands” are clearly faceted and have basal dimensions in the few hundred nm to μm range with a variety of basal shapes. “Small islands” are not clearly faceted and have basal diameters in the 10s of nm range. Big islands form via a nucleation and growth mechanism, and small islands form via precipitation of Ag contained in a planar layer between the big islands that is thicker than the Stranski-Krastanov layer existing at room-temperature.
The pseudodielectric functions of epitaxial Ag islands on Si(100) substrates were investigated with spectroscopic ellipsometry. Comparing the experimental pseudodielectric functions obtained for Si with and without Ag islands clearly identifies a plasmon mode with its dipole moment perpendicular to the surface. This observation is confirmed using a simulation based on the thin island film (TIF) theory. Another mode parallel to the surface may be identified by comparing the experimental pseudodielectric functions with the simulated ones from TIF theory. Additional results suggest that the LSP energy of Ag islands can be tuned from the ultra-violet to the infrared range by an amorphous Si (α-Si) cap layer.
Heterostructures were grown that incorporated Ge QDs, an epitaxial Si cap layer and Ag islands grown atop the Si cap layer. Optimum growth conditions for distinct Ge dot ensembles and Si cap layers were obtained. The density of Ag islands grown on the Si cap layer depends on its thickness. Factors contributing to this effect may include the average strain and Ge concentration on the surface of the Si cap layer.
The effects of the Ag LSP on the PL of Ge coherent domes were investigated for both α-Si capped and bare Ag islands. For samples with low-doped substrates, the LSPs reduce the Ge dot-related PL when the Si cap layer is below some critical thickness and have no effect on the PL when the Si cap layer is above the critical thickness. For samples grown on highly-doped wafers, the LSP of bare Ag islands enhanced the PL of Ge QDs by ~ 40%.
The pseudodielectric functions of epitaxial Ag islands on Si(100) substrates were investigated with spectroscopic ellipsometry. Comparing the experimental pseudodielectric functions obtained for Si with and without Ag islands clearly identifies a plasmon mode with its dipole moment perpendicular to the surface. This observation is confirmed using a simulation based on the thin island film (TIF) theory. Another mode parallel to the surface may be identified by comparing the experimental pseudodielectric functions with the simulated ones from TIF theory. Additional results suggest that the LSP energy of Ag islands can be tuned from the ultra-violet to the infrared range by an amorphous Si (α-Si) cap layer.
Heterostructures were grown that incorporated Ge QDs, an epitaxial Si cap layer and Ag islands grown atop the Si cap layer. Optimum growth conditions for distinct Ge dot ensembles and Si cap layers were obtained. The density of Ag islands grown on the Si cap layer depends on its thickness. Factors contributing to this effect may include the average strain and Ge concentration on the surface of the Si cap layer.
The effects of the Ag LSP on the PL of Ge coherent domes were investigated for both α-Si capped and bare Ag islands. For samples with low-doped substrates, the LSPs reduce the Ge dot-related PL when the Si cap layer is below some critical thickness and have no effect on the PL when the Si cap layer is above the critical thickness. For samples grown on highly-doped wafers, the LSP of bare Ag islands enhanced the PL of Ge QDs by ~ 40%.
ContributorsKong, Dexin (Author) / Drucker, Jeffery (Thesis advisor) / Chen, Tingyong (Committee member) / Ros, Robert (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2015