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University of Massachusetts Amherst

Theses/Dissertations

2019

Articles 1 - 30 of 89

Full-Text Articles in Physical Sciences and Mathematics

Elliptic Curves And Power Residues, Vy Thi Khanh Nguyen Nov 2019

Elliptic Curves And Power Residues, Vy Thi Khanh Nguyen

Doctoral Dissertations

Let E1 x E2 over Q be a fixed product of two elliptic curves over Q with complex multiplication. I compute the probability that the pth Fourier coefficient of E1 x E2, denoted as ap(E1) + ap(E2), is a square modulo p. The results are 1/4, 7/16, and 1/2 for different imaginary quadratic fields, given a technical independence of the twists. The similar prime densities for cubes and 4th power are 19/54, and 1/4, respectively. I also compute the probabilities without the technical …

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A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh Nov 2019

A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh

Doctoral Dissertations

High performance parallel computing and direct (factorization-based) solution methods have been the two main trends in electromagnetic computations in recent years. When time-harmonic (frequency-domain) Maxwell's equation are directly discretized with the Finite Element Method (FEM) or other Partial Differential Equation (PDE) methods, the resulting linear system of equations is sparse and indefinite, thus harder to efficiently factorize serially or in parallel than alternative methods e.g. integral equation solutions, that result in dense linear systems. State-of-the-art sparse matrix direct solvers such as MUMPS and PARDISO don't scale favorably, have low parallel efficiency and high memory footprint. This work introduces a new …

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Petrogenesis Of Basaltic Lavas In Iceland And The Springerville Volcanic Field, U.S.A.: The Influence Of Tectonic Setting, Depth Of Melting And Volatiles, Marissa Mnich Nov 2019

Petrogenesis Of Basaltic Lavas In Iceland And The Springerville Volcanic Field, U.S.A.: The Influence Of Tectonic Setting, Depth Of Melting And Volatiles, Marissa Mnich

Doctoral Dissertations

Icelandic basalts were long thought to be low in water (e.g. Gunnarsson et al., 1998), but more recent studies suggest that hotspots, like the Iceland mantle plume, may be a source of hydrous basaltic melts (Nichols et al., 2002). To explore a possible link between location, volatile concentration and resulting petrogenetic implications, samples were collected from eleven volcanic centers throughout Iceland. Water concentrations were measured in melt inclusions and phenocrysts using Fourier transform infrared (FTIR) spectroscopy. Results for a subset of samples indicate variable water in melt inclusions ranging from approximately 50 ppm to over 3000 ppm. Samples from southwestern …

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Tools For Tutoring Theoretical Computer Science Topics, Mark Mccartin-Lim Nov 2019

Tools For Tutoring Theoretical Computer Science Topics, Mark Mccartin-Lim

Doctoral Dissertations

This thesis introduces COMPLEXITY TUTOR, a tutoring system to assist in learning abstract proof-based topics, which has been specifically targeted towards the population of computer science students studying theoretical computer science. Existing literature has shown tremendous educational benefits produced by active learning techniques, student-centered pedagogy, gamification and intelligent tutoring systems. However, previously, there had been almost no research on adapting these ideas to the domain of theoretical computer science. As a population, computer science students receive immediate feedback from compilers and debuggers, but receive no similar level of guidance for theoretical coursework. One hypothesis of this thesis is that immediate …

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Fluorescence Spectroscopy And Microscopy Studies Of Chromophore Coupling In Isolated Small Molecule Nanostructures, Sarah R. Marques Oct 2019

Fluorescence Spectroscopy And Microscopy Studies Of Chromophore Coupling In Isolated Small Molecule Nanostructures, Sarah R. Marques

Doctoral Dissertations

My thesis focused on understanding the structural changes producing different spectral signatures seen in aggregates of 7,8,15,16- tetrazaterrylene (TAT). Recent work from our group showed crystallographically selective directional charge-separation within isolated extended TAT crystals without the need of an interface. Aggregates of different size not only exhibited different exciton recombination kinetics, but different spectral signatures. The motivation for understanding the change in the structural properties producing the unique spectral signatures is elucidating the mechanism of this directional charge-separation, intrinsic or extrinsic. In this case, an intrinsic mechanism means it is caused by molecular design and packing, and extrinsic mechanism means …

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Characterization Of Β-2-Microglobulin Pre-Amyloid Oligomers And Their Role In Amyloid Inhibition, Tyler M. Marcinko Oct 2019

Characterization Of Β-2-Microglobulin Pre-Amyloid Oligomers And Their Role In Amyloid Inhibition, Tyler M. Marcinko

Doctoral Dissertations

In dialysis patients, β-2 microglobulin (β2m) can aggregate and eventually form amyloid fibrils in a condition known as dialysis-related amyloidosis, which deleteriously affects joint, bone, and organ function, and eventually causes organ failure. To understand the early stages of the amyloid assembly process, we have employed a series of biophysical tools including chromatography, spectroscopy, and most especially, native electrospray ionization (ESI) together with ion mobility mass spectrometry (IM-MS) to study soluble pre-amyloid oligomeric species. We have also collaborated and integrated computational modeling to help better understand and rationalize the structural basis behind oligomerization. Recently, several small molecules have been identified …

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Neural Models For Information Retrieval Without Labeled Data, Hamed Zamani Oct 2019

Neural Models For Information Retrieval Without Labeled Data, Hamed Zamani

Doctoral Dissertations

Recent developments of machine learning models, and in particular deep neural networks, have yielded significant improvements on several computer vision, natural language processing, and speech recognition tasks. Progress with information retrieval (IR) tasks has been slower, however, due to the lack of large-scale training data as well as neural network models specifically designed for effective information retrieval. In this dissertation, we address these two issues by introducing task-specific neural network architectures for a set of IR tasks and proposing novel unsupervised or \emph{weakly supervised} solutions for training the models. The proposed learning solutions do not require labeled training data. Instead, …

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Joint Asymptotics For Smoothing Spline Semiparametric Nonlinear Models, Jiahui Yu Oct 2019

Joint Asymptotics For Smoothing Spline Semiparametric Nonlinear Models, Jiahui Yu

Doctoral Dissertations

We study the joint asymptotics of general smoothing spline semiparametric models in the settings of density estimation and regression. We provide a systematic framework which incorporates many existing models as special cases, and further allows for nonlinear relationships between the finite-dimensional Euclidean parameter and the infinite-dimensional functional parameter. For both density estimation and regression, we establish the local existence and uniqueness of the penalized likelihood estimators for our proposed models. In the density estimation setting, we prove joint consistency and obtain the rates of convergence of the joint estimator in an appropriate norm. The convergence rate of the parametric component …

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Response Retrieval In Information-Seeking Conversations, Liu Yang Oct 2019

Response Retrieval In Information-Seeking Conversations, Liu Yang

Doctoral Dissertations

The increasing popularity of mobile Internet has led to several crucial changes in the way that people use search engines compared with traditional Web search on desktops. On one hand, there is limited output bandwidth with the small screen sizes of most mobile devices. Mobile Internet users prefer direct answers on the search engine result page (SERP). On the other hand, voice-based / text-based conversational interfaces are becoming increasing popular as shown in the wide adoption of intelligent assistant services and devices such as Amazon Echo, Microsoft Cortana and Google Assistant around the world. These important changes have triggered several …

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Extreme Dynamics Of Nanomaterials Under High-Rate Mechanical Stimuli, Wanting Xie Oct 2019

Extreme Dynamics Of Nanomaterials Under High-Rate Mechanical Stimuli, Wanting Xie

Doctoral Dissertations

Nanomaterials demonstrate novel mechanical properties attributed to the extremely large interfacial area. At quasi-static rates, the interfacial interactions are crucial in mechanical behaviors, however, materials under extreme mechanical stimuli are rarely studied at nanoscale. With an advanced laser-induced projectile impact test, we perform supersonic impact of micro-projectiles on polymer films, multilayer graphene, carbon- based nanocomposites membranes as well as individual micro-fibers, to study the interface interactions in the high-rate regime, and develop a simplified model to characterize the ballistic performance of materials.

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Extracting And Representing Entities, Types, And Relations, Patrick Verga Oct 2019

Extracting And Representing Entities, Types, And Relations, Patrick Verga

Doctoral Dissertations

Making complex decisions in areas like science, government policy, finance, and clinical treatments all require integrating and reasoning over disparate data sources. While some decisions can be made from a single source of information, others require considering multiple pieces of evidence and how they relate to one another. Knowledge graphs (KGs) provide a natural approach for addressing this type of problem: they can serve as long-term stores of abstracted knowledge organized around concepts and their relationships, and can be populated from heterogeneous sources including databases and text. KGs can facilitate higher level reasoning, influence the interpretation of new data, and …

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Residual Stress Models For Large Eddy Simulation Of Stratified Turbulent Flows, Felipe Augusto Ventura De Bragança Alves Oct 2019

Residual Stress Models For Large Eddy Simulation Of Stratified Turbulent Flows, Felipe Augusto Ventura De Bragança Alves

Doctoral Dissertations

The residual stresses and scalar fluxes are required to close the momentum and scalar transport equations in simulations of turbulence that are not fully resolved in space. In stratified turbulence, the stress and fluxes are statistically anisotropic unless the smallest resolved length scale is smaller than the Ozmidov scale and the buoyancy Reynolds number is sufficiently high for there to exist a range of scales that is statistically isotropic. In this work, a tensorial basis set is derived analytically that potentially contains sufficient information about the anisotropic interaction between resolved and residual scales. The residual stress tensor is evaluated by …

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Efficient Self-Supervised Deep Sensorimotor Learning In Robotics, Takeshi Takahashi Oct 2019

Efficient Self-Supervised Deep Sensorimotor Learning In Robotics, Takeshi Takahashi

Doctoral Dissertations

Deep learning has been successful in a variety of applications, such as object recognition, video games, and machine translation. Deep neural networks can automatically learn important features given large training datasets. However, the success of deep learning in robotic systems in the real world is still limited mainly because obtaining large datasets and labeling are costly. As a result, much of the successful work in deep learning has been limited to domains where large datasets are readily available or easily collected. To address this issue, I propose a framework for acquiring re-usable skills efficiently combining intrinsic motivation and the control …

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Machine Learning Models For Efficient And Robust Natural Language Processing, Emma Strubell Oct 2019

Machine Learning Models For Efficient And Robust Natural Language Processing, Emma Strubell

Doctoral Dissertations

Natural language processing (NLP) has come of age. For example, semantic role labeling (SRL), which automatically annotates sentences with a labeled graph representing who did what to whom, has in the past ten years seen nearly 40% reduction in error, bringing it to useful accuracy. As a result, a myriad of practitioners now want to deploy NLP systems on billions of documents across many domains. However, state-of-the-art NLP systems are typically not optimized for cross-domain robustness nor computational efficiency. In this dissertation I develop machine learning methods to facilitate fast and robust inference across many common NLP tasks. First, …

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Protein Detection And Structural Characterization By Mass Spectrometry Using Supramolecular Assemblies And Small Molecules, Bo Zhao Oct 2019

Protein Detection And Structural Characterization By Mass Spectrometry Using Supramolecular Assemblies And Small Molecules, Bo Zhao

Doctoral Dissertations

Mass spectrometry (MS) has played an increasingly prominent role in proteomics and structure biology because it shows superior capabilities in identification, quantification and structural characterization of proteins. To realize its full potential in protein analysis, significant progress has been made in developing innovative techniques and reagents that can couple to MS detection. This dissertation demonstrates the use of polymeric supramolecular assemblies for enhanced protein detection in complex biological mixtures by MS. An amphiphilic random co-polymer scaffold is developed to form functional supramolecular assemblies for protein/ peptide enrichment. The influences of charge density and functional group pKa on host-guest interactions …

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Top-Down And Bottom-Up Fabrication Of Key Components In Miniature Energy Storage Devices, Wenhao Li Oct 2019

Top-Down And Bottom-Up Fabrication Of Key Components In Miniature Energy Storage Devices, Wenhao Li

Doctoral Dissertations

The advent of miniature electronic devices demands power sources of commensurate form factors. This spurs the research of micro energy storage devices, e.g., 3D microbatteries. A 3D microbattery contains nonplanar microelectrodes with high aspect ratio and high surface area, separated by a nanoscale electrolyte. The device takes up a total volume as small as 10 mm3, allowing it to serve on a chip and to provide power in-situ. The marriage of nanotechnology and electrochemical energy storage makes microbattery research a fascinating field with both scientific excitement and application prospect. However, successful fabrication of well-functioned key components …

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Characterization Of The Anomalous Ph Of Aqueous Nanoemulsions, Kieran P. Ramos Oct 2019

Characterization Of The Anomalous Ph Of Aqueous Nanoemulsions, Kieran P. Ramos

Doctoral Dissertations

Aqueous water-in-oil nanoemulsions have emerged as a versatile tool for use in microfluidics, drug delivery, single-molecule measurements, and other research. Nanoemulsions are often prepared with perfluorocarbons which are remarkably biocompatbile due to their stability, low surface tension, lipophobicity, and hydrophobicity. Therefore it is often assumed that droplet contents are unperturbed by the perfluorinated surface. However, in microemulsions, which are similar to nanoemulsions, it is known that either the pH of the aqueous phase or the ionization constants of encapsulated molecules are different from bulk solution. There is also recent evidence of low pH in perfluorinated aqueous nanoemulsions. The current underlying …

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Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee Oct 2019

Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee

Doctoral Dissertations

Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them. In this thesis, I argue that the IoT …

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Providing Molecular Insight For Understanding Anion Exchange Membrane Conductivity, Michael Kwasny Oct 2019

Providing Molecular Insight For Understanding Anion Exchange Membrane Conductivity, Michael Kwasny

Doctoral Dissertations

Anion exchange membranes (AEMs) are notorious for having both low alkaline stability and poor ion conductivity in fuel cell operation conditions, with solutions to these two challenges often being developed independent of each other. The chemical instability of an AEM is viewed through degradation of the polymer backbone and the cationic species and improving a material’s stability is approached by altering the polymer backbone, the cation, or both. On the other hand, poor ion conductivity is typically addressed by modifying bulk membrane properties such as increasing the ion exchange capacity (IEC), changing the morphology, or increasing the water uptake. These …

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Observational Studies Of Fragmentation In Molecular Clouds, Riwaj Pokhrel Oct 2019

Observational Studies Of Fragmentation In Molecular Clouds, Riwaj Pokhrel

Doctoral Dissertations

In this dissertation, I explore fragmentation physics in multiple scales in nearby molecular clouds and discuss some implications of fragmentation for cloud structure formation and star formation, primarily by analyzing multi-wavelength observations of dust emission. First, I tested the complete thermal and combined thermal and nonthermal support mechanisms that balance gravitational contraction at multiple scales in the Perseus molecular cloud. I found that the observed multiscale structures in Perseus are consistent with an inefficient thermal Jeans fragmentation, where the Jeans efficiency increases from the largest scale ($\gtrsim$10s of pc) to the smallest scale ($\sim$10s of AU). Next, I studied the …

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Energy-Aware Algorithms For Greening Internet-Scale Distributed Systems Using Renewables, Vani Gupta Oct 2019

Energy-Aware Algorithms For Greening Internet-Scale Distributed Systems Using Renewables, Vani Gupta

Doctoral Dissertations

Internet-scale Distributed Systems (IDSs) are large distributed systems that are comprised of hundreds of thousands of servers located in hundreds of data centers around the world. A canonical example of an IDS is a content delivery network (CDN) that delivers content to users from a large global deployment of servers around the world. IDSs consume large amounts of energy and their energy requirements are projected to increase significantly in the future. With carbon emissions from data centers increasing every year, use of renewables to power data centers is critical for the sustainability of data centers and for the environment. In …

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The Role Of Agulhas Leakage In Pliocene Climate Change, Neil Patel Oct 2019

The Role Of Agulhas Leakage In Pliocene Climate Change, Neil Patel

Doctoral Dissertations

The late Pliocene (2.6-3.3 Myr) was an epoch of gradual cooling, with expanding Antarctic ice sheets and sea ice preceding a general Northern Hemisphere glaciation. A decline in the strength of the Atlantic Meridional Circulation (AMOC) in the late Pliocene may have decreased Southern Hemisphere oceanic heat transport into the Northern Hemisphere; pre-conditioning it for glaciation. A common explanation for a weakening of the AMOC in paleoclimate is freshwater forcing into the North Atlantic. In this thesis, I posit that a northward shift in the Southern Hemisphere westerlies in the late Pliocene, due to an expanded Antarctic ice sheet, weakens …

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Modeling And Simulation Of Driven Nanopatterning Of Bulk-Material And Thin-Film Surfaces, Ashish Kumar Oct 2019

Modeling And Simulation Of Driven Nanopatterning Of Bulk-Material And Thin-Film Surfaces, Ashish Kumar

Doctoral Dissertations

Material nanostructures such as nanowires, quantum dots, and nanorings have a wide variety of applications in electronic and photonic devices among numerous others. Assembling uniformly arranged and consistently sized nanostructure patterns on solid material surfaces is a major challenge for nanotechnology. This dissertation focuses on developing predictive models capable of simulation and analysis of such nanopattern formation on bulk material and strained thin film surfaces. Single-layer atomic clusters (islands) of sizes larger than a critical size on crystalline conducting substrates undergo morphological instabilities when driven by an externally applied electric field or thermal gradient. We have conducted a systematic and …

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Amorphous-Crystalline Brush Block Copolymers: Phase Behavior, Rheology And Composite Design, Gayathri Kopanati Oct 2019

Amorphous-Crystalline Brush Block Copolymers: Phase Behavior, Rheology And Composite Design, Gayathri Kopanati

Doctoral Dissertations

Bottlebrush block copolymers are polymers with chemically distinct polymer side chains grafted onto a common backbone. The unique architecture induced properties make these materials attractive for applications such as photonic materials, stimuli responsive actuators and drug delivery vehicles to name a few. This dissertation primarily investigates the phase transitions and rheological behavior of amorphous-crystalline bottlebrush brush block copolymers and their composites. The temperature induced phase behavior is investigated using time resolved synchrotron X-ray source. Irrespective of volume fraction and backbone length, the samples display strong segregation even at high temperatures (200 °C) and there is no accessible order-disorder transition in …

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Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh Oct 2019

Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh

Doctoral Dissertations

Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …

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Polymeric Impulsive Actuation Mechanisms: Development, Characterization, And Modeling, Yongjin Kim Oct 2019

Polymeric Impulsive Actuation Mechanisms: Development, Characterization, And Modeling, Yongjin Kim

Doctoral Dissertations

Recent advances in the field of biomedical and life-sciences are increasingly demanding more life-like actuation with higher degrees of freedom in motion at small scales. Many researchers have developed various solutions to satisfy these emerging requirements. In many cases, new solutions are made possible with the development of novel polymeric actuators. Advances in polymeric actuation not only addressed problems concerning low degree of freedom in motion, large system size, and bio-incompatibility associated with conventional actuators, but also led to the discovery of novel applications, which were previously unattainable with conventional engineered systems. This dissertation focuses on developing novel actuation mechanisms …

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The Impact Of Protostellar Feedback On Astrochemistry, Brandt Gaches Oct 2019

The Impact Of Protostellar Feedback On Astrochemistry, Brandt Gaches

Doctoral Dissertations

Star formation is the lynch pin that lies in between the scales of galaxy and planet formation. Observational studies of molecular clouds, the sites of star formation, primarly use molecular line emission, providing dynamical and chemical information. Two of the key parameters of astrochemical models are far-ultraviolet (FUV) flux and the cosmic ray ionization rate. We use analytic accretion histories to predict the bolometric and FUV luminosities of protostar clusters and compare different histories with observed bolometric luminosities. We find that the Tapered Turbulent Core model best represents the observed luminosities and their dispersion. We extend the models to calculate …

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Model-Form Uncertainty Quantification For Predictive Probabilistic Graphical Models, Jinchao Feng Oct 2019

Model-Form Uncertainty Quantification For Predictive Probabilistic Graphical Models, Jinchao Feng

Doctoral Dissertations

In this thesis, we focus on Uncertainty Quantification and Sensitivity Analysis, which can provide performance guarantees for predictive models built with both aleatoric and epistemic uncertainties, as well as data, and identify which components in a model have the most influence on predictions of our quantities of interest. In the first part (Chapter 2), we propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, …

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Designing Ion-Containing Polymers With Controlled Structure And Dynamics, Joshua Enokida Oct 2019

Designing Ion-Containing Polymers With Controlled Structure And Dynamics, Joshua Enokida

Doctoral Dissertations

Ion-containing polymers are a unique class of materials for which strong electrostatic interactions dictate physical properties. By altering molecular parameters, such as the backbone chemical structure, the ion content, and the ion-pair identity, the structure and dynamics of these polymers can be altered. Further investigation of the molecular parameters that govern their structure-property relationships is critical for the future development of these polymeric materials. Particularly, the incorporation of ammonium-based counterions into these polymers offers a facile method to tune their electrostatic interactions and hydrophobicity. Applying this concept, a bulky dimethyloctylammonium (DMOA) counterion was used to modify the organic solubility of …

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Comparison Of Three Dimensional Selfdual Representations By Faltings-Serre Method, Lian Duan Oct 2019

Comparison Of Three Dimensional Selfdual Representations By Faltings-Serre Method, Lian Duan

Doctoral Dissertations

In this thesis, we prove that, a selfdual 3-dimensional Galois representation constructed by van Geemen and Top is isomorphic to a quadratic twist of the symmetric square of the Tate module of an elliptic curve. This is an application of our refinement of the Faltings-Serre method to 3-dimensional Galois representations with ground field not equal to Q. The proof makes use of the Faltings-Serre method, $\ell$-adic Lie algebra, and Burnside groups.

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