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Dense and porous Silicon Carbide (SiC) ceramics and composites are used in a wide range of applications that require high thermal, mechanical, and electrical stability, excellent corrosion, and wear resistance. However, manufacturing of SiC through conventional powder metallurgy technique techniques is often challenging due. Due to the covalent bonding between Si and C, they have a high melting point. Hence high temperatures, pressures, and controlled atmospheres are required during sintering to manufacture SiC ceramic with good mechanical and thermal strength. Other techniques to manufacture SiC at relatively low temperatures involve thermal oxidation, pressureless sintering, and the addition of sintering additives. Some applications like biological scaffolds, ballistic armor, space mirror substrates, and ceramic filters involve complex geometries. Manufacturing of complex geometries through the conventional route involves machining or molding. Machining SiC is a challenge due to its extreme hardness and abrasiveness. Molding a pre-form utilizes polymer resin which can cause shrinkage to the final product. upon debinding and sintering. Hence, the additive manufacturing route is considered feasible for the manufacturing of SiC ceramics or composites. Additive manufacturing (AM) enables 3D printing of complex geometries from a CAD model. Multiple direct AM methods were realized for the printing of SiC such as selective laser sintering (SLS), selective laser melting (SLM), stereolithography (SL), direct ink writing (DIW), and binder jetting (BJ). Among these techniques, the binder jetting technique was found to be easier to manufacture complex geometries of SiC as it does not require, i) polymer additives that cause shrinkage of the part upon sintering and it doesn’t require, ii) high laser power to melt SiC, and iii) ceramic slurry, where the amount of ceramic used is less. Binder jetting also allows the mixing of different ceramic particles and additives that can help in the densification and strengthening of the printed part. In this work, the following areas are addressed: i) a route for densifying and strengthening the powder bed binder jet-printed SiC through the mixing of particles of different sizes, formation of siloxane bonding, secondary surface modification, and sintering, ii) strengthening and densification of SiC composites using mineral binders using powder metallurgy technique, and iii) realizing the properties of SiC-mineral binder composites for space mirror and thermal applications. Part (ii) of the project was preliminary work done in order to realize the outcomes of SiC-mineral binder composites in strengthening so that it can be adopted into additive manufacturing mentioned in part (i). Future work will involve the inclusion of SiC-mineral binders into the feedstock in a powder bed binder jet in order to reduce the voids between the interspace of SiC particles and to have a strong interfacial region comprising of mineral binders that can fuse the SiC particles together and densify the printed part. This eliminates the need for the post-processing techniques such as melt infiltration, polymer impregnation, or chemical vapor infiltration.
SiC ceramics are 3D printed into cylindrical discs in a powder bed binder jet using a water binder. In this method, SiC of an average particle size of 40 µm was surface activated with NaOH to form a silica gel layer at room temperature, to which, 30% of 2 µm and 600 nm SiC particles were added and mixed homogeneously through milling. The presence of OH- ions in silica gel, creates a repulsion between SiC particles which eliminates agglomeration of particles upon spreading. The mixing of coarse and fine particle sizes reduced the percentage porosity by 50%. The as-printed green part was heat treated to 650 °C for 5h to create siloxane bonding which provided an improved handling strength. The heat-treated parts were then impregnated in various concentrations of NaOH to create silica gel through secondary surface activation. SEM images showed that the impregnated samples had more silica nucleation droplets that gave rise to silica nanowires upon sintering at temperatures between 800 °C – 1000 °C. The silica nanowires are responsible for fusing the SiC particles and bridging the pores. The optimum NaOH concentration for secondary surface activation, sintering temperature, and dwell time were determined. A 100% increase in the strength of the SiC was obtained in the samples heat treated at 650 °C, impregnated in 20% NaOH, and sintered at 1000 °C for 24h. Moreover, the formation of nanowires under an oxygen environment proved that silica nanowires can be formed at a temperature as low as 800 °C, and in air, the discs are oxygen deprived which hinders the growth of silica nanowires. Hence the mechanism of the growth of nanowires was found to be similar to the solid-vapor phase deposition. Cordierite and spodumene are silicate minerals that are known for their excellent thermal properties namely nearly zero thermal expansion coefficient. SiC is a ceramic with excellent mechanical and thermal properties. SiC, Cordierite, and Spodumene are materials that are considered for space mirrors, mirror substrates, and high-temperature applications. However, the glass ceramic form of Cordierite and Spodumene are less considered for space applications due to their poor stiffness and fracture toughness. On the other hand, SiC is highly considered for such applications however manufacturing them is a challenge considering their high melting point and hardness. Hence, in this work, a combination of SiC and the mineral format of cordierite and spodumene is introduced as SiC-mineral binder composites. SiC-mineral binder composites are 80% SiC and 20% Cordierite or Spodumene minerals prepared through the powder metallurgy technique. SiC-mineral binder composites were found to have good mechanical and thermal properties and can be a promising candidate for space mirror applications. SiC-mineral binders were combined with 1% of NaOH, pressed at 250 MPa, and heat treated to 1200 °C for 8 h. The SEM-EDX analysis showed a strong interfacial region of cordierite or spodumene fusing the SiC particles together. The fracture mechanism was found to be transgranular which is due to the strong interfacial bond that was created by the atomic diffusion of Si and Al at the grain boundary of SiC and the mineral interface. The characterization involves the comparison of SiC-mineral binders to the control SiC-cristobalite without mineral binders. The phase analysis from XRD showed the presence of cordierite, spodumene, and cristobalite phases. A transformation of β-SiC to α-SiC was also observed. A slight shift in the d-spacing, the lattice constants, and crystallite size was observed as a result of a solid solution of phases. The density and porosity of these composites were measured using Archimedes and mercury porosimetry. Further pore size analyses were done using SEM and ImageJ analysis. The results showed that the introduction of mineral binders reduced the pore size and the porosity percentage. The compressive strength of the SiC-Cordierite and SiC-Spodumene was 282.57 MPa and 184.58 MPa which was much higher than the control SiC-Cris, 97.45 MPa. The average compressive strength of SiC-Cord was three times higher than control SiC-Cris (p < 9.7 x 10-7) and two times higher than that of SiC-Spod (p <0.003). Moreover, the average compressive strength of the SiC-Spod was significantly higher than that of the control SiC-Cris (p <9.8 x10-7). Elastic modulus was found using the nanoindentation technique and was 380.54 GPa and 341.04 GPa for SiC-Cord and SiC-Spod composites. Thermal shock resistance is an important factor for materials to qualify for space applications. SiC-mineral composites showed excellent thermal shock resistance and dimensional stability when quenched from 1200 °C to room temperature. A thermal expansion coefficient of 3 x 10-6 /K was obtained for both SiC-Cord and SiC-Spod composites. The SiC-mineral composites were polished to a mirror finish and the surface roughness of areas comprised of SiC particles along with the mineral binder without pores measured using atomic force microscopy was 20.89 nm. The mean roughness of the SiC microconstituent in the SiC-Cord composite was found to be 2.37 ± 0.28 nm. Owing to these excellent thermos-mechanical properties, SiC-mineral binder composites are promising candidates for space mirror applications, mirror substrates, substrates for high-temperature devices, and catalytic converters. Also, porous SiC-mineral binder composites can be used as gas/fuel filters for automobile industries.
Recent advancements in vehicular technology aim to enhance traffic safety by warning drivers or automating driving tasks. Driver warning systems (DWSs) alert drivers to unsafe situations. Advanced driver assistance systems (ADASs) can actively control acceleration, braking, and steering, reducing the reliance on human drivers. Although vehicles with DWS and ADAS are expected to enhance safety, the effectiveness of these systems in real-world driving conditions with varying traffic and vehicle interactions remains a knowledge gap. This dissertation provides an analysis framework to identify factors influencing fatal crashes involving vehicles with varying DWSs and ADASs. The objectives include evaluating data on vehicles with various DWSs and ADASs, comparing factors affecting fatal crashes involving vehicles with and without these systems, and examining the influence of traffic and vehicle characteristics on safety. Logistic regression models are employed to analyze the data and identify factors affecting fatal crashes, considering different DWSs, ADASs, and crash types. The findings from this research contribute to improving traffic safety by enhancing the understanding of factors that influence fatal crashes involving vehicles with DWSs and ADASs. The results will assist in developing effective strategies to mitigate risks, improve the design of these technologies, and facilitate infrastructure planning for future adoption.
From the perspective of manufacturing, it is not always ideal to use conventional methods of surface and optical metrology. Most optical metrology systems require a stable and pressure-temperature controlled environment in a laboratory setting as they are sensitive to such disturbances. The main contributing factor to these levels of sensitivity is the presence of a reference mirror. In most interferometric systems, interference patterns are generated by overlapping the wavefield generated from the object being measured with that generated from a reference mirror. Different algorithms can be used further by modulating the interference patterns to generate three-dimensional surface maps. Similar setups and algorithms could be used to not only generate the surface maps but also the object complex wavefield which extends its applications in digital holography. The goal of this research is to develop interferometric holography systems that are robust to environmental effects and suitable for in-situ metrology in manufacturing processes. Part 1 of this dissertation focuses on developing a lateral shear interferometric holography system using a pair of geometric-phase (GP) gratings. Two designs are proposed which allowed for different shear selection strategies. The proposed designs are robust to environmental effects by virtue of their design as a self-referenced and common-path configuration. A polarized camera sensor is used to record the interferograms with different phase shifts. Using an alternating projection algorithm, the recorded intensity maps are used to estimate the object wavefield. The errors generated by the algorithm are studied as a function of the shears selected to record the interferograms using synthetic intensity maps for both designs. The correlation is investigated using spatial and frequency information density functions and the errors generated by both designs are compared. Part 2 investigates the limitations of selected shears from the perspective of the spatial information density function. The major outcome from Parts 1 and 2 is proof that the shear selection strategies, the shear amounts, and the shear orientations affect the wavefield reconstruction. This leads to Part 3 of the dissertation which focuses on the optimal selection of shears for this system. Due to the complexity of the equations that govern the effect of shears on the reconstruction of different surface frequencies, a statistical approach was used to optimize the shears based on simulations that reconstructed a defocused point source wavefield. A point source wavefield is used for these simulations because it is the ideal wavefield demonstrating the reconstruction of all possible frequencies within the field of view. The results were compared to frequency information density maps to correlate the results. Parts 1,2 and 3 show a complete work starting from exploring designs to identifying optimal shear settings for a coherent digital holography system to measure transmissive and reflective samples. Part 4 shows a secondary application for this system that uses the GP grating pairs to make a fringe projection system that is suitable for diffused surfaces. The proposed system provides flexibility to adjust the characteristics of the projected fringes easily by changing the space between the gratings and the grating pair orientation. Example measurements are presented, and the capabilities of the setup are demonstrated. The proposed design can produce adjustable fringe patterns with fringe spacing varying from large values to as small as sub-millimeter distances. The fringe orientation can also be changed, and the patterns can be projected on objects of a wide range of sizes without losing the fringe contrast.
Traditional cyber defense approaches lack the necessary agility to effectively counter stealthy and undetectable attacks, placing defenders at a disadvantage. In response, Active Cyber Deception (ACD) has emerged as a promising solution by dynamically orchestrating deceptive environments to mislead and corrupt attackers' decision-making processes. However, the development of efficient and effective deception systems requires the integration of human intelligence and comprehensive malware analysis to understand attack behaviors and automate deception strategies.
This dissertation presents three innovative approaches in the field of ACD. Firstly, DodgeTron combines dynamic analysis using symbolic execution tools and machine learning to automate the creation of deception schemes against malware by categorizing malware into known families and utilizing HoneyThings. Secondly, symbSODA performs dynamic analysis on real-world malware and data flow analysis to extract malicious sub-graphs (MSGs) and map them to the MITRE ATT&CK framework using Natural Language Processing. This enables the creation of a Deception Playbook for deceiving specific malicious behaviors with deceptive API hookings. Finally, ranDecepter integrates active cyber deception to identify ransomware in its early stages and employs binary orchestration methods to repurpose the malware as a channel for exhaustively transmitting encryption information (including keys) to the attacker, effectively depleting their available resources.
Comprehensive evaluations validate the accuracy and effectiveness of these approaches in deceiving adversaries, reducing analysis time, and mitigating malware threats. This research significantly contributes to the field of active cyber deception and offers efficient and scalable solutions for protecting digital systems against sophisticated adversaries.
Beta-lactamase proteins are major contributors to antibiotic resistance, rendering beta-lactam antibiotics ineffective against bacterial infections. The emergence of novel beta-lactamases with expanded substrate specificity poses a global health threat. This study utilizes computational techniques to investigate the mechanisms by which beta-lactamases expand their substrate specificity, enabling bacteria to resist new antibiotics. By exploring the relationship between protein dynamics and function, the impact of enzyme motion on substrate specificity is elucidated.
Molecular dynamics simulations are conducted and analyzed to identify the functional dynamics involved in substrate recognition in beta-lactamase. Dynamic signatures are identified using a novel approach called Supervised Projective Learning with Orthogonal Completeness (SPLOC). Increased flexibility in loops neighboring the enzyme's active site facilitates optimal interactions with different antibiotics through local conformational flexibility. Notably, dynamic signatures differ between protein-antibiotic systems, highlighting the complexity of antibiotic binding mechanisms. These dynamic signatures are demonstrated as viable predictors of antibiotic resistance in beta-lactamase enzymes.
A proof-of-concept is presented for designing de-novo peptides that target these regions, offering a potential new class of beta-lactamase inhibitors capable of hindering the motions necessary for substrate recognition. This approach presents a promising strategy for controlling beta-lactamase-mediated antibiotic resistance.
This dissertation seeks to improve the budget allocation process for economic mobility policy portfolios by leveraging multi-objective optimization as a decision support tool, accounting for population, political, social, and budgetary constraints. Economic mobility is measured as the difference in income between Black and White populations, known as the racial wealth gap. First, I run regression, mediation, and moderated mediation analyses to understand the impact of local authority, consolidation, local partisanship, unified government, and racial demographics on aid, budget expenditures and economic mobility. I then propose a novel application of multi-objective optimization1 to identify optimal mixes aimed at increasing economic mobility in urban cities. In doing so, I seek to improve decision support tools available to local urban governments. My work intends to enable local urban governments to leverage multi-objective optimization to guide their decisions regarding policy selection and budget allocation. Better informed policy processes lead to a better mix of policies, which allows for more holistic solutions with greater societal returns. This not only improves outcomes for residents; it also recovers waste in the governmental process, increasing effectiveness and efficiency.
In recent decades, the demand for ultra-precise optical components with intricate geometric profiles has increased dramatically. Traditionally, polymer-based lenses have dominated the industry, but due to the benefits of using glass components, the demand for ultra-precision glass aspherical components has been rising consistently. When producing aspherical glass components, however, conventional manufacturing processes become time-consuming and expensive. Precision glass molding (PGM) technology offers an alternate method of production for aspherical glass lenses and irregular optical products. Compared to the conventional manufacturing process, it has the advantages of high forming accuracy, short manufacturing cycles, low cost, and high-volume production. However, the process has a few drawbacks, such as lens profile deviations, stress birefringence, etc. Before the glass molding process can be a viable option for mass-producing optical components, these drawbacks must be addressed. As such, a coupled thermo-mechanical finite element model is developed in this dissertation to simulate the precision glass molding process on two distinct glass varieties, D-ZK3 (CDGM) and P-SK57 (Schott). A novel testing method is developed to precisely characterize the viscoelasticity of the glass material. It is demonstrated that the obtained material parameters accurately depict the experimental data at various molding temperatures. In addition, the material testing experiments are designed to be implemented on a glass molding machine, simplifying the development and characterization of different moldable glass materials. The obtained material parameters are implemented in the finite element model to predict the profile deviation in the molded lens and compared with experimental results. A mold compensation technique is used to correct the mold profiles. The lens molded on the modified molds is shown in fall within the tolerance specifications. However, it was observed that the process parameters used during the molding process have an influence on the deviations and the stresses in the molded lens. Therefore, it is essential to optimize the molding process prior to implementing mold compensation techniques. The developed numerical model is used to analyze the impact of various process stages and parameters on the optical quality of molded lenses. Based on the observations, a modified molding process was developed which is shown to minimize the influence of the molding parameters on the deviations and the residual stress. In addition, it was demonstrated that the modified manufacturing process reduces the total cycle time for producing a glass lens of comparable optical quality by more than 50%, reducing the manufacturing cost of a molded glass lens.
At-home DNA testing and sharing in public genealogy databases are becoming widespread. This will facilitate finding out ancestry, genetic relatives, biological parents, making new connections, advancing medicine, and determining predisposition to various diseases and health issues. While the biomedical community glorifies the uses of the genomics revolution, the expanded obtainability of such sensitive data has substantial implications for individual privacy as genes carry sensitive personal information about human traits and predispositions to any diseases. Furthermore, DNA data has identification capability (e.g., forensics) as well as reveals familial interconnections. However, commercial DNA testing is not vigorously governed by any laws and policies. The privacy implications of public DNA data sharing remain largely unexplored. This dissertation explores users' privacy concerns and proposes a method for communicating the risks to users to inform users when sharing their DNA data.
In the first study, we explored users' perceptions regarding DNA data. We asked about their views of at-home DNA testing and sharing, followed by their expected benefits and concerns. We also talked about public genealogy databases like GEDmatch. We focused on understanding the users' preferences and perceptions on the disclosure of their genetic information under the different types of platforms and entities. Our results show that users are mostly unaware and uncomprehending of the interconnected nature of genetic data. We noted users' general perceptions and focused on understanding their preferred privacy controls while sharing their DNA data, their desired settings, policies, and rules.
From this study, we identified the need to develop a privacy-enhancing technology such that the users can make an informed choice while sharing DNA data. We also found that several policies and settings should be to preserve the privacy of sensitive data. With these findings in mind, the ultimate objective of this dissertation is to design and implement privacy risk communication methods that aid users in comprehending the risks and benefits associated with sharing DNA data, as well as enhancing transparency in access control. To evaluate the effectiveness of our developed risk communication approach, we deployed it within an existing platform, allowing us to assess users' decision-making processes and gain a deeper understanding of the nature of DNA data.
Recent advancements in manufacturing and post-processing of optics with sub-aperture methods have enabled greater degrees of freedom to realize complex optical surfaces. Introduction of residual mid-spatial frequency (MSF) surface errors is a consequence of sub-aperture manufacturing. MSF errors have spatial frequencies between ‘low frequency’ form and ‘high frequency’ roughness with ambiguous bounds and with distributions that range from nearly random to highly deterministic and complex, depending on manufacturing method and conditions. MSF errors degrade optical performance and present significant challenges for both specification and optical performance predictions. The lack of specifications that directly connect to optical performance and the lack of widely available capabilities and procedures for modeling of generalized MSF errors are significant impediments to understanding their impacts in imaging systems.
The primary goals of this dissertation are (1) to explore and expand the connections between MSF specifications and optical performance for complex MSF error distributions, and (2) to demonstrate the implementation of these concepts within commercial software packages to enable the exploration of generalized MSF errors in optical systems. Results are addressed through three articles. The first article addresses the mathematical development and benefits of pupil-difference probability distribution (PDPD) moments to specify MSF errors and connect them to optical performance. The second article builds from this work to provide modeling procedures and explores their application to both random and deterministic MSF errors. The third article demonstrates the integration of these new concepts and methods into MATLAB™ and CODE V™, and their use on sample refractive and reflective imaging systems.
Gas Metal Arc Welding (GMAW) was investigated as a method for the rapid Wire Arc Additive Manufacturing (WAAM) of magnesium alloys. Magnesium AZ61a deposition wire was used to build multilayer walls, large blocks, and hollow cylinders using both high and low input-energy-rate (IER) parameters. The printed structures were analyzed to determine mechanical properties, microstructure, and porosity. Multilayer-wall samples printed at the same torch travel speed (TTS) showed a material yield strength (YS) of 120 MPa, independent of print orientation in relation to the applied tensile test pull force. The samples that were printed at a faster TTS showed the same response to loading conditions, but had a lower YS of 106 MPa, thus demonstrating how an increase in TTS lowers the YS of the deposited material. The stress-at-fracture for all these samples was between 260 MPa and 270 MPa. For the large multi-layer/multi-row (MRML) samples a YS of 120 MPa was also obtained but with lower stress-at-fracture points between 150 MPa and 220 MPa depending on print orientation, due to the presence of larger internal defects caused by bead overlap issues. Scanning Electron Microscope (SEM) analysis was performed on the fracture surface, showing ductile behavior in the fused regions and also uncovering material defects in the MRML samples such as trapped spatter, trapped gas bubbles, and cracks. Optical micrographs were obtained to analyze the microstructure of the samples in the heat affected zone (HAZ) as well as in the bulk material. Grain refinement from 38 µm pre-weld down to 10 µm and 28 µm post-weld was determined for MRML blocks and multilayer walls, respectively. Multilayer hollow cylinders were printed to test the ability of the method to produce closed-shape parts. These cylinders were produced at both high and low IERs and yielded parts with post-deposition machined wall thicknesses ranging from 1.5 mm to 4.5 mm. X-ray Computed Tomography (XCT) was performed to determine the porosity of these parts. The three sections analyzed showed a total-part percent porosity of 0.04 %, 0.039 %, and 0.07%. Larger individual defects, particularly at the closure-of-bead zone were detected, with a maximum single layer percent porosity of 0.8 %. Lastly, a Finite Element Analysis (FEA) model was created to simulate the deposition of the beads and the heat transfer throughout the process. The element activation feature in COMSOL Multiphysics was combined with the simulated torch path to model the deposition of the material. Heat transfer modes of conduction, radiation, and convection were conditionally assigned to the boundaries of the substrate and of the beads as functions of time and material deposition. The Goldak double-ellipsoid heat source was used as the input heating method for the substrate. To simulate the true-to-life GMAW process, where already molten material drops onto the substrate, a bead pre-heating function was created and applied to the inactive elements of the bead before it gets deposited during the simulation so that when the elements are activated above the weld pool they are at the correct temperature.
