Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item Phonon Transport and Nonequilibrium Kinetics with Stimulation Modeling in Molecular Crystals(2024) Liu, Zhiyu; Chung, Peter W.; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)An important family of materials known as molecular crystals has been used extensively in fields such as organic semiconductors, energy, optoelectronics, and batteries. Due to their periodic crystal structure, phonons are the predominant heat and energy carriers. Phonons and their transport behaviors are crucial to the performance of semiconductors, the figure of merit of thermoelectrics, shock-induced properties of molecular crystals, and light-matter interactions of materials. Recent decades have seen significant advancements in the understanding of the phonon transport behaviors in inorganic crystals. However, a comprehensive understanding of phonon properties in molecular crystals is still lacking. While various theoretical models and computational simulations have been developed to study vibrational energy transfer in molecular crystals and to correlate vibrational structure with the stability of materials, these approaches often suffer from limitations. Many of these studies either neglect anharmonic scattering entirely or rely on simplified representations of phonon scattering. In this dissertation, we focus on investigating the phonon transport and nonequilibrium kinetics in molecular crystals. In the first work, we study the harmonic phonon properties of cellulose Iβ using tapered reactive force fields (ReaxFF). While geometry optimization with the original ReaxFF potential often results in structures with negative eigenvalues, indicating structural instability, the modified potential with a tapering function yields structures with no associated negative eigenvalues. Three ReaxFF parameterizations are evaluated by comparing lattice properties, elastic constants, phonon dispersion, temperature-dependent entropy, and heat capacity with experimental results from the literature. In the second study, we study the phonon transport behavior of Si, Cs2PbI2Cl2, cellulose Iβ, and α-RDX by calculating the thermal conductivity using different thermal transport models including the Phonon gas model, Cahill-Watson-Pohl, and the Allen-Feldman model and the Wigner formulation. By comparing the calculated thermal conductivity with experimental values, we highlight the significant contributions of wave-like heat carriers in cellulose Iβ and α-RDX. We show how different phonon properties influence particle-like and wave-like behavior in various materials and reveal unusual mechanisms present in molecular crystals. Lastly, we investigate nonequilibrium phonon kinetics resulting from direct vibrational excitations by employing the phonon Boltzmann transport equations. The results of our mid-IR pump-probe spectroscopy simulations align closely with experimental data from the literature. Additionally, by exciting different phonon modes at varying frequencies, we uncover distinct stages and pathways of vibrational energy transfer. To gain insights into the decomposition mechanism of RDX under excitation, we further calculate the bond activities of the N-N and N-O bonds, identifying possible stimuli that could trigger bond cleavage.Item MEASURING AND MODELING ELECTROMAGNETIC FORCES THAT INFLUENCE GRANULAR BEHAVIOR(2024) Pett, Charles Thomas; Hartzell, Christine M; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)On the surfaces of small, airless planetary bodies, forces other than gravity, such as cohesive, magnetic and electrostatic forces, may dominate the behavior of regolith. Yet, the magnitude of these forces remains uncertain, as well as the link between grain-scale and bulk-scale physics. In this work, techniques for measuring and modeling electromagnetic forces that influence granular behavior are developed. We discuss an experimental method for measuring interparticle cohesion by breaking cohesive bonds between grains with electrostatic forces. The centroid positions of the lofted grains at the moment of detachment are imaged in order to numerically calculate initial accelerations to solve for cohesion. We propose the design of a payload that would be deployed on the Moon or an asteroid and use an electrically biased plate to induce electrostatic dust lofting and measure interparticle cohesion in situ. We would call the system \textbf{Small--FORCES} because it would be able to image \textbf{Small} \textbf{F}orces \textbf{O}ptically \textbf{R}esolved for \textbf{C}ohesion \textbf{E}stimation via \textbf{E}lectrostatic \textbf{S}eparation. We numerically integrate Poisson's equation and develop a model for the potential distribution of a photoelectron sheath as a function of distance from surfaces. We use this model to gauge the extent to which the solar wind will perturb the Small-FORCES electric field that is used to loft charged regolith inside the sheath and obtain suitable trajectories for imaging lofted regolith that will be used to measure cohesion. We then derive a formula to quantify the maximum region of our system's electric field that we predict can be shielded from the ambient solar wind, which depends on system dimensions and applied voltage. In another experiment, we investigated the affect of magnetic cohesion on the avalanching behavior of magnetic grains. We will introduce an instrument and novel method for characterizing the bulk magnetic susceptibility of granular mixtures by submerging an inductor coil in a bed of metallic beads. In prior works, the magnetic force on grains was calculated based on the magnetic susceptibility of a single grain, but our coil uniquely quantifies effects from void spaces and demagnetization in the bulk. Compared to both a commercial Terraplus Inc. KT-10 meter and theoretical approximations, we report similar trends in susceptibility values measured as a function of mass of ferromagnetic material per volume. We conclude the talk with a discussion on a conductive model we developed to simulate surfaces other than dielectrics in the solar wind. We use a 2D grid-free treecode to enable complex surface geometries that would be computationally intensive for traditional PIC codes. Instead of using the capacitance matrix method to calculate the induced surface charge magnitudes, we discretized the conductor surface into point charges and allow them to have Coulomb interactions with the external plasma particles. The linear system used to explicitly solve for the induced surface charge magnitudes couples the interaction between surface charges and plasma particles self-consistently via the conductive boundary condition. The model has been validated thus far with image charge theory.Item Understanding the effect of fabrication conditions on the structural, electrical, and mechanical properties of composite materials containing carbon fillers(2022) Morales, Madeline Antonia; Salamanca-Riba, Lourdes G; Material Science and Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Carbon structures are commonly used as the reinforcement phase in composite materials toimprove the electrical, mechanical, and/or thermal properties of the matrix material. The structural diversity of carbon in its various forms (graphene, carbon nanotubes, graphite fibers, for example) makes it a useful reinforcement phase, as the properties of the composite material can be tailored for a specific application depending on the structure and properties of the carbon structure used. In this work, the incorporation of graphene/graphitic carbon into an aluminum metal matrix by an electrocharging assisted process (EAP) was investigated to create a composite material with enhanced electrical conductivity and yield strength. The increased electrical conductivity makes the composite suitable for application in more efficient power transmission lines. The increased strength makes it useful as a lightweight structural material in aerospace applications. The EAP involves applying a direct current to a mixture of molten aluminum and activated carbon to induce the crystallization of graphitic sheets/ribbons that extend throughout the matrix. The effect of processing conditions (current density, in particular) on the graphitic carbon structure, electrical properties, and mechanical properties of the composite material was investigated. The effect of porosity/voids and oxide formation was discussed with respect to the measured properties, and updates to the EAP system were made to mitigate their detrimental effects. It was found that the application of current results in some increase in graphitic carbon crystallite size calculated from Raman spectra, but many areas show the same crystallite size as the activated carbon starting material. It is likely that the current density used during processing was too low to see significant crystallization of graphitic carbon. There was no increase in electrical conductivity compared to a baseline sample with no added carbon, most likely due to porosity/voids in the samples. The mechanical characterization results indicated that the graphitic carbon clusters formed by the process did not act as an effective reinforcement phase, with no improvement in hardness and a decrease in elastic modulus measured by nanoindentation. The decreased elastic modulus was a result of compliant carbon clusters and porosity in the covetic samples. The porosity/voids were not entirely eliminated by the updates to the system, thus the electrical conductivity still did not improve. Additionally, a multifunctional composite structure consisting of a carbon-fiber reinforced polymer (CFRP) laminate with added copper mesh layers was investigated for use in aerospace applications as a structural and electromagnetic interference (EMI) shielding component. The CFRP provides primarily a structural function, while the copper mesh layers were added to increase EMI shielding effectiveness (SE). Nanoindentation was used to study the interfacial mechanical properties of the fiber/polymer and Cu/polymer interfaces, as the interfacial strength dictates the overall mechanical performance of the composite. Further, a finite element model of EMI SE was made to predict SE in the radiofrequency to microwave range for different geometry and configurations of the multifunctional composite structure. The model was used to help determine the optimum design of the multifunctional composite structure for effective shielding of EM radiation. It was found from nanoindentation near the fiber/polymer and Cu/polymer interfaces that the carbon fibers act as an effective reinforcement phase with hardness in the matrix increasing in the interphase region near the carbon fibers due to strong interfacial adhesion. In contrast, the Cu/polymer interface did not exhibit an increase in hardness, indicating poor interfacial adhesion. The EMI SE model indicated that the combination of CFRP layers, which primarily shields EMI by absorption, and Cu mesh, which predominantly shields by reflection, provided adequate SE over a wider frequency range than the individual components alone. Further, it was found that the SE of the CFRP layers were improved by including multiple plies with different relative fiber orientations.Item Electromagnetic Characterization of Misaligned Serpentine Waveguide Structures in Traveling-Wave Tubes at Microwave Frequencies(2022) Kuhn, Kyle; Antonsen, Jr., Thomas M; Beaudoin, Brian L; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Modern-day millimeter and microwave source technology has advanced considerably over the past century, but to meet the defense industry’s demand for high power and large bandwidth, vacuum electronic devices (VEDs) are still the ideal candidate to fulfill such requirements as opposed to their solid-state semiconductor counterparts. Of the numerous VEDs available, the traveling-wave tube (TWT) amplifier provides novel solutions in areas where size, weight, and power (SWaP), and bandwidth are of great importance such as on satellites and in electronic warfare applications. The advancement in computer-aided design (CAD) and simulation has allowed for increasingly complicated device configurations to be designed with ease. Instead, challenges arise in fabrication as extremely tight manufacturing tolerances on the order of micron to submicron levels are necessary due to the very short wavelengths in the mm-wave and sub-mm-wave regimes. Without this level of manufacturing precision, VEDs will not operate at optimal levels in power, bandwidth, and efficiency. We present a serpentine waveguide (SWG) design to be used as the slow-wave structure (SWS) in a TWT amplifier. Manufacturing techniques for the design are discussed, and a detailed study into how one-dimensional and two dimensional misalignments in the circuit’s half-plane affect the radio frequency (RF) signal that propagates through the device. Figures of merit include the device’s reflected power, or S11, the transmitted power through the SWG, or S21, the device’s cutoff frequency, and the SWG’s dispersion curves. Computer simulations using Ansys’s High Frequency Structure Simulator, or HFSS, and cold test laboratory measurements for aligned and misaligned Ka-band (26.5 GHz – 40 GHz) SWG circuits are presented. Upon completing a thorough RF characterization of the Ka-band device, efforts will shift focus to designing a SWG circuit for a W-band (75 GHz – 110 GHz) TWT amplifier prototype.Item BUILDING KINETIC MODELS FOR COMPLEX SYSTEMS WITH ARBITRARY MEMORIES(2022) Tsai, Sun-Ting; Tiwary, Pratyush; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Analyzing time series from complex dynamical systems in nature is a common yet challenging task in scientific computation since these time series are usually high-dimensional. To apply our physics intuitions to these dynamical systems often requires projecting these time series to certain low-dimensional degrees of freedom, which often introduces complicated memory effect. A simplest and classic example can be a 2-dimensional coupled differential equation. When one only looks at one of the Cartesian coordinates, one loses the predictability to predict what will happen next given the current 1-dimensional coordinate. The well-known solution is to describe the solution using the eigenvector, and the coupled equation is decoupled into a constant and a 1-dimensional memoryless equation. However, it can be imagined in a more complicated system we may have to look back to more time steps in the past, and it can be impossible to obtain a simple 1-dimensional eigenvector. In this work, we examine such memory effect within time series generated from Langevin dynamics, Molecular Dynamics (MD) simulations, and some experimental time series. We also develop computational methods to minimize and model such memory effects using statistical mechanics and machine learning. In recent years, MD simulation has become a powerful tool to model complex molecular dynamics in physics, chemistry, material science, biology, and many other fields. However, rare events such as droplet formation, nucleation, and protein conformational changes are hard to sample using MD simulations since they happen on the timescales far away from what all-atom MD simulation can reach. This makes MD simulation less useful for studying the mechanism of rare event kinetics. Therefore, it is a common practice to perform enhanced sampling techniques to help sample rare events, which requires performing dimensionality reduction from atomic coordinates to a low-dimensional representation that has a minimal memory effect. In the first part of this study, we focus on reducing the memory effect by capturing slow degrees of freedom using a set of low-dimensional reaction coordinates (RCs). The RCs are a low-dimensional surrogate of the eigenvector in the example of coupled equations. When describing the system using RCs, other dimensions become constant except fast randomly fluctuating noise. These RCs can then be used to help reproducing correct kinetic connectivity between metastable states using enhanced sampling methods such as metadynamics. We demonstrate the utility of our method by applying them to the droplet formation from the gaseous phase of Lennard-Jones particles and the conformational changes of a small peptide Ace-Ala3-Nme. The second part of the study aims at modeling another type of memory coming from intrinsic long-term dependency induced by ignored fast degrees of freedom wherein we utilize one of the fundamental machine learning techniques called the recurrent neural network to model non-Markovianity within time-series generated from MD simulations. This method has been shown to work not only on the molecular model of alanine dipeptide but also on experimental time series taken from single-molecule force spectroscopy. At the end of this second part, we also improve this method to extrapolate physics that the neural network had never seen in the training dataset by incorporating static or dynamical constraints on the path ensemble it generates.Item Emergent behaviors in adaptive dynamical networks with applications to biological and social systems(2021) Alexander, Brandon Marc; Girvan, Michelle; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this thesis, we consider three network-based systems, focusing on emergent behaviors resulting from adaptive dynamical features. In our first investigation, we create a model for gene regulatory networks in which the network topology evolves over time to avoid instability of the regulatory dynamics. We consider and compare different rules of competitive edge addition that use topological and dynamical information from the network to determine how new network links are added. We find that aiming to keep connected components small is more effective at preventing widespread network failure than limiting the connections of genes with high sensitivity (i.e., potential for high variability across conditions). Finally, we compare our results to real data from several species and find a trend toward disassortativity over evolutionary time that is similar to our model for structure-based selection. In our second investigation, we introduce a bidirectional coupling between a phase synchronization model and a cascade model to produce our `sync-contagion' model. The sync-contagion model is well-suited to describe a system in which a contagious signal alerts individuals to realign their orientations, where `orientation' can be in the literal sense (such as a school of fish escaping the threat of a predator) or a more abstract sense (such as a `political orientation' that changes in response to a hot topic). We find that success in realigning the population towards some desired target orientation depends on the relative strengths of contagion spread and synchronization coupling. In our third and final investigation, we attempt to forecast the complex infection dynamics of the COVID-19 pandemic through a data-driven reservoir computing approach. We focus our attention on forecasting case numbers in the United States at the national and state levels. Despite producing adequate short-term predictions, we find that a simple reservoir computing approach does not perform significantly better than a linear extrapolation. The biggest challenge is the lack of data quantity normally required for machine learning success. We discuss methods to augment our limited data, such as through a `library-based' method or a hybrid modeling approach.Item Simulating many-body quantum spin models with trapped ions(2021) Kyprianidis, Antonis; Monroe, Christopher R; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Richard Feynman in 1981 suggested using a quantum machine to simulate quantum mechanics.Peter Shor in 1994 showed that a quantum computer could factor numbers much more efficiently than a conventional one. Since then, the explosion of the quantum information field is attesting to how motivation and funding work miracles. Research labs in the field are multiplying, commercial companies manufacturing prototypes are proliferating, undergraduate Physics curricula incorporate more than one courses in aspects of quantum information, quantum advantage over classical computers has been claimed, and the United States and European Union will be spending more than \$$10^9$ each in quantum information over the next few years. Naturally, this expansion has led to diversification of the devices being developed. The quantum information systems that cannot simulate an arbitrary evolution, but are specialized in a specific set of Hamiltonians, are called quantum \emph{simulators}. They enjoy the luxury of being able to surpass computational abilities of classical computers \emph{right now}, at the expense of only doing so for a narrow type of problem. Among those systems, ions trapped in vacuum by electric fields and manipulated with light have proved to be a leading platform in emulating quantum magnetism models. In this thesis I present trapped-ion experiments realizing a prethermal discrete time crystal. This exotic phase occurs in non-equilibrium matter subject to an external periodic drive. Normally, the ensuing Floquet heating maximizes the system entropy, leaving us with a trivial, infinite-temperature state. However, we are able to parametrically slow down this heating by tuning the drive frequency. During the time window of slow thermalization, we define an order parameter and observe two different regimes, based on whether it spontaneously breaks the discrete time translation symmetry of the drive or it preserves it. Furthermore, I demonstrate a simple model of electric field noise classically heating an ion in an anharmonic confining potential. As ion traps shrink, this kind of noise may become more significant. And finally, I discuss a handful of error sources. As quantum simulation experiments progress to more qubits and complicated sequences, accounting for system imperfections is becoming an integral part of the process.Item Scaling Quantum Computers with Long Chains of Trapped Ions(2021) Egan, Laird Nicholas; Monroe, Christopher; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Quantum computers promise to solve models of important physical processes, optimize complex cost functions, and challenge cryptography in ways that are intractable using current computers. In order to achieve these promises, quantum computers must both increase in size and decrease error rates. To increase the system size, we report on the design, construction, and operation of an integrated trapped ion quantum computer consisting of a chain of 15 171Yb+ ions with all-to-all connectivity and high-fidelity gate operations. In the process, we identify a physical mechanism that adversely affects gate fidelity in long ion chains. Residual heating of the ions from noisy electric fields creates decoherence due to the weak confinement of the ions transverse to a focused addressing laser. We demonstrate this effect in chains of up to 25 ions and present a model that accurately describes the observed decoherence. To mitigate this noise source, we first propose a new sympathetic cooling scheme to periodically re-cool the ions throughout a quantum circuit, and then demonstrate its capability in a proof-of-concept experiment. One path to suppress error rates in quantum computers is through quantum error correction schemes that combine multiple physical qubits into logical qubits that robustly store information within an entangled state. These extra degrees of freedom enable the detection and correction of errors. Fault-tolerant circuits contain the spread of errors while operating the logical qubit and are essential for realizing error suppression in practice. We demonstrate fault-tolerant preparation, measurement, rotation, and stabilizer measurement of a distance-3 Bacon-Shor logical qubit in our quantum computer. The result is an encoded logical qubit with error rates lower than the error of the entangling operations required to operate it.Item An Integrated Photonic Platform For Quantum Information Processing(2021) Dutta, Subhojit; Waks, Edo EW; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Quantum photonics provides a powerful toolbox with vast applications ranging from quantum simulation, photonic information processing, all optical universal quantum computation, secure quantum internet as well as quantum enhanced sensing. Many of these applications require the integration of several complex optical elements and material systems which pose a challenge to scalability. It is essential to integrate linear and non-linear photonics on a chip to tackle this issue leading to more compact, high bandwidth devices. In this thesis we demonstrate a pathway to achieving several components in the quantum photonic toolbox on the same integrated photonic platform. We focus particularly on two of the more nontrivial components, a single photon source and an integrated quantum light-matter interface. We address the problem of a scalable, chip integrated, fast single photon source, by using atomically thin layers of 2D materials interfaced with plasmonic waveguides. We further embark on the challenge of creating a new material system by integrating rare earth ions with the emerging commercial platform of thin film lithium niobate on insulator. Rare earth ions have found widespread use in classical and quantum information processing. However, these are traditionally doped in bulk crystals which hinder their scalability. We demonstrate an integrated photonic interface for rare earth ions in thin film lithium niobate that preserves the optical and coherence properties of the ions. This combination of rare earth ions with the chip-scale active interface of thin film lithium niobate opens a plethora of opportunities for compact optoelectronic devices. As an immediate application we demonstrate an integrated optical quantum memory with a rare earth atomic ensemble in the thin film. The new light matter interface in thin film lithium niobate acts as a key enabler in an already rich optical platform representing a significant advancement in the field of integrated quantum photonics.Item Study and Mitigation of Transverse Resonances with Space Charge Effects at the University of Maryland Electron Ring(2020) Dovlatyan, Levon; Antonsen, Thomas M; Beaudoin, Brian L; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Research at the intensity frontier of particle physics has led to the consideration of accelerators that push the limits on achievable beam intensities. At high beam intensities Coulomb interactions between charged particles generate a space charge force that complicates beam dynamics. The space charge force can lead to a range of nonlinear, intensity- limiting phenomena that result in degraded beam quality and current loss. This is the central issue faced by the next generation of high-intensity particle accelerators. An improved understanding of the interaction of the space charge forces and transverse particle motion will help researchers better design around these limiting issues. Furthermore, any scheme able to mitigate the impacts of such destructive interactions for space charge dominated beams would help alleviate a significant limitation in reaching higher beam intensities. Experimental work addressing these issues is presented using the University of Maryland Electron Ring (UMER). This dissertation presents experimental studies of space charge dominated beams, and in particular the resonant interaction between the transverse motion of the beam and the periodic perturbations that occur due to the focusing elements in a circular ring. These interactions are characterized in terms of the tune shifts, Qx and Qy, that are the number of transverse oscillations (in and out of the plane of the ring) per trip around the ring. Resonances occur for both integer and half-integer values of tune shift. Particle tune measurement tools and resonance detection techniques are developed for use in the experiment. Results show no shift for either the integer (Qx = 7.0, Qy = 7.0) or half-integer (Qx = 6.5, Qy = 6.5) resonance bands as a function of space charge. Accepted theory predicts only a shift in the half-integer resonance case. A second experiment testing the potential mitigation of transverse resonances through nonlinear detuning of particle orbits from resonance driving terms is also presented. The study included the design, simulation, and experimental test of a quasi-integrable accelerator lattice based on a single nonlinear octupole channel insert. Experiments measured a nonlinear amplitude dependent tune shift within the beam on the order of ∆Qx ≈ 0.02 and ∆Qy ≈ 0.03. The limited tolerances on accelerator steering prevented measuring any larger tune shifts.