Heat transfer and solidification models were developed for use in a numerical model of a continuous caster to provide a means of predicting how the developing shell would react under variable operating conditions. Measurement data of the operating conditions leading up to a breakout occurrence were provided by an industrial collaborator and were used to define the model boundary conditions. Steady-state and transient simulations were conducted, using boundary conditions defined from time-averaged measurement data. The predicted shell profiles demonstrated good agreement with thickness measurements of a breakout shell segment – recovered from the quarter-width location. Further examination of the results with measurement data suggests pseudo-steady assumption may be inadequate for modeling shell and flow field transition period following sudden changes in casting speed. An adaptive mesh refinement procedure was established to increase refinement in areas of predicted shell growth and to remove excess refinement from regions containing only liquid. A control algorithm was developed and employed to automate the refinement procedure in a proof-of-concept simulation. The use of adaptive mesh refinement was found to decrease the total simulation time by approximately 11% from the control simulation – using a static mesh.

This work includes the development of computational fluid dynamic (CFD) and finite element analysis (FEA) models to investigate fluid flow , solidification, and stress in the shell within the mold during continuous casting. The flow and solidification simulation is validated using breakout shell measurements provided by an industrial collaborator. The shell can be obtained by the solidification model and used in a FEA stress model. The stress model was validated by former research related to stress within a solidifying body presented by Koric and Thomas. The work also includes the application of these two models with a transient solidification model and a carbon percentage investigation on both solidification and deformation.

<div>Glutamate is the principal excitatory neurotransmitter in the central nervous system. As one of the most abundant neurotransmitters, glutamate plays an essential role in many processes of the central nervous system and beyond. As a result, any disruption that causes an abnormal glutamate level can significantly impact the central nervous system's neurological functions. Glutamate excitotoxicity is a neuropathology that persists in many neurodegenerative disorders such as Parkinson's and Alzheimer's disease as well as in the traumatic brain and spinal cord injuries. Thus, the ability to obtain precise information about the extracellular glutamate level in the living brain and spinal cord tissue may provide new insights into the fundamental understanding of glutamate in neurological disorders and neurophysiological phenomena.</div><div><br></div><div>Conventional bioanalytical techniques that characterize glutamate levels <i>in vivo</i> have a low spatiotemporal resolution that has impeded our understanding of this dynamic event. The electrochemical sensor has emerged as a promising solution that can satisfy the requirement for highly reliable and continuous monitoring methods with an excellent spatiotemporal resolution for the characterization of extracellular glutamate concentration. In this thesis, I present various amperometric biosensors fabricated using a simple direct ink writing technique for<i> ex vivo </i>and <i>in vivo</i> glutamate monitoring.</div><div><br></div><div>The amperometric biosensor is fabricated by immobilizing glutamate oxidase on nanocomposite electrodes made of platinum nanoparticles, multiwalled carbon nanotubes, and a conductive polymer. The biosensors demonstrate good sensitivity and selectivity that can be inserted into a spinal cord and measure extracellular glutamate concentration. Additionally, another type of glutamate biosensor is fabricated from commercially available activated carbon with platinum microparticles. We utilize astrocyte cell culture to demonstrate our biosensor's ability to monitor the glutamate uptake process. We also present a direct measurement of glutamate release from optogenetic stimulation in mouse primary visual cortex brain slides. </div><div><br></div><div>Moreover, we explore a new type of material, perovskite nickelate-Nafion heterostructure, to fabricate biosensors and measure glutamate inside the mouse brain. Finally, by utilizing the nanocomposite ink and direct ink writing technique, we also fabricate the gold-ruthenium non-enzymatic glucose biosensor. We apply a modified Butler-Volmer non-linear model to evaluate the impact of geometrical and chemical design parameters of non-enzymatic biosensor performance. </div><div><br></div>

Recent advances in atomically thin two-dimensional materials have led to various promising technologies such as nanoelectronics, sensing, energy storage, and optoelectronics applications. Graphene with sp2-bonded carbon atoms densely packed in a honeycomb crystal lattice has attracted tremendous interest with excellent electrical, optical, mechanical, and chemical properties. In this work, graphene’s mechanical properties, chemical properties, and piezoelectric properties are explored as graphene is implemented in the automotive electrical distribution system. Graphene is useful in friction reduction, corrosion protection, and piezoelectric energy harvesting cell improvement. Besides graphene, transition metal dichalcogenides (TMDs), which are the metal atoms sandwiched between two chalcogen atoms, have also attracted much attention. Unlike graphene, many TMDs are semiconductors in nature and possess enormous potential to be used as a potential channel material in ultra-scaled field-effect transistors (FETs). In this work, chemical doping strategies are explored for the tunnel FETs applications using different metal phthalocyanines and polyethyleneimines as dopants. TMDs FETs can also be used as a selective NO₂ gas sensor with a polydimethylsiloxane filter and a highly sensitive photo-interfacial gated photodetector application.

FeCrAl alloys are being investigated as candidate materials for replacing zirconium based alloys as nuclear reactor fuel cladding because of their superior high temperature oxidation resistance in steam environments. Unirradiated FeCrAl as well as Fe²⁺ ion irradiated FeCrAl to a peak dose of 20DPA were mechanically tested and compared against each other. Nanohardness tests were performed on both the unirradiated and irradiated conditions and it was found that the irradiated alloy was about 1GPa harder than its unirradiated counterpart. TEM <i>in situ</i> tensile tests were performed using the Bruker push to pull device alongside a PI95 Picoindenter on single crystals with grain orientations 001, 011 and 111. The unirradiated 001 grains tended to fail without yielding in a brittle manner while the irradiated 001 grain yielded and reached an ultimate tensile strength before failure. The unirradiated 011 grains behaved in a mixed manner, where one failed without yielding and one slipped many times before failing. The irradiated 011 grain yielded and failed quickly thereafter. The unirradiated 111 grain yielded, slipped and twinned before failing and both irradiated 111 grains slipped. Two general trends were observed. One, each unirradiated single grain was stronger than its irradiated counterpart. This trend is indicative of the ion irradiated microstructure facilitating bulklike mechanical behavior in the irradiated samples whereas the unirradiated samples exhibited mechanical size effects due to either the total lack of preexisting defects or the ability for existing defects to escape easily to the surface of the sample resulting in a pristine, defect free sample. Two, regardless of irradiation condition, the 001 grain orientation was brittle, the 011 grain orientation deformed in a mixed brittle/ductile manner and the 111 grain orientation was ductile through all tests. These results are indicative of the geometry of the BCC crystal structure and the slip system involving these orientations.

<p>Ni-based superalloys continue to exert themselves as the industry standards in high stress and highly corrosive/oxidizing environments, such as are present in a gas turbine engine, due to their excellent high temperature strengths, thermal and microstructural stabilities, and oxidation and creep resistances. Gas turbine engines are essential components for energy generation and propulsion in the modern age. However, Ni-based superalloys are reaching their limits in the operating conditions of these engines due to their melting onset temperatures, which is approximately 1300 °C. Therefore, a new class of materials must be formulated to surpass the capabilities Ni-based superalloys, as increasing the operating temperature leads to increased efficiency and reductions in fuel consumption and greenhouse gas emissions. One of the proposed classes of materials is termed refractory complex concentrated alloys, or RCCAs, which consist of 4 or more refractory elements (in this study, selected from: Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, and W) in equimolar or near-equimolar proportions. So far, there have been highly promising results with these alloys, including far higher melting points than Ni-based superalloys and outstanding high-temperature strengths in non-oxidizing environments. However, improvements in room temperature ductility and high-temperature oxidation resistance are still needed for RCCAs. Also, given the millions of possible alloy compositions spanning various combinations and concentrations of refractory elements, more efficient methods than just serial experimental trials are needed for identifying RCCAs with desired properties. A coupled computational and experimental approach for exploring a wide range of alloy systems and compositions is crucial for accelerating the discovery of RCCAs that may be capable of replacing Ni-based superalloys. </p> <p>In this thesis, the CALPHAD method was utilized to generate basic thermodynamic properties of approximately 67,000 Al-bearing RCCAs. The alloys were then down-selected on the basis of certain criteria, including solidus temperature, volume percent BCC phase, and aluminum activity. Machine learning models with physics-based descriptors were used to select several BCC-based alloys for fabrication and characterization, and an active learning loop was employed to aid in rapid alloy discovery for high hardness and strength. This method resulted in rapid identification of 15 BCC-based, four component, Al-bearing RCCAs exhibiting room-temperature Vickers hardness from 1% to 35% above previously reported alloys. This work exemplifies the advantages of utilizing Integrated Computational Materials Engineering- and Materials Genome Initiative-driven approaches for the discovery and design of new materials with attractive properties.</p> <p> </p> <p><br></p>

<p>Plasmonics with the capability to harness electromagnetic waves at a nanoscale can be utilized for multitude of applications in ultra-compact miniature optical devices. Plasmonic metasurfaces which are artificially designed sub-wavelength structures have gained unprecedented interest in being able to engineer and effectively modulate the amplitude and phase of the incident wave. Introducing randomness to such plasmonic metasurfaces can also advance possibilities for extraordinary wave manipulation. Hence, by exploiting the plasmonic response of the ordered and disordered metasurfaces, we can design high performance devices for nanoscale optics.</p> <p>Aiming to provide a holistic solution to the current device limitations and bio-compatibility, my research focuses on non-toxic and environment-friendly coloration using plasmonic disordered metasurfaces. These structures generate a broad range of long-lasting colors in reflection that can be applied to real-life artistic or technological applications with a spatial resolution on the order of 0.3 mm or less. Moreover, my research also deals with the possibility of even concentrating energy in the smallest phase-space volume in optics in the form of coherent radiation through designing nanolasers. The study of carrier dynamics and photophysics of the gain media can be extremely beneficial towards the practicability of these lasers. This work elucidates the evolution of different competing mechanisms for coherent lasing. The dynamic study and experimental demonstration of these devices and respective materials can therefore provide a novel aspect to fundamental and applied research.</p>

<div>The interactions of femtosecond lasers with gold targets were investigated with a numerical method combining molecular dynamics (MD) and the two-temperature model (TTM). Previous works using MD-TTM method did not consider all the thermodynamic parameters and the interatomic potential dependent of the electron temperature simultaneously. Therefore, we developed a LAMMPS function to achieve this. To accurately capture the physics behind the interactions, we also included the electron blast force from free electron pressure and the modified Fourier law with steep electron temperature gradient in our model. For bulk materials, a stress non-reflecting and heat conducting boundary is added between the atomistic and the continuum parts. The modified boundary force in our study greatly reduces the reflectivity of the atomistic-continuum boundary compared with its original form. Our model is the first to consider all these factors simultaneously and manage to predict four femtosecond laser ablation phenomena observed in the experiments. </div><div><br></div><div>In this dissertation, the thermodynamic parameters in the two-temperature model were extensively explored. We considered three different approaches to calculate these parameters: namely interpolation, <i>ab initio</i> calculation, and analytical expression. We found that simple interpolation between solid state and plasma state could lead to high level of inaccuracy, especially for electron thermal conductivity. Therefore, <i>ab initio</i> calculation and analytical expression were used for the calculation of the thermodynamic parameters in more advanced studies. The effects of electron thermal conductivity and electron-phonon coupling factor on electron and lattice temperatures were analyzed.</div><div><br></div><div>Our studies considered electron temperature dependent (ETD) and electron temperature independent (ETI) interatomic potentials. The ETI interatomic potential is easier to implement and therefore it is used in our phase change study to investigate the effects of target thickness on melting. Homogeneous melting occurred for thin films, while melting can be observed through the movement of the solid-liquid interface in thick or bulk materials. However, the ETI potential overestimated the bond strength at high temperatures. Therefore, ablation process was studied with the ETD potential. Three ablation mechanisms were found in our simulations at different laser fluences. Short nonthermal ablation was only observed at the ablation threshold. With increasing laser fluence, spallation was then seen. In high laser fluence regime, phase explosion occurred on the surface and coexisted with spallation.</div><div><br></div><div>Lastly, we researched on the effects of the delay time between two femtosecond laser pulses. Various delay times did not have much influence on melting depth. In low laser fluence regime, with increasing delay time, the target went through nonthermal ablation, to spallation and to no ablation. In high laser fluence regime, longer delay time encouraged phase explosion while suppressed spallation.</div>

<p>Thorium dioxide (ThO₂) and metallic uranium (alpha-U) represent important alternative nuclear fuels. Investigating the behavior of defects introduced into these materials in an irradiation environment is critical for understanding microstructure evolution and property changes. The objective of this dissertation is to investigate the clustering of point defects in ThO₂ and alpha-U under irradiation, into voids and prismatic dislocation loops as a function of irradiation dose rate and temperature. To achieve this, we have developed a mean-field cluster dynamics (CD) model based on reaction rate theory to predict the evolution of self-interstitial atom (SIA) and vacancy loops in neutron-irradiated alpha-U. Detailed atomistic simulations have been carried out using molecular dynamics (MD) to study the configuration of such loops and compute their energetics, which are essential parameters of the CD model. Bond-boost hyper-MD simulations have been performed to compute the diffusivity of uranium SIA and vacancies, which govern the kinetics of the clustering phenomenon. Another CD model has been demonstrated for proton-irradiated ThO₂, considering the clustering of Th and O SIA and vacancies into SIA loops and voids, respectively, with varying sizes and stoichiometry. The compositions of all SIA loops and voids dictated by crystallography of ThO₂ in its fluorite structure have been presented in their respective cluster composition space (CCS). The CD model solves the density evolution of off-stoichiometric loops and voids, with irradiation, in their respective CCS. MD simulations have been performed to compute the energetics of different clusters in their CCS, as parameters of the CD model. Temperature-accelerated MD simulations have been performed to compute the diffusivity of Th and O point defects, that dictates the kinetics of defect clustering on irradiation. In alpha-U, the CD predictions show an accumulation of small sized vacancy loops and the growth of SIA loops with irradiation dose, which closely fits the reported size distribution of loops in neutron-irradiated alpha-U by Hudson and coworkers. The CD predicted density of defect clusters in proton-irradiated ThO₂, shows the evolution of near-stoichiometric SIA loops in their CCS. The size distribution of SIA loops at high irradiation doses closely corresponds to the transmission electron microscopy (TEM) observations reported in the literature. Also, the CD model did not predict the growth of voids and vacancy clusters, which is consistent with findings in literature. The model was further used to predict the density of sub-nanometric defect clusters and point defects, on low-dose irradiation, that significantly impairs the thermal conductivity of ThO₂. An extensive TEM and CD investigation has also been carried out to study the growth and coarsening of SIA loop and voids during post-irradiation isochronal annealing of ThO₂ at high temperatures.</p>

Additive manufacturing (AM) introduces high variability in the microstructure and defect distributions, compared with conventional processing techniques, which introduces greater uncertainty in the resulting fatigue performance of manufactured parts. As a result, qualification of AM parts poses as a problem in continued adoption of these materials in safety-critical components for the aerospace industry. Hence, there is a need to develop precise and accurate, physics-based predictive models to quantify the fatigue performance, as a means to accelerate the qualification of AM parts. The fatigue performance is a critical requirement in the safe-life design philosophy used in the aerospace industry. Fatigue failure is governed by the loading conditions and the attributes of the material microstructure, namely, grain size distribution, texture, and defects. In this work, the crystal plasticity finite element (CPFE) method is employed to model the microstructure-based material response of an additively manufactured Ni-based superalloy, Inconel 718 (IN718). Using CPFE and associated experiments, methodologies were developed to assess multiple aspects of the fatigue behavior of IN718 using four studies. In the first study, a CPFE framework is developed to estimate the critical characteristics of porosity, namely the pore size and proximity that would cause a significant debit in the fatigue life. The second study is performed to evaluate multiple metrics based on plastic strain and local stress in their ability to predict both the modes of failure as seen in fractography experiments and estimate the scatter in fatigue life due to microstructural variability as obtained from fatigue testing. In the third study, a systematic analysis was performed to investigate the role of the simulation volume and the microstructural constraints on the fatigue life predictions to provide informed guidelines for simulation volume selection that is both computationally tractable and results in consistent scatter predictions. In the fourth study, validation of the CPFE results with the experiments were performed to build confidence in the model predictions. To this end, 3D realistic microstructures representative of the test specimen were created based on the multi-modal experimental data obtained from high-energy diffraction experiments and electron backscatter diffraction microscopy. Following this, the location of failure is predicted using the model, which resulted in an unambiguous one to one correlation with the experiment. In summary, the development of microstructure-sensitive predictive methods for fatigue assessment presents a tangible step towards the adoption of model-based approaches that can be used to compliment and reduce the overall number of physical tests necessary to qualify a material for use in application.