Doctor of Philosophy, University of Akron, 2020, Polymer Engineering

The nature of glassy aging has been a topic of study for over half a century, and yet a number of open questions remain in the understanding of the glassy state. Since a polymer's physical and mechanical properties are directly dependent on its molecular structure and changes in that structure alter the physical properties of the glass, considerable economic impact can result from aging-related physical changes. Characterization of aging dynamics in under-dense and over-dense glasses and a comparison of the aging response in solvent-processed vs thermally-quenched glasses are two important questions that are addressed here. This work reports on the development of a protocol for studying physical aging via molecular dynamics simulation after a near-instantaneous temperature quench. The resulting data display characteristic experimental signatures of glassy aging in both a pure polymer and a polymer-plasticizer system, indicating that this protocol can potentially be used to study aging in a variety of systems. Results indicate that aging dynamics in under-dense and over-dense glasses are fundamentally different in character. Unlike in under-dense glasses, translational dynamics in over-dense glasses are mechanistically different than relaxation in equilibrium glass-forming liquids, which is supported by the finding that relaxation in over-dense glasses occurs through an explosive burst of superdiffusive motion. Addition of a plasticizer appears to moderate this response compared to that of the pure polymer system, which can be attributed to a decrease in system fragility in the plasticized system. Higher additive loadings may have an even greater effect and further research would be beneficial in clarifying this. Aging relaxation time in over-dense glasses obeys a zero parameter dependence on purely equilibrium properties. This finding enables prediction of non-equilibrium relaxation time given knowledge only of the starting temperature and the in-equilibrium (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2019, Physics and Astronomy (Arts and Sciences)

We study the collective dynamics of diffusively coupled excitable elements in small tree networks with regular and random connectivity, which model sensory neurons with branched myelinated distal terminals. These neurons possess dendritic trees with myelinated branches and with nodes of Ranvier at every branching points. They may show spontaneous noisy periodic spiking. Examples of such neurons include touch receptors, muscle spindles afferents and some electroreceptors. A mathematical model of such a neuron is a system of excitable elements coupled on a tree network. We show that the mechanism of periodic firing is rooted in the synchronization of local activity of individual nodes, even though peripheral nodes may receive random independent inputs. We developed a theory that predicts the collective spiking activity in physiologically-relevant strong coupling limit. The structural variability in random tree networks translates into collective network dynamics leading to a wide range of firing rates and coefficients of variations, which is most pronounced in the strong coupling regime. We studied signal detection in regular and random trees. Our results indicate that the highest sensitivity occurs in specific optimum values of the input current for any given tree network. In the presence of a time-dependent uniform stimulus, we have shown that the highest information carried by spikes of the central node of a tree about the stimulus is attained for the strong coupling, even though the firing rate is at maximum for smaller values of coupling strength. Finally, we studied the effect of inhomogeneous inputs on the collective response of tree networks and showed that it leads to additional variability of collective firing.

Doctor of Philosophy, Case Western Reserve University, 2015, Macromolecular Science and Engineering

Computational studies have emerged as a key class of scientific approached to solving different problems of interest in the past few decades. Dissipative Particle Dynamics, DPD, a mesoscale simulation technique based on Molecular Dynamics has been established as a powerful technique in recovering a wide range of physical and chemical processes. Nevertheless, absence of robust bridge between the computational parameters to the physical characteristics of a system has limited applications of DPD. Thus in the second chapter of this dissertation (after a brief introduction and organizational guideline in chapter 1) a systematic study will be presented, providing several routes for setting the simulation parameters based on the real experimental measures. Although computational and theoretical works have always been a crucial areas of research in the rheology society, DPD has not been employed in rheological studies. This is mainly due to the fact that a step-by-step guideline does not exist for rheological measurements in DPD. Another reason for this lack of success in rheological community is that the built-in thermostat in DPD is not capable of providing a stable control over the thermodynamics of the system under flow conditions. Thus, firstly in chapter 3 different methods of viscosity measurement and rheological studies will be discussed in detail, and consequently in chapter 4 a novel thermostat is presented to modify the natural shortcomings of DPD under flow. For decades now, scientists across different disciplines have attempted at identifying the nature of versatile rheological response of colloidal suspensions. Exhibiting Newtonian behavior at very low, shear-thinning at intermediate, and shear-thickening at high flow rates in dense colloidal suspensions exemplifies a broad range of rheological regimes within a simple solid-liquid system. Despite numerous experimental and computational efforts in explaining the underlying mechanism of these behavior, there i (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2014, Polymer Science

For decades, device design has focused on decreasing length scales. In computer and electronic engineering, small feature sizes allow increasing computational power in ever-smaller packages; in medicine, nanoscale in vivo devices and sensors and coatings have myriad applications. These applications all focus strongly on material/component interfaces. While recent advances in experimental techniques probing interfaces at nanometer and sub-nanometer scales have improved dramatically, computational simulation remains vital to obtaining detailed information about structure and energetics in nanometer-scale interactions at interfaces and the physical properties arising from interactions at larger scales. We start with all-atom molecular dynamics simulations of methane and chloromethane adsorption on the (100) surface of molybdenum to understand adsorbate polarity/geometry and substrate interaction potential effects on interfacial structure, packing and energetics. For featureless substrates, adsorbate geometry and orientation do not influence packing and affinity. Substrates with explicit surface structure show cooperation between substrate and adsorbate geometry via adsorption-site preference. Methane prefers sites over unit cell faces, roughly commensurate with the Mo surface, whereas chloromethane invites disorder, orienting its long axis along ”bridges” between surface Mo atoms. In the second phase, we used a coarse-grained bead-spring model to perform simulations of bottle-brush homopolymers tethered to a wall substrate at long time/length scales. We studied the intra- and intermolecular accumulation of tension in tethered bottle-brush backbones vs. bottle-brush dimensions and surface grafting density. Variations in bond force and bottle-brush/component shape and size descriptors uncovered three tension ”regimes”: (i) an isolated-brush regime (low surface grafting density), where intramolecular interactions dominate and tension is minimal; (ii) a ”soft-contac (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2012, Mechanical Engineering

This research involved the modeling, control and state estimation of a Roll Simulator. The focus of this study was on the Roll Simulator's application in emulating rollovers for vehicles such as ROVs. The Roll Simulator was designed to study occupant kinematics during a vehicle rollover in a laboratory setting. Little research has been performed where the focus has been on the vehicle rolling over to 90 degrees and the interaction of the occupant with the road plane at this instance has been closely examined. The Roll Simulator allows for these types of analyses to occur. In this dissertation, a two (2) degree-of-freedom model, describing the dynamics of the Roll Simulator, is developed. Equations of motion, derived using Lagrange's energy methods, describe the dynamics of the sled-platform assembly. Additional sub-system modeling is also performed to capture the dynamics of a hydraulic system, electro-magnetic particle brake and electric roll motor. The validity of the full simulation is corroborated by comparisons with experimental data from the Roll Simulator. Control strategies for the Roll Simulator are also discussed. The strategies are derived utilizing simple physics of the system. This allows for desired trajectories to be met using feed-forward terms. Application of feedback is limited due to the configurations of the actuators and the short duration maneuever. A variety of linear observers are introduced to estimate states within the Roll Simulator. A Kalman Filter is developed to estimate sled speed. To tune the filter, the Kalman Filter is applied to a higher fidelity model which has four (4) degrees-of-freedom. To capture the non-linear behavior of the sled-platform assembly, an Extended Kalman Filter (EKF) is used. When applied to experimental data, the observed sled speed exhibits gross over-estimation of the true speed. This is due to a disturbance in the system. A disturbance observer is used to estimate rolling resistance between the sled and f (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2007, Biophysics

One of the detrimental effects of UV radiation on the biosphere is the formation of cyclobutane pyrimidine dimers (Pyr<>Pyr) between two adjacent thymine bases in DNA. Pyr<>Pyr dimers bring DNA repair machinery in the cell to a standstill and may result in mutation or cell death. Photolyase which is a photoenzyme that exists in all three branches of life, harnesses blue or near-UV light energy to cleave the cyclobutane ring of the Pyr<>Pyr and, thus, prevents the harmful effects of UV radiation. Photolyase obtained from E.coli is a monomeric protein with two noncovalently attached cofactors: one is a light-harvesting photoantenna, a pterin molecule in the form of methenyltetrahydrofolate (MTHF), and the other one is the catalytic cofactor, a fully reduced deprotonated flavin molecule (FADH -). In the proposed hypothesis for the catalysis, the enzyme binds a Pyr<>Pyr in DNA, independent of light. The antenna chromophore MTHF harvests UV/blue-light photon, and transfers the excitation energy (dipole-dipole interaction) to FADH -. Excited FADH -*then transfers an electron to the Pyr<>Pyr, which consequently splits the Pyr<>Pyr into two pyrimidines and hence repairs the damaged DNA. The repair cycle ends when the excess electron is transferred from the repaired pyrimidine back to the nascent-formed FADH and regenerates the active FADH -form. The complex mechanism of energy and electron transfer in photolyase enzyme was investigated using state-of-the-art femtosecond laser spectroscopy in this study. The photophysics of FADH -cofactor was also studied in aqueous solution. Dramatic shortening of the excited state lifetime of FADH -in aqueous solution compare to its lifetime in protein environment compelled us to propose that enzyme photolyase modulates photophysical properties of the flavin cofactor to perform the essential biological function of electron transfer to repair damaged DNA.

Doctor of Philosophy, Case Western Reserve University, 2011, Macromolecular Science and Engineering

We studied the self-assembly dynamics of two polymeric systems, block copolymer micelles and supramolecular polymer solutions using computer simulation. Dissipative Particle Dynamics simulations were applied to study the equilibrium properties, kinetics of micellization and equilibrium chain-exchange in A2B3 and A4Bx(x=4,6,8) diblock copolymer micelle solutions. The critical micelle concentration, micelle aggregation number distribution and micelle structure were found to agree well with previous experimental and theoretical studies. The time-evolution of micelles from unimers is found to follow three stages: unimer consumption, equilibration of the number of micelles progressing mainly by the fusion/fission mechanism and slow adjustment of the weight-average aggregation number by micelle fusion, unimer and small aggregate exchange. The effect of polymer concentration, hydrophobic interaction energy and block length on the kinetics of micellization were also considered. By performing micelle hybridization simulations, we found the equilibrium chain exchange follows a first-order kinetic process and the characteristic time, mainly determined by chain expulsion and does not depend on polymer concentration. The chain exchange characteristic time, τ, increases exponentially with core block length, NA and interaction parameter between blocks, χAB as τ ~ exp(0.67χABNA). We also found that in contrast to theoretical predictions, chain exchange between micelles occurs more rapidly for micelles with a longer corona-block length due to a higher compatibility of diblock copolymers and therefore a lower potential barrier for chain expulsion. Using coarse-grained molecular dynamics simulations we studied the equilibrium and rheological properties of dilute and semi-dilute solutions of head-to-tail associating supramolecular polymers with our newly-developed model for spontaneous reversible association. We found that for a given spacer length all shear-rate-dependent reduced visc (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Engineering and Applied Science: Aerospace Engineering

Understanding and characterization of turbulence over the flight deck of large marine vehicle is important to assess its influence on the helicopter pilot workload while performing launch and recovery maneuvers. This research is regarding understanding the turbulent flow field over the flight deck of simplified frigate model (SFS2) using an Embedded Large Eddy Simulation turbulence model. The characterization of integral time and length scales of turbulent vortical structures in the superstructure air wake is carried out using correlation analysis. Focus of this research work is to understand the underlying reasoning of the generation of bistable airwake of the superstructure, asymmetry in the mean airwake structure and to ascertain the influence of its upstream flow field on the nature and characteristics of airwake. The asymmetry in the mean airwake behind superstructure was attributed to “locking” and/or differential momentum flux on sides of superstructure in literature, however no concrete evidence of causation was reported. In this research, the in-depth analysis of turbulent boundary layer buildup, vorticity distribution, relative size and orientation of vortices on and along the starboard and port sides of superstructure provides clear understanding and evidence of the influence of bow region flow field on airwake. The dynamics of bow flow field and vortical structures like leading edge vortices and horseshoe base vortex, generated upstream of superstructure forward facing step (bow-superstructure junction), and their possible interaction is investigated to ascertain their contribution towards the generation of asymmetrical mean airwake of superstructure. The time averaged flow field analysis revealed that bow flow field and the nature of the interaction between its leading edge vortices on the port and starboard sides respectively, with the base vortex highly influence the turbulence generation on the sides of the superstructure and ultimately influence the (open full item for complete abstract)

MS, University of Cincinnati, 2023, Engineering and Applied Science: Mechanical Engineering

Multi-robot systems are a promising solution for object transportation as they have huge advantages over single-purposed robots - they are more versatile, less specialized, and more resilient to system failure while they can be scaled in numbers to meet operating requirements. As humans continue to explore further into our universe and domestic needs continue to grow with an increasing population, more robots will be required to complete more jobs. Most importantly, this current philosophy does not consider environments without human intervention or teleoperation. In projects such as NASA Gateway where “galactic pitstops” may not have a human aboard for many months, faults or incomplete tasks would endanger any mission relying on consistent uptime. Tasks such as moving a simple object from an initial position to a target region, such as staging materials, must be completed by a reliable robotic system to save mission critical resources and time. However, when scaling numbers, multi-robot control and communication becomes complex as either monitoring technology or environmental cues must be deployed to enable coordination. In order to make the multi-robot system not only resilient, but also independent from environmental cues and hence universally deployable out-of-the-box, we propose a purely emergent interaction model based on touch between the individual mobile robots and contact with a manipulated object. This is realized with an attractor dynamics trajectory planner coined as “convergence” and a contact controller referred as “adherence” is benchmarked in a simulated non-prehensile object transportation task. The outcomes from this project include the “convergence” and “adherence” algorithms and how they behave as a coupled dynamic system, a Gazebo and Robotic Operating System (ROS) simulation, documentation and analysis of emergent behaviors from the coupled dynamic syste (open full item for complete abstract)

Doctor of Philosophy (PhD), Wright State University, 2023, Engineering PhD

In fluid flow experiments, there have been numerous techniques developed over the years to measure velocity. Most popular techniques are non-intrusive such as particle image velocimetry (PIV), but these techniques are not suitable for all applications. For instance, PIV cannot be used in examining in-vivo measurements since the laser is not able to penetrate through the patient, which is why medical applications typically use X-rays. However, the images obtained from X-rays, in particular digital subtraction angiography, are projective images which compress 3D flow features onto a 2D image. Therefore, when intensity techniques, such as optical flow method (OFM), are applied to these images the accuracy of the velocity measurements suffer from 3D effects. To understand the error introduced in using projective images, a vertical square tube chamber was constructed to achieve various water flow rates with variable dye injection points to perform dye visualization velocimetry (DVV). The results from DVV were compared with PIV measurements to quantify the error associated with DVV. Results from DVV were comparable with PIV, but a machine learning correction method, more specifically multilayer perceptron (MLP), was needed to adjust the DVV results. To train the MLP model, CFD simulations were conducted to generate detailed velocity distributions in the tube and projected dye images which would be used for DVV analysis and thus used as input for training. These CFD simulations were compared with PIV measurements and dye visualization images to validate proper boundary conditions and meshing. For the laminar case, MLP reduces the error associated with DVV from 35% down to 6.9%. When MLP was used to correct instantaneous DVV measurements for the turbulence cases, the error decreased from 22% to 9.8% for measurements 20 mm downstream of the dye inlet. For a time-averaged turbulent case, MLP was able to decrease the v-velocity error down to 5% and reduce the error of DVV by 5 (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2023, Biophysics

This dissertation explores the use of applying molecular dynamics (MD) and enhanced sampling methods towards understanding dynamics of the cardiac troponin complex (cTn) and the thermodynamic and functional consequences introduced by cardiomyopathic mutations. Chapter 2 explores an idea from the Davis group at Ohio State that cardiomyopathic mutations in the cTnI inhibitory peptide region (cTnIIP) can cause a reduced effective concentration of the cTnI switch peptide (cTnISP) to the cTnC hydrophobic patch region (cTnCHP). We utilized the Ca2+-unbound cTn structure produced by Yamada and colleagues to simulate both a normal cTn complex (tethered) and a model of the cTn complex with the cTnIIP removed and a free cTnISP (untethered) using molecular dynamics. Our results showed that the tether was essential in producing an effective concentration of cTnISP necessary for physiological function. We also observed that cardiomyopathic mutations did not significantly affect the effective concentration of cTnISP to the cTnCHP but did cause alterations to the dynamics and flexibility of the cTnIIP region. We observed in our simulations from chapter 2 that the cTnCHP never opened for any significant amount of time. Therefore, in the third chapter we sought to produce a trajectory of the transition event between the Ca2+-unbound and Ca2+-bound cTn forms by again using structures produced by Yamada. We successfully performed this using Targeted MD (TMD) and were able to observe a transition from a Ca2+-unbound, cTnCHP closed, cTnISP unbound form of cTn to a Ca2+-bound, cTnCHP open, cTnISP bound cTn. We then selected windows from the trajectory that correlated strongly with the cTnCHP opening and cTnISP binding transition events and performed umbrella sampling (US) simulations. Our results show near perfect replication of NMR studies on the cTnISP binding event and strong correlation with previous computational studies on the cTnCHP opening event. We then introduced mutations to (open full item for complete abstract)

PhD, University of Cincinnati, 2022, Arts and Sciences: Psychology

Complex, dynamic environments such as sports fields of play, present unique navigation demands for athletes striving to achieve both ultimate objectives (getting to a location to head a ball towards the goal) and relatively more immediate objectives (avoiding obstacles that might impede their progress towards a desired location). Narrow openings (or gaps) are among the most frequent potential impediments that athletes encounter when navigating the field of play. Decisions to go around a passable closing gap could result in a delay getting to a desired location on time undermining task success; decisions to go through an impassable gap could result in collision. Previous work has shown that pressure to arrive at a desired location shapes action decisions about the passability of closing gaps. In particular, the decision boundary of participants under pressure is biased towards end-gaps of smaller sizes and is less reliably defined, resulting in a higher number of collisions. The objective of this dissertation is to capture the mechanisms that underlie temporal pressure-based differences in gap passability decisions from an ecological dynamical perspective. The general hypothesis was that temporal pressure to arrive at a desired location shapes decisions about passability of closing gaps because it modifies how individuals perceptually explore and, in turn, respond to aspects of a task environment relevant for navigation. To test this hypothesis, I examined the responsiveness and gaze patterns of thirty participants instructed to navigate toward a waypoint in a virtual, sport-inspired environment. During the task, participants had to decide whether they could pass through closing gaps formed by virtual humans (and take the shortest route) or steer around them (and take the longer route). One group of participants (n=15) were told to arrive at the waypoint as fast as possible while the other group (n=15) received no further instruction. To determine the effect of tempo (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2022, Mathematics/Mathematics (Pure)

Hypercyclicity and universality have been extensively studied in the setting of Euclidean spaces. We show how to transfer such phenomena to the setting of smooth manifolds. We focus on operators on spaces of smooth functions defined on open subsets of smooth manifolds with an emphasis on partial differentiation operators. Furthermore, we provide a framework to extend the notions of universality and hypercyclicity to spaces of smooth functions defined on general smooth and complex manifolds. Motivated by our framework, we study the hypercyclicity phenomenon on differential forms on smooth manifolds. Finally, we construct a universal sequence of integral operators on spaces of differential forms defined on open subsets of smooth manifolds.

Doctor of Philosophy, The Ohio State University, 2021, Chemistry

Molecular dynamics (MD) simulations provide a unique atomic-level description of the structure and dynamics of proteins, which is essential for the mechanistic understanding of protein interactions and function in living organisms. However, traditional MD force fields that are optimized for folded proteins often generate overly compact structures and incorrect characteristics of intrinsically disordered proteins (IDPs) and protein regions (IDRs), thereby limiting the quantitative insights that can be gained from MD simulations. We introduce the residue-specific protein force field, ff99SBnmr2, which is derived from ff99SBnmr1 by balancing the backbone dihedral angle potentials in a residue-specific manner to quantitatively reproduce dihedral angle distributions from an experimental coil library. The new force field substantially improves the backbone conformational ensembles of disordered proteins, protein regions, and peptides while keeping well-defined protein structures stable and accurate. This balanced new force field should enable a myriad of applications that require quantitative descriptions of IDPs, IDRs, loop dynamics, and folding/unfolding equilibria in the presence and absence of interaction partners. The prevalence of IDPs and IDRs in structural biology has prompted the recent development of MD force fields for the more realistic representations of such systems. Using experimental nuclear magnetic resonance (NMR) backbone scalar 3J-coupling constants of the IDPs α-synuclein and amyloid-β in their native aqueous environment as a metric, we compare the performance of four recent MD force fields, namely, AMBER ff14SB, CHARMM C36m, AMBER ff99SB-disp, and AMBER ff99SBnmr2, by partitioning the polypeptides into an overlapping series of heptapeptides for which a cumulative total of 276 μs MD simulations were performed. The results show substantial differences between the different force fields at the individual residue level. Except for ff99SBnmr2, the forc (open full item for complete abstract)

MS, University of Cincinnati, 2021, Engineering and Applied Science: Mechanical Engineering

This thesis aims to develop a modular sensor fusion framework based on Unscented Kalman Filter (UKF) that estimates the 6-DOF (Degree-of-Freedom) pose of a quadrotor UAV using the dynamics derived from Newton's laws of motion and localization systems such as visual-inertial odometry (VIO) system and GPU-IMU (GI) system for both indoor and outdoor environments. Micro Aerial Vehicles (MAVs), especially quadrotors, are gaining attention for applications such as package delivery, inspection, emergency response, and search and rescue missions. State estimation becomes very crucial for carrying out both remotely-controlled and autonomous operations. This problem, known as localization, has been explored in the literature using a wider range of sensors such as radars, lidars, cameras, IMUs, and global positioning systems (GPS). In outdoor environments, GPS provides a reliable source of information for carrying out localization. Onboard sensing means such as cameras, IMUs, radars, or lidars are used for indoor environments. The localization problem becomes challenging for indoor environments for several reasons: i) difficulty in processing information from these sensors; ii) most onboard sensors are prone to erroneous measurements; and iii) need specific environmental conditions to satisfy (such as the presence of unique features in the environment, adequate lighting). This thesis focuses on improving localization by incorporating the UAV dynamics into the estimation alongside various localization sensors. We used a monocular camera and an IMU as sensing devices for indoor localization while GPS and IMU for outdoor localization. In recent times, VIO has been explored using different approaches. However, few research works exploit the quadrotor Newtonian dynamics and the known thrust and torque inputs. Incorporating the information from the dynamics with known control inputs provide robust state estimation. Hence, this thesis aims to estimate the quadrotor UAV 6-DOF pose (open full item for complete abstract)

PHD, Kent State University, 2020, College of Arts and Sciences / Department of Physics

Condensed Matter Physics studies the states of matter in solids. Perhaps one of the most interesting physical phenomena are realized when materials are cooled down to very low temperatures, so that the principles of quantum mechanics together with the inter-particle correlations lead to the emergence of novel states of matter. In my work, I have successfully used the methods of Quantum Field Theory and Computational Physics to study and predict the novel phases of strongly correlated fermionic systems. In particular, I have explored the emergence of temporal and spatial phases in quantum mechanical systems ranging from degenerate atomic condensates to iron-based superconductors at very low temperatures. In this document, I will provide the details of my work with the specific examples of the fascinating problem of superfluid order parameter dynamics in fermionic condensates driven out-of-equilibrium, spatial phases in novel superfluids, and calculations of Josephson's interface between two iron-based superconductors.

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2020, Photochemical Sciences

Single-molecule Magnetic tweezers have been developed as a powerful approach that provides detailed insight into single-molecule studies by mechanically manipulating and simultaneously monitoring the change of the photophysical properties. We have developed a few generations of magnetic tweezers and further utilized them for the studies of the mechanism of the product release during an enzymatic reaction, correlated studies of single-molecule enzymatic reaction dynamics and conformational dynamics, and live-cell motion manipulation. It is highly informative to manipulate the enzyme under the enzymatic conditions and simultaneously real-time monitor the conformational fluctuations of the enzymatic active site as well as the reaction activity change. Understanding how the enzyme dynamics of the conformational fluctuation relates to the enzyme activity can shed light on the field of enzymology. Motion manipulation of living cells and other biological entities is also important in the fields of biological research and tissue engineering. Particularly, in this dissertation, we have employed a Horseradish Peroxidase (HRP) catalyzed fluorogenic enzymatic reaction as a powerful probe to study the reaction and conformational dynamics of the enzymatic active site under mechanical force manipulation. The typical fluorogenic feature of this reaction makes the nascent-formed product molecule at its perfect fitted position at the enzymatic active site, serving as an in-situ probe to report the real-time active-site configuration and its fluctuations. Interestingly, the product releasing dynamics of HRP show the complex conformational behavior with multiple product-releasing pathways. However, under constant magnetic force manipulation, the complex nature of the multiple product- releasing pathways disappears, and more simplistic conformations of the active site are populated. Under oscillation force manipulation at different frequencies, we have observed that conformational dyna (open full item for complete abstract)

Master of Science, The Ohio State University, 2019, Mechanical Engineering

Noise and vibration performance of a gear system is critical in any industry. Vibrations caused by the excitations at the gear meshes propagate to the transmission housing to cause noise, while also increasing gear tooth stresses to degrade durability. As such, gear engineers must seek gear designs that are nominally quiet with low vibration amplitudes. They must also ensure that this nominal performance is robust in the presence of various manufacturing errors. This thesis research aims at an experimental investigation of the influence of one type of manufacturing error, namely random tooth spacing errors, on the vibratory responses of spur and helical gear pairs. For this purpose, families of spur and helical gear test specimens having intentionally induced, tightly controlled random spacing error sequences are fabricated. These specimens are paired and assembled in various ways to achieve different sequences of composite spacing errors. Static and dynamic motion transmission error measurements from these tests are compared to the baseline case of “no error” gear to quantify the impact of random spacing errors on the dynamic response. These comparisons show that there is a significant, quantifiable impact of random spacing errors on both spur and helical gear dynamics. In general, vibration amplitudes of gear pairs having random spacing errors are higher than those of the corresponding no-error gear pairs. In the frequency domain, gears having random spacing errors exhibit broad-band spectra with significant non-mesh harmonics, pointing to potential noise quality issues.

Master of Science, The Ohio State University, 2019, Environment and Natural Resources

Conservation practices, such as no-till and diversifying crop rotations are known for their capacity to reduce soil erosion and improve soil properties. However, the impact of these management practices on emerging soil health tests and the ability of these tests to reflect active organic matter dynamics and nutrient cycling, and corn productivity has not been explored. This project focused on determining the effects of half a century of continuous tillage treatments (moldboard plow, chisel till, and no-till) and crop rotations (continuous corn, corn-soybean, and corn-forage-forage) on soil health indicators and its relationship with crop productivity. The forages were alfalfa in Wooster and red clover and oats in Northwest. Soil labile carbon (C) and nitrogen (N) temporal dynamics were quantified with permanganate oxidizable C (POXC), mineralizable carbon (Min C), and soil protein at six key stages in corn (Zea mays) development: before planting (around three weeks before planting), V5, V10, R1, R4, R6 in the 2017 and 2018 growing seasons. Corn leaf chlorophyll, aboveground plant biomass, nutrient uptake, and grain yield were also quantified. The soil health indicators (POXC, Min C, soil protein) and crop parameters (leaf chlorophyll, total nitrogen uptake, and total aboveground biomass) were higher in reduced tillage (chisel and no-till) compared to moldboard plow and higher in the most diverse crop rotation (corn-forage-forage) compared to corn-soybean. Corn yields were not significantly different between tillage treatments but were higher in the more diverse rotations (corn-soybean and corn-forage-forage) compared to corn monoculture. Although the treatment effects varied by site and year, rotation had a consistently larger effect on soil health indicators and corn productivity than tillage, highlighting the importance of including crop rotations in corn production. We conclude that Ohio soils under half a century of continuous tillage and rotation treatments ha (open full item for complete abstract)

Master of Science, The Ohio State University, 2019, Aero/Astro Engineering

This thesis details aeroelastic response prediction of hoods on automobiles in the wake of a leading vehicle. Such conditions can lead to significant hood vibration due to the unsteady loads caused by vortex shedding. A primary focus is the sensitivity of the aeroelastic response to the aerodynamic modeling fidelity. This is assessed by considering both Reynolds-Averaged Navier-Stokes (RANS) and Detached Eddy Simulation (DES) flow models. The aeroelastic analysis is carried out by coupling a commercial computational Fluid dynamics (CFD) solver (StarCCM+) to a commercial computational structural dynamics (CSD) solver (Abaqus). Two different configurations are considered: 1) sedan-sedan and 2) sedan-SUV. This enables the consideration of both varied geometry and structural stiffness on the aeroelastic response. Comparisons between RANS and DES emphasize the importance of turbulence modeling fidelity in order to capture the unsteadiness of the flow and the vibration response of the hood. These comparisons include analysis of the lift forces, pressure loads on the hood, and Power Spectral Density Analysis (PSD) of the flow in the region between the two vehicles. As expected, DES predicts higher frequency content and significantly higher turbulence levels than RANS. Both the sedan and SUV hoods are sensitive to the turbulent fluctuations predicted by DES. The increased levels of turbulence result in up to 40 - 60% higher maximum peak to peak deformation and the excitation of a torsional mode of the hood for the sedan-sedan case. For the more flexible hood configuration (sedan - SUV), these differences are even higher, with maximum peak to peak deformations of up to 17 – 71% higher than the RANS solution.