Browsing by Subject "Dynamics"

Now showing 1 - 19 of 19

Component terminal dynamics in weakly and strongly interacting blends.
(2009-12) Ozair, Sehban N.
Miscible blend dynamics have been long been a subject of interest and are not as well understood as dynamics of homopolymer melts. Their anomalous behavior, such as time-temperature superposition failure, broadening of calorimetric glass transition, etc., makes these systems very intriguing and challenges our understanding of miscible blend dynamics. In this work we investigated temperature and composition dependence of two different, dynamically heterogeneous blend systems using rheology and forced Rayleigh scattering (FRS). The first blend investigated was a weakly interacting one comprising poly(ethylene oxide) (PEO) and poly(methyl methacrylate) (PMMA). Monomeric friction factors of PEO and PMMA were reported for a wide range of temperature and composition. PEO terminal dynamics were found to have strong composition dependence unlike that of PEO segmental dynamics previously reported. Also, PEO maintained its rapid relaxation mechanisms even in stiffer surroundings. The PEO hydroxyl end groups were found to have no significant impact on component chain dynamics. The FRS and rheology results agreed remarkably well for this system. The Lodge-McLeish model failed to describe the experimental results. In order to understand the role of hydrogen bonding on chain dynamics, a strongly interacting system of PEO/poly(vinyl phenol) (PVPh) was investigated using rheology. The blends consisted of a high molecular polymer tracer dispersed in low molecular weight matrix to extract relevant dynamic information from tracer contribution to material properties. Monomeric friction factors were reported for a wide temperature and composition range. Time-temperature superposition failure was observed in PEO tracer blends at high PVPh concentration. The shape of tracer relaxation spectra for PVPh tracer blends had a strong composition dependence while those for PEO tracer blends were independent of composition. The tracer contribution to blend viscosity had a strong temperature dependence at high PVPh composition. Across the composition range, single and narrow glass transitions were observed for these blends. PVPh chain conformations were investigated using SANS and contradictory conclusions were reached. Therefore, no conclusive remarks can be made regarding PVPh chain conformations in dilute solution.
Data-Driven and Physics-Aware Machine Learning Methods for Mechanical System Analysis
(2022-10) Fabro, Jacob
Modeling of complex dynamical systems is necessary to facilitate identification, prediction, and control of those system. Which in turn allows for safe, efficient, well-informed operation of those systems. Specifically, unexpected downtime of manufacturing equipment, Computer Numeric Controlled (CNC) machines for example, costs US manufacturers approximately $50 billion a year [5]. In order to reduce the unplanned downtime of such equipment, dynamic modeling of the operation of those machines should occur. Two methods of modeling the dynamic response of a CNC machining spindle are evaluated in this thesis. Firstly, a method to learn a data-driven model for damped coupled oscillators from a mixed-mode response signal using neural differential equations is proposed. The univariate time-series data of the impulse response is first resampled into a multi-variate time-delayed embedding. A singular value decomposition (SVD) is then applied to find the dominant orthogonal basis (oscillator modes). The decoupled modes are then modeled with parameterized neural differential equations. The unknown parameters can be learned from a segment of historical data. The proposed methodology is validated using impact testing data of an end mill in a machine tool spindle. The results demonstrate that the proposed method can effectively model damped coupled oscillators. Secondly, a general method to learn a data-driven frequency response function (FRF) is developed. The FRF provides an input-output model that describes the system dynamics. Learning the FRF of a mechanical system can facilitate system identification, adaptive control, and condition-based health monitoring. In this thesis, learning FRFs from operational data with a nonlinear regression approach is investigated. A multiple input, multiple output (MIMO) regression model with a learned nonlinear basis is proposed for FRF learning for run-time systems under dynamic steady state. The proposed method is tested and validated for dynamic cutting force estimation of machining spindles under various operating conditions. It is shown that the proposed method can predict dynamic cutting forces with high accuracy by using measured vibration signals. It is also demonstrated that the learned data-driven FRF can be easily applied with a few-shot learning scheme to machine tool spindles with different frequency responses when limited training samples are available.
Design, modeling, and control of a novel architecture for automatic transmission systems
(2013-06) Mallela, Virinchi
Automotive transmissions are required to efficiently transfer energy from the engine to the wheels. Automatic transmissions are one of the most widely used transmission systems in the United States. This transmission houses a hydraulic system which is used to actuate the clutch system to realize different gear ratios. Currently, these clutches are primarily controlled in open-loop using hydraulic valves in a physical embodiment designed specifically for a given transmission system in order to perform precise pressure and flow control. To meet the increasing demand for higher fuel economy, transmissions with greater number of gear ratios are being introduced. The hydraulic architecture is becoming increasingly complicated with more clutches and control elements. With the advancement of MEMS technology, the sensor-based direct feedback control of clutches becomes possible. This paper first analyzes the current architecture of transmission hydraulic system and then presents a new architecture for the feedback-based clutches. The proposed architecture is further validated through experiments using hardware-in-the-loop system.
Efficient Propulsion for Versatile Unmanned Aerial Vehicles: Studies in Mechanics and Control
(2021-02) Henderson, Travis
This thesis presents a control algorithm for significantly enhancing the available thrust and minimizing the required electrical power consumption of a Variable-Pitch Propulsion (VPP) system, where the VPP system is made up of a brushless DC motor and a variable-collective-pitch propeller with its own servo motor. The variable-collective-pitch propeller mechanism has received recent attention because of the mechanism’s capability to enhance thrust response bandwidth and propulsive efficiency compared to conventional Unmanned Aerial Vehicle (UAV) propulsion systems with rigid-geometry propellers; the mechanism has this capability due to a second mechanical degree of freedom in the propeller geometry, allowing the collective pitch angle of the propeller blades to vary according to actuation from a servo motor. When paired with a properly designed control algorithm, the motor speed and pitch angle can be tuned in real time to track prescribed thrust trajectories while satisfying some optimality condition. Motivation for research into highly efficient VPP propulsion systems is encouraged by the intense interest from private and public sectors in UAVs that are capable of Vertical TakeOff and Landing (VTOL); while generally capable of both fixed-wing and hovering flight, VTOL UAVs with rigid-geometry propellers often exhibit short flight time due to non-optimal propulsion system efficiency across-the-board. Prior research into power-minimizing control strategies for small VPP systems has been targeted at multi-rotor platforms and has thus made assumptions that limit variation in the speed of propeller inflow and in the magnitude of thrust, thus limiting the technology’s applicability to VTOL platforms. The control algorithm presented in this thesis is designed to accommodate for the wide range of air inflow speeds and thrust magnitudes through the following algorithm components: a linear feedback thrust controller with a nonlinear, adaptive feedforward thrust model derived from Blade Element Momentum propeller theory; an estimator to tune the thrust feedforward model parameters in real-time; and an Extremum Seeking algorithm for tracking the minimum-power control input configuration. Analysis of controller performance is discussed with reference to simulated and physical validation experiments.
Emergent 1/f noise in systems of oscillating nanomagnetic dots
(2016-08) Costanzi, Barry
The observation of noise signals with a $\frac{1}{f}$ power spectral density dependence on frequency \emph{f} is both ubiquitous in quantitative measurements across fields, and not entirely well understood. So-called ``$\frac{1}{f}$" spectra have been observed in systems spanning the realm of physics, and in other disciplines as well. Van der Ziel's model of $\frac{1}{f}$ noise as a composite of Lorentizian noise signals is the most widely accepted explanation for $\frac{1}{f}$, but experiments have for the most part only implicitly confirmed the result thus far. In this thesis, an explicit bottom-up approach to the Van der Ziel model is presented by combining random telegraph noise signals in square magnetic dots. Square dots made of the iron-nickel alloy Permalloy were fabricated to be 250 nm on a side and $\sim$ 10 nm thick. The configurational anisotropy of the dots is small enough to reduce energy barriers between adjacent magnetic states to approximately thermal energies through the application of an external field, causing two-state thermal hopping of the magnetization. This magnetization was measured through the anisotropic magnetoresistance of the dots. The random telegraph signals generate Lorentizan spectra when transformed to the frequency domain, and are shown to combine to form $\frac{1}{f}$ spectra when multiple dots are measured in series. The energy landscape of the dots is determined through easy-axis coercivity measurements, and the distribution of energy barriers predicts a range of applied fields where individual noise signals should combine to produce $\frac{1}{f}$ noise by the Van der Ziel model. Experiment shows good agreement with the predicted range of these ``noise fields" for two different series of samples with different coercivity distributions. Measurements of both individual dots and aggregate multi-dot signals show that the number of individual oscillating dots necessary to produce an aggregate $\frac{1}{f}$ signal is lower than might be expected, with $\frac{1}{f}$ observed in collections of fewer than ten oscillating dots, and in some cases as few as two. Additionally, while the statistics over multiple samples agree with the Van der Ziel model, individual collections of dots exhibiting $\frac{1}{f}$ noise can either vary signifcantly from the ideal Van der Ziel distribution, or defy the distribution description altogether when the number of dots becomes too few. This suggests that the Van der Ziel model is a sufficient but not necessary condition for observing $\frac{1}{f}$ noise in a collection of Lorentizan oscillators, and that the actual requirements to generate $\frac{1}{f}$ noise are much looser than Van der Ziel's. In systems with any type of distribution of Lorentizan signals, $\frac{1}{f}$ noise is likely due to combination of those signals. This result is relevant other systems exhibiting magnetic noise, as well as non-magnetic systems displaying both RTN and $\frac{1}{f}$ noise.
Evaluation of the E-TRAN Vehicle Propulsion Concept
(1994-01) Hennessey, Michael P.; Donath, Max
The viability of the patented E-TRAN electric roadway and vehicle concept was examined from an engineering systems point of view. Specific recommendations are made regarding the end-usage and development of the propulsion concept. Based on this study, two research areas were identified and investigated in more detail: (a) quantify the auxiliary power needs due to power input discontinuities and (b) the dynamic effects of road pantograph bounce. Auxiliary power needs arise because of power input discontinuities, either due to: (1) power strip segment failures, (2) lane changing, and/or (3) E-TRAN grid discontinuities, which includes getting the vehicle to and from the grid. Simulation results indicate that power strip segment failures will have the least effect on system performance. E-TRAN grid discontinuities will have serious effects on the system while the effects of lane changing will affect performance at a level in between the other two. The dynamic effects of a road pantograph in contact with a road mounted power strip was also studied, first using simulated models and then verified by experiment. From a mechanical point of view, key issues that affect the design include friction, wear and dynamic bounce effects. Since good correspondence was achieved between the experimentally measured and simulated support forces and pantograph angular displacement, the models can be used for future design analysis.
Excited state dynamics of metalloporphyrins utilized in optoelectronic devices
(2013-08) Hinke, Jonathan Arthur
Energy consumption in the world is currently dominated by fossil fuels (85%) which include coal, gas, and oil while photovoltaics constitute a small portion (0.1%). The hotovoltaic market is primarily comprised of silicon based photovoltaics which are currently unable to compete with fossil fuels in cost per kilowatt hour. However, emerging organic photovoltaics (OPVs) have shown potential to be surpass silicon based photovoltaics and be cost competitive with fossil fuels. One of the limitations in OPVs is the short diffusion length (10 nm) relative to the absorbing layer thickness (100-200 nm). Porphyrins, of which chlorophylls are derivatives, remain at the forefront of OPV investigation due to their success in natural photosynthesis and potential in photovoltaic devices. Furthermore, platinum octaethyl porphyrin (PtOEP) has been estimated to have a diusion length between 18-30 nm and long triplet lifetime (100 microsecondss). This long diffusion length indicates that platinum porphyrins are able to efficiently funnel excitons to the interface, showing promise as suitable donor materials. Other porphyrins, such as nickel, palladium, tin, and indium show similar properties including strong absorption, enhanced excited state lifetimes, and charge separated states. This thesis investigates the excited state properties of porphyrin materials. Ultrafast pump probe spectroscopy allows for investigation of excited state dynamics including intramolecular energy transfer observed in nickel porphyrins. Femtosecond dynamics of palladium and platinum porphyrins are explored as well as triplet fusion in PtOEP neat films, providing a unique way to study energy transfer and amorphous films. Finally, pump probe studies aim to explain photoluminescent quenching behavior in tin and indium porphyrins through observation of charge separated states. Investigation of these porphyrins is crucial to improving device efficiency through fundamental understanding of the excited state dynamics in films and neat films.
Impact resistance of filled concrete box sections
(2013-08) Bruhn, Christopher Michael
The purpose of this research is to analyze the effects of drop-weight impact tests on filled concrete box sections. Research in other areas of soil filled container walls has proved favorable in blast loading environments suggesting a concrete system may also work well. In the experiment, thirty different box sections were cast and broken via drop weight test with six different fill materials. The testing yielded that compacted sand is the most favorable fill material for the sections. The research results indicate that further testing and applications should use compacted sand as a fill material.
Innovative Technologies for Lifetime Extension of an Aging Inventory of Vulnerable Bridges
(Center for Transportation Studies, University of Minnesota, 2011-12) Gastineau, Andrew; Wojtkiewicz, Steven; Schultz, Arturo
This report refines a response modification framework, previously developed by the authors, which combines technological developments in the fields of control systems, health monitoring, and bridge engineering to increase bridge safety. To enhance the modification framework, the numerical bridge model is refined and additional modification apparatuses are added to the numerical model to further develop and confirm the advantages of the response modification approach. A parameter study of the modification apparatus characteristics is carried out to optimize member sizes and modification device characteristics. Finally, a frequency response analysis is carried out to investigate the use of a semi-active system within the scope of the response modification framework.
Mining dynamic relationships from spatio-temporal datasets: an application to brain fMRI data
(2014-05) Atluri, Gowtham
Spatio-temporal datasets are being widely collected in several domains such as climate science, neuorscience, sociology, and transportation. These data sets offer tremendous opportunities to address the imminent problems facing our society such as climate change, dementia, traffic congestion, crime etc. One example of a spatio-temporal dataset that is the focus of this dissertation is Functional Magnetic Resonance Imaging (fMRI) data. fMRI captures the activity at all locations in the brain and at regular time intervals. Using this data one can investigate the processes in the brain that relate to human psychological functions such as cognition, decision making etc. or physiological functions such as sensory perception or motor skills. Above all, one can advance the diagnosis and treatment procedures for mental disorders.The focus of this thesis is to study dynamic relationships between brain regions using fMRI data. Existing work in neuroscience has predominantly treated the relationships among brain regions as stationary. There is growing evidence in this community that the relationships between brain regions are transient. In the time series data mining community transient relationships have been studied and are shown to be useful for various tasks such as clustering and classification of time series data. In this work we focused on discovering combinations of brain regions that exhibit high similarity in the activity time series in small intervals. We proposed an efficient approach that can discover all such combinations exhaustively. We demonstrated its effectiveness on synthetic and real world data sets.We applied our approach on fMRI data collected in different settings on different groups of people and studied the reliability and replicability of the combinations we discover. Reliability is the degree to which a combination that is discovered using fMRI scans from a population can be found again using a different set of scans on the same population. Replicability is the degree to which a combination discovered using scans from one set of subjects can be discovered again using scans from a different set of subjects. These two factors reflect the generality of the combinations we discover. Our results suggest that the combinations we discover are indeed reliable and replicable. This indicates the validity of the combinations and they suggest that the underlying neuronal principles drive these combinations. We also investigated the utility of the combinations in studying differences between healthy and schizophrenia subjects.Existing work in estimating transient relationships among time series typically uses sliding time windows of a fixed length that are shifted from one end to the other using a fixed step size. This approach does not directly identify the intervals in which a pair of time series exhibit similarity. We proposed another computational approach to discover the time intervals where a given pair of time series are highly similar. We showed that our approach is efficient using synthetic datasets. We demonstrated the effectiveness of our approach on a synthetic dataset. Using this approach we provided a characterization of the transient nature of a relationship between time series and showed its utility in identifying task related transient connectivity in fMRI data that is collected while a subject is resting and while involved in a task.In summary, the computational approaches proposed in this thesis advance the state-of-the-art in time series data mining. Whereas the extensive evaluations that are performed on multiple fMRI datasets demonstrate the validity of the findings and provide novel hypothesis that can be systematically studied to advance the state-of-the-art in neuroscience.
Multi-Scale Modeling of Microtubule Dynamics and the Regulation by Microtubule-Targeting Agents
(2020-01) Hemmat, Mahya
Microtubules (MTs) serve to facilitate vital cellular functions, such as chromosome segregation during mitosis and synaptic plasticity. MTs self-assemble via “dynamic instability,” in which the dynamic plus ends switch stochastically between alternating phases of polymerization and depolymerization. A key question in the field is what are the atomistic origins of this switching, i.e., what is different between the GTP- and GDP-tubulin states that enables MT growth and shortening, respectively? More generally, MTs are a great example of a complex biological system with spatial and temporal scales ranging from atomistic interactions such as GTP hydrolysis to cell-level behavior such as response to MT dynamics during mitotic progression. To understand a complex biological system behavior, a key challenge is connecting together the vast range of theoretical frameworks across length- and time scales. At the same time, MT interactions with associated proteins and binding agents, such as chemotherapy drugs, can strongly affect this dynamic process through molecular mechanisms that remain to be elucidated. The work in this dissertation integrates multiscale computational modeling with high resolution experimental observations to understand the molecular mechanism underlying MT dynamic instability and the regulation of dynamics by a well-established microtubule-targeting agent (MTA), colchicine. First, we develop a multi-scale modeling framework in which molecular dynamics (MD) are performed to investigate the interaction potential energies of tubulin-tubulin heterodimers, then, those results will be incorporated into Brownian dynamics (BD) simulations to study the kinetics of dimers assembly into MT lattice, and finally, thermo-kinetic and mechanochemical modeling of MT assembly, with inputs from MD and BD simulations, provide an insight into individual MT dynamics and details about MT tip structures. The model results point to a nucleotide-independent lateral bond of ~4 kBT, a nucleotide-dependent longitudinal bond of ~9 and ~5 kBT (∆∆G_long^0≈ 4 kBT) for GTP- and GDP-dimers, respectively and a radial bending angle preference (~1.5 kBT) for GDP-dimers. Furthermore, the framework informs us on how a well-known MTA, colchicine, affects MT dynamics. We found that colchicine binds mainly to free tubulin and sub-stoichiometrically poisons the end of protofilaments (PFs) through a copolymerization mechanism by which tubulin-colchicine (TC) complexes reduce the affinity of the PF for further tubulin addition and reinforce tubulin-tubulin lateral bond, a mechanism entirely distinct from that of paclitaxel or vinblastine.. In summary, this dissertation advances our knowledge about the molecular mechanism that drives dynamic instability and its regulation by MTAs within the context of cellular biology through a multi-scale approach and can be used for the development of more effective cancer therapeutic agents.
Reverse engineering biological networks: computational approaches for modeling biological systems from perturbation data
(2013-09) Kim, Yungil
A fundamental goal of systems biology is to construct molecule level models that explain and predict cellular or organism level properties. A popular approach to this problem, enabled by recent developments in genomic technologies, is to make precise perturbations of an organism's genome, take measurements of some phenotype of interest, and use these data to "reverse engineer" a model of the underlying network. Even with increasingly massive datasets produced by such approaches, this task is challenging because of the complexity of biological systems, our limited knowledge of them, and the fact that the collected data are often noisy and biased. In this thesis, we developed computational approaches for making inferences about biological systems from perturbation data in two different settings: (1) in yeast where a genome-wide approach was taken to make second-order perturbations across millions of mutants, covering most of the genome, but with measurement of only a gross cellular phenotype (cell fitness), and (2) in a model plant system where a focused approach was used to generate up to fourth-order perturbations over a small number of genes and more detailed phenotypic and dynamic state measurements were collected. These two settings demand different computational strategies, but we demonstrate that in both cases, we were able to gain specific, mechanistic insights about the biological systems through modeling. More specifically, in the yeast setting, we developed statistical approaches for integrating data from double perturbation experiments with data capturing physical interactions between proteins. This method revealed the highly organized, modular structure of the yeast genome, and uncovered surprising patterns of genetic suppression, which challenge the existing dogma in the genetic interaction community. In the model plant setting, we developed both a Bayesian network approach and a regularized regression strategy for integrating perturbations, dynamic gene expression levels, and measurements of plant immunity against bacterial pathogens after genetic perturbation. The models resulting from both methods successfully predicted dynamic gene expression and immune response to perturbations and captured similar biological mechanisms and network properties. The models also highlighted specific network motifs responsible for the emergent properties of robustness and tunability of the plant immune system, which are the basis for plants' ability to withstand attacks from diverse and fast-evolving pathogens. More broadly, our studies provide several guidelines regarding both experimental design and computational approaches necessary for inferring models of complex systems from combinatorial mutant analysis.
Static and Dynamic Properties of DNA Confined in Nanochannels
(2017-10) Gupta, Damini
Next-generation sequencing (NGS) techniques have considerably reduced the cost of high-throughput DNA sequencing. However, it is challenging to detect large-scale genomic variations by NGS due to short read lengths. Genome mapping can easily detect large-scale structural variations because it operates on extremely large intact molecules of DNA with adequate resolution. One of the promising methods of genome mapping is based on confining large DNA molecules inside a nanochannel whose cross-sectional dimensions are approximately 50 nm. Even though this genome mapping technology has been commercialized, the current understanding of the polymer physics of DNA in nanochannel confinement is based on theories and lacks much needed experimental support. The results of this dissertation are aimed at providing a detailed experimental understanding of equilibrium properties of nanochannel-confined DNA molecules. The results are divided into three parts. In first part, we evaluate the role of channel shape on thermodynamic properties of channel confined DNA molecules using a combination of fluorescence microscopy and simulations. Specifically, we show that high aspect ratio of rectangular channels significantly alters the chain statistics as compared to an equivalent square channel with same cross-sectional area. In the second part, we present experimental evidence that weak excluded volume effects arise in DNA nanochannel confinement, which form the physical basis for the extended de Gennes regime. We also show how confinement spectroscopy and simulations can be combined to reduce molecular weight dispersity effects arising from shearing, photo-cleavage, and nonuniform staining of DNA. Finally, the third part of the thesis concerns the dynamic properties of nanochannel confined DNA. We directly measure the center-of-mass diffusivity of single DNA molecules in confinement and show that that it is necessary to modify the classical results of de Gennes to account for local chain stiffness of DNA in order to explain the experimental results. In the end, we believe that our findings from the experimental test of the phase diagram for channel-confined DNA, with careful control over molecular weight dispersity, channel geometry, and electrostatic interactions, will provide a firm foundation for the emerging genome mapping technology.
The structural dynamics of force generation in muscle, probed by electron paramagnetic resonance of bifunctionally labeled myosin.
(2009-05) Thompson, Andrew Russell
Two proteins in muscle, actin and myosin, are the key structural components that interact in order to produce muscle contraction. Myosin is a molecular motor that utilizes the chemical energy of ATP to undergo conformational changes that translate actin linearly, resulting in mechanical work. While previous studies have provided high-resolution measurement of these structural changes, many are unable to do so in intact muscle or in systems where myosin and actin can interact. This project seeks to make high-resolution structural measurements of myosin in actomyosin complexes during the different biochemical states associated with contraction. These measurements are being made using electron paramagnetic resonance (EPR), a spectroscopic technique sensitive to protein dynamics and orientation. In order to study myosin with EPR, a spin label is chemically attached to cysteine within the protein structure. In certain cases, native cysteines are used for spin labeling whereas in others, mutant protein is created with cysteines engineered in desired locations, a process known as site-directed spin labeling.Traditional spin probes attach via a single, flexible bond. This monofunctional attachment limits the sensitivity of EPR to protein orientation and dynamics because the resultant spectra are a mixture of probe and protein states. This project, on the other hand, uses a novel bifunctional spin label that is rigidly coupled to the protein via attachment to two engineered cysteines. Due to this rigid coupling, high-resolution structural measurements can be made with a degree of sensitivity not available to other techniques.
Time Resolved Vibrational Spectroscopies as a Tool for Exploring Dynamics of Confined Systems
(2022-01) Pyles, Cynthia
This thesis examines a variety of vibrational probe-containing molecules such as triphenyl hydrides, CO2, and metal carbonyls with the goal of better understanding the dynamics for each system. Particular emphasis is placed on understanding how the behavior of a restricted probe, such as one dissolved in a rigid polymer or confined to a nanopore, may differ from the same probe placed in bulk solvent or a more rubbery polymer. The first study described herein scrutinized the vibrational heavy atom effect and its impact on ultrafast vibrational dynamics. A series of three triphenyl hydride compounds was investigated in a range of solvents by Fourier transform infrared (FTIR), infrared (IR) pump-probe, and two-dimensional infrared (2D-IR) spectroscopies. The mass of the central atom in the three compounds was varied systematically down the group 14 elements of silicon, germanium, and tin while keeping the rest of the molecule unaltered. Interestingly, frequency-frequency correlation functions obtained from 2D-IR spectra indicated that an increasingly large central atom produces small, but measurable changes in the dynamics of the solvation shell surrounding each compound. Next, CO2 (g) was examined via 2D-IR spectroscopy as a precursory study to understanding its behavior inside polymers. Processes which lead to dephasing of the vibrational echo such as collisions were largely circumvented by using CO2 diluted in N2 under ambient pressure and temperature. Off diagonal features in the 2D-IR spectra were observed which correspond to population and coherence exchange between rovibrational transitions. Then, CO2 (g) was dissolved inside polymers such as poly(methyl methacrylate), poly (methyl acrylate), and poly(dimethylsiloxane). These polymers with differing properties were chosen to study the impact of the glass transition on the dynamics of the dissolved CO2 probe. Interactions between the polymeric backbone and probe also impacted the dynamics. The parameters obtained from 2D-IR studies directly correlated with the diffusivity of CO2 through the polymer matrices. Next, I inspected CO2 (g) adsorbed to microporous systems such as MIL-53(Al) and ZIF-8. Preliminary FTIR studies suggest that these samples could possess a wealth of dynamic information despite narrow FTIR peaks, much like CO2 dissolved in polymers. Experimental limitations regarding these novel systems are briefly discussed. Lastly, I compared the dynamics of three ruthenium-bound carbonyl complexes: Ru3CO12 in bulk THF, [HRu3(CO)11]- entrapped in an aluminum sol-gel, and [NEt4][HRu3(CO)11] in bulk THF. Ru3CO12 is catalytically inactive but becomes active upon incorporation into an alumina sol-gel matrix. Pump probe and 2D-IR studies indicated that the changed dynamics are primarily due to an altered solvent shell which most likely exhibits long-range ordering. Though it is uncertain whether the increased catalytic activity of [HRu3(CO)11]- is due to the presence of the hydride or this newly ordered solvent shell, the results nonetheless showcase 2D-IR’s efficacy in sensing dynamics of confined environments.
Time- and phase-resolved spectroscopy of three-magnon scattering
(2023-06) Hamill, Alex
In ferromagnets, scattering processes between magnon modes have been an active platform for the investigation of nonlinear wave interactions and chaotic dynamics for over six decades. Despite this rich history, questions remain regarding the nature of these interactions. In this regard, three-magnon scattering of the ferromagnetic resonance (FMR) mode is of particular appeal: the threshold FMR magnon population at which scattering occurs is distinctly low, enabling its investigation over a wide range of excitation powers. This particular scattering process requires the availability of magnon modes at half of the frequency of the FMR mode. This requirement is readily fulfilled in magnetic films of micrometer thickness, as the associated dipolar interactions lead to a dip in their magnon dispersion. Existing studies of three-magnon scattering have largely focused on its influence on the magnon populations and on the steady-state behavior. A comprehensive understanding of its transient behavior (i.e. how it evolves in time as it approaches steady state) is missing. Similarly, little is known about the influence of three-magnon scattering on the magnons' phases. This is largely the case for other magnon scattering processes as well. There is also a lack of a formal understanding of the relationship between the forward and backward three-magnon scattering processes, i.e. between splitting and confluence. These gaps are, in part, owing to the fact that there is a lack of a comprehensive time- and phase-resolved experimental investigation of the three-magnon scattering process. Magnon scattering processes are most commonly investigated through diode-based techniques, which are relatively insensitive and lack phase resolution. They are also most commonly investigated through Brillouin light scattering spectroscopy; this technique is typically employed for large excitation powers, and its phase-sensitive implementations have not been applied to three-magnon scattering. Motivated by the above, I have assembled a time- and phase-resolved homodyning spectrometer that is operable over six orders of magnitude in microwave power. This spectrometer demonstrates a time resolution of 2 ns, and its sensitivity enables measurement of the transient behavior down to an excitation power of 10 microwatts. Upon measuring the resonance peak of the FMR mode, I observed satellite peaks near that of the FMR resonance. Such satellite peaks are observed in the literature as well. I found that they originate from the excitation of magnon modes with finite in-plane wavevectors, due to the inhomogeneity of the microwave field throughout the sample. To address this inhomogeneity, I created a microstrip waveguide with a signal line width of approximately 3.4 mm, such that it is appreciably wider than the 2 mm-wide sample. This ensures a highly uniform microwave field and, therefore, the highly isolated excitation of the FMR mode. Isolating the excitation of the FMR mode in this manner enables a clear interpretation of the measured transient behavior, and contributes toward the strong agreement observed between my experiment and my semianalytical model. With the above developments, I have investigated the transient behavior of the FMR mode during this scattering process over five orders of magnitude in power. In addition to my observing the expected transient behavior, in which the scattering monotonically suppresses the FMR magnon population to its threshold value, I find a second nonlinear in which the FMR magnon population exhibits transient oscillations about its threshold value. I find that both these oscillations and the timescale of the initial transient peak are highly dependent on the excitation power. At high powers, I find a third nonlinear regime in which the scattering generates 180-degree phase shifts of the FMR magnons. Moreover, I find that both these phase shifts and the transient oscillations reappear upon removing the microwave excitation (i.e. after turn-off). To supplement the experiment, and to understand my findings, I have derived a simplified semianalytical model of this scattering process based on the Landau-Lifshitz-Gilbert equation. Upon linearizing my model, I found that the oscillatory regime corresponds to a transition of the nonlinear regime's fixed point from a stable node to a stable spiral. I also extracted the predicted scaling of the oscillation frequency with the microwave field amplitude. Upon extracting the associated scaling of the experimental data, I found it to be in quantitative agreement with the predicted scaling over several orders of magnitude in power. To investigate the 180-degree phase shifts observed in the experiment, I generalized my model to allow for phase dynamics by omitting the standard assumption of harmonic time dependence. Numerically solving this generalized model, I found that it predicts these 180-degree phase shifts. In order to derive the equations of motion of the magnon populations, one begins with the generalized model and assumes harmonic time dependence. Remarkably, when accounting for the 180-degree phase shift in this harmonic approximation, I found that the phase shifts correspond to reversals in the scattering direction: in the magnon populations' equations of motion, the phase shift switches the sign of the scattering terms such that the scattering is now driving the FMR mode instead of damping it. These reversals explain the observed transient oscillations after turn-off: even without the excitation field, the FMR population may still oscillate via reversals between the forward and backward scattering process. These experimental and theoretical developments further the state of the art of the investigation of magnon scattering processes. The findings of my investigation provide a more comprehensive understanding of the transient behavior of this scattering process, and reveal the nontrivial interplay between three-magnon scattering and the magnons' phases.
Time-Resolved Magneto-Optical Kerr Effect for the Study of Ultrafast Magnetization Dynamics in Magnetic Thin Films
(2020-05) Lattery, Dustin
As traditional complementary metal oxide semiconductors (CMOS) struggle to extend previous industrial trends, new technologies must be researched and delivered. One of the most important aspects that must be considered is the transport of heat within the material. By advancing the design of materials and interfaces, heat transfer within electronic devices can be improved. At the same time, novel technologies that rely on the magnetism of thin films also need to have their transient magnetic behavior optimized. By measuring the magnetic response of the materials, engineers can select the best-matched materials to design and fabricate devices with lower power consumption and higher processing speed, and thus improved performance. Such material transport studies require new methods and metrology development that can provide highly sensitive and accurate characterization of the materials. The time-resolved magneto-optical Kerr effect (TR-MOKE) technique is capable of probing both thermophysical and magnetic properties of a variety of materials, and it offers superb spatial (micrometer) and temporal (sub-picosecond) resolutions. In this thesis, information about this technique will be discussed including thorough examples of its applications in the study of magnetization dynamics.
Understanding and Mitigating the Dynamic Behavior of RICWS and DMS under Wind Loading
(2018-05) Finley, Nicole
Dynamic Messaging Signs (DMS) and Rural Intersection Conflict Warning Signs (RICWS) are roadside signs that feature much larger and heavier signs than are typically placed on their respective support systems. There is a concern that the excess weight and size of the DMS and RICWS, in conjunction with their breakaway support systems, may introduce wind-induced vibration problems not seen in the past. The AASHTO 2015 LRFD Specification for Structural Supports for Highway Signs, Luminaires, and Traffic Signals (SLTS) does not yet address vibration design for these nontraditional roadside signs. Research was done to explore the wind-induced vibrations in the DMS and RICWS. The DMS support system, specifically the friction fuse connection, is susceptible to the formation of stress concentrations and potential fatigue issues. A dynamic numerical model was validated with experimental field data and used to evaluate the fatigue life of the DMS support system instrumented in the field. The fatigue life of the DMS instrumented in the field was found to be approximately 23.8 years. Results of the analysis should be expanded beyond the behavior of the specific DMS instrumented in the field to encompass other varieties of the DMS in service. Large amplitude oscillations under wind loading have already been observed in the RICWS. Research was done to explore the wind-induced dynamic behavior of the RICWS and determine suitable modifications to the RICWS support system for reducing the amplitude of the wind-induced oscillations. Based on data collected from a RICWS instrumented in the field and experiments done on a scaled model of the RICWS at the St. Falls Anthony Laboratory, vortex shedding was identified as the predominant wind phenomena acting on the RICWS structure. Modifications to reduce the impacts of vortex shedding, such as fins, appear most appropriate for reducing the amplitude of the wind-induced oscillations. The effectiveness of the recommended modifications requires further exploration with the experimentally validated numerical models of the RICWS.
Vibrational Spectroscopy on the Silicon Hydride Mode: Probing Ultrafast Dynamics in Small Molecules to Macromolecular Polymer Systems
(2019-06) Olson, Courtney Marie
This thesis describes Fourier transform infrared (FTIR) and two-dimensional infrared (2D-IR) spectroscopy applied to small molecule silanes (trimethoxysilane and triphenylsilane) and polydimethylsiloxane (PDMS). 2D-IR spectroscopy gives information about the dynamics that the vibrational probe is sensitive to and the heterogeneous and homogeneous contributions to the linear FTIR lineshape. The vibrational probe used for all the studies in this thesis is the silicon hydride stretch due to being present in the small molecule silanes and in PDMS. The studies presented show how the silicon hydride mode was first characterized in small molecules to understand the probe more. Then, the probe was utilized in polymer systems to study more complex motions to make the connection between the ultrafast dynamics of polymers to the macroscopic properties. The first study involved studying the solvation dynamics of two small molecule silanes in three neat solvents using FTIR and 2D-IR spectroscopies along with molecular dynamics simulations. The two different molecules exhibited different degrees of vibrational solvatochromism, and the differences was found to be a result of higher mode polarization with more electron withdrawing ligands using density functional theory calculations. The solvent dynamics were found to be dominated by their interactions with neighboring solvent molecules rather than with the solute. Next, FTIR and 2D-IR spectroscopies were used to study PDMS cross-linked films and siloxane oligomers without solvent and swollen or dissolved in various solvents. There is an absence of vibrational solvatochromism in these systems, which was shown by 2D-IR spectroscopy to be due to the heterogeneity. The silicon hydride mode in the cross-linked, solvent-free PDMS film exhibited spectral diffusion, which must be due to the polymer structural motions. However, once the solvent penetrates the network, the dynamics become a convolution of the solvent and polymer motions due to the motions being of similar timescale. In the last study discussed, FTIR and 2D-IR spectroscopies were used to study the ultrafast structural dynamics of PDMS thin films with various physical and chemical changes done to the polymer, which included elevated curing temperature, increased cross-linker agent concentration, compression, and cooling near the glass transition temperature. The FTIR spectra were found to be relatively insensitive to all of these perturbations, which 2D-IR spectroscopy revealed was caused by the overwhelming heterogeneity. There is clearly a disconnect between the microscopic and macroscopic behavior in this polymer due to having only slight differences in the heterogeneous and homogeneous dynamics.

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