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Continuous scaling of complementary metal-oxide-semiconductor (CMOS) transistor technology over the past few decades following Moore’s law has led to significant enhancement in the speed and performance of computing architectures. In today’s world with high demand in data processing, CMOS scaling is focusing more on low power, cost-effective processes, and high performance to meet the requirements of high-end computations. To meet the high computation demands, reengineered, high performance, and low power device structures were necessary, and hence field effect transistors (FET) structures have evolved from planner to multi-gate, and gate all around (GAA) structures. Also, other than the very well matured silicon electronics, advanced technologies allowing heterogeneous integration of different materials systems (e.g., Si, Ge, III–V, and II-VI groups) have been developed. Though heterogeneous integration of silicon electronics with compound semiconductors can be beneficial, such developments in hybrid integration cannot address the fundamental limitations of the pure CMOS circuits, the resistive capacitive (RC) delay associated with metallic wires, and the dielectric gate delay associated with FETs. These delays ultimately limit the data speed and energy consumption.
In this research work we have explored novel applications in electronic-photonic integrated circuits of a special type of metal-semiconductor-metal (MSM) photoconductive structure known as the light effect transistor (LET) which can emulate the current voltage characteristics of a FET but with much better performances in terms of switching speed (considering carrier transit delay), energy consumption per switch and Ion/Ioff ratio, and also other optoelectronic functions like optical iv
logic gates, optical summation, optical amplification, and optoelectronic analog operation using LETs, which cannot be done using FETs. The LET can provide extremely fast optoelectronic switching (of the order of ~ ps), and its simplistic structure does-not add unwanted parasitic and leakages which are common in all gated FETs.
To understand the superiority of LETs over FETs, particularly the potential vast performance improvement in a hybrid integrated circuit of the two types of devices, we have explored the possibilities of LETs to replace some FETs in various pure electronic circuits. Using analytical relations and simulations, we have extensively studied the effect of replacing the access FETs in a 6T SRAM (six transistor static random-access memory) structure with LETs and have made some drastic changes in the hybrid 6T FET - LET structure by replacing the whole electrical word line with an optical waveguide (OWG). We have also proposed a prototype novel hybrid 3D integration scheme for the 6T SRAM architecture where all the typical electronic and optoelectronic components (4T FET latch, access LETs, bit lines, peripherals, etc.) will be placed on a single electronic layer while photonic components (OWGs, on-chip lasers to drive the OWGs, etc.) will be placed separately on the photonic layer with regularly spaced openings that provide the optical signal for switching four LETs grouped together from two adjacent hybrid 6T cells in the electronic layer. Also a fully functional FET - LET hybrid SRAM bit cell with superior performance has been designed and implemented using the mixed-mode design environment of Synopsys Sentaurus TCAD.
Infectious diseases pose a significant threat to public health worldwide as evidenced by the recent coronavirus 2019 (COVID-19) pandemic. Despite significant human losses, the advent of web-accessed, map-based “data dashboards” that can monitor disease outbreaks, proved essential in managing public health responses. In many cases, the backend of these dashboards employs basic mapping functionality, displaying counts or rates. As the pandemic advanced, the identification of elevated rates was increasingly important in the geographical allocation of public health resources. However, such maps miss the opportunity to provide accurate information to policy decision makers such as the rate of disease spread, cyclicity, direction, intensity, and the risk of diffusion to new regions. Space-time geoanalytics, when coupled with rich visualizations, can address these shortcomings. Moreover, when implemented over the web, such functionality can be accessed from virtually anywhere.
This dissertation presents a web-based geographic framework for detecting and visualizing explicit space-time clusters of infectious diseases. First, I conduct a systematic review of the literature around the theme of space-time cluster detection for infectious diseases to identify state-of-the-art techniques that should be included in the proposed web-based framework. Second, I develop a tightly coupled, web-based analytical framework for the detection of clusters of infectious diseases using interactive and animated 3D visualizations to aid epidemiologists in readily and adequately uncovering the characteristics of space-time clusters. As a proof of concept, I populate the framework with COVID-19 county-level data for the 48 contiguous states in the US, and demonstrate data retrieval and storage, space-time cluster detection analysis, and 3D visualization within an open source WebGIS environment. Third, I evaluate the prototype in two steps: 1) present this and two existed COVID-19 systems to a group of infectious diseases experts and solicit feedback, 2) and evaluate functionalities on the prototype by conducting a user study with graduate students in a setting of online surveys.
This tightly coupled approach facilitates the detection of space-time clusters of diseases in a computationally acceptable timeframe. The characteristics of this framework (generic, open source, highly accurate, modifiable) will enable low-cost monitoring of the spatial and temporal trends of diseases causing high risks of infection.
This dissertation explores Black/African American students’ perceptions of college readiness through student demographic questionnaires, semi-structured interviews, and focus group data. One objective of this study was to explore how advanced coursework contributed to the college readiness of Black students. Another objective was to examine academic writing readiness for Black students, which is an under-researched aspect of college readiness. The findings indicated that having a fostered college mindset, collegiate academic exposure, and being provided foundational skills and knowledge were aspects of advanced course participation that contributed to postsecondary success for the participants. In terms of writing readiness, writing opportunities and writing skill enhancement contributed to the participants’ college writing readiness and success. However, misalignment between high school and college expectations, mismatch of collegiate level writing expectations, and lack of citation knowledge were other areas related to college readiness that also emerged from the data. This study provides implications for policy, teachers, school personnel, and teacher educators.
Organic-inorganic hybrid perovskites are viewed as a cost-effective alternative for photovoltaic devices, among other applications. Solution and low-temperature processing have gathered much attention for this class of materials. However, the stability and variability of reported fundamental properties have limited their progress toward practical applications. They suffer from environmental instabilities and undergo photochemical processes under light illumination that ultimately cause material degradation. The photostability of methylammonium lead triiodide (MAPbI3) is probed by Raman spectroscopy, revealing that photodecomposition scales with surfaces and grain boundaries. Surface or defective regions are also shown to affect carrier transport properties and act as scattering centers for low-energy emitted photons. The disordered nature of MAPbI3 and the additional structural defects of polycrystalline films result in restricted carrier diffusion lengths on the order of a micron determined by photoluminescence imaging, despite relative emission yields being much higher than an inorganic semiconductor like GaAs. In the literature, carrier diffusion lengths for MAPbI3 have been significantly larger when determined by photocurrent measurements. However, conducting photoluminescence imaging on polycrystalline films under an applied bias illustrates that carrier diffusion is still relatively small. Carrier drift or the possible reabsorption of traveling low-energy photons reaching the perovskite/electrode interface can give a false impression of a much longer carrier diffusion within MAPbI3.
The “Urban Stream Syndrome” is a term that refers to a group of predictable negative impacts to stream ecosystems due to the alteration of the natural hydrologic regime associated with urbanization including increases in the volume and intensity of storm water inputs to streams, channel erosion, streambed sedimentation, and nutrient and pollutant concentrations. These negative impacts of urbanization degrade the habitat available to the aquatic biota in streams. The decline in aquatic insect taxa richness due to urbanization has been well documented. However, the impact of the stressors associated with the increased stormwater flashiness to the composition of the aquatic insect assemblages’ taxa and trait richness and diversity is not well known.
For my dissertation, I proposed three research studies designed to improve the understanding of how the increased stormwater from urban areas impacts the aquatic insect assemblages’ taxa and trait richness and diversity. To do this, I first examined a 26-year data set to study the impact of land use changes on biodiversity and ecosystem function in stream ecosystems in watersheds that span a gradient of impervious cover and stream habitat conditions. Next, to better understand the impact of urbanization on biodiversity and ecosystem function, I examined the relationship between aquatic insect taxa and trait richness and diversity and stream habitat diversity at the watershed scale and the importance of microhabitats at the reach scale. Finally, to better understand stormwater impacts on aquatic insect assemblages, I compared macroinvertebrate taxa and trait richness and diversity in 2 adjacent headwater tributaries that received stormwater runoff through different processes (stormwater infrastructure verse natural overland and subsurface processes).
Organizations often struggle to engage their workforces despite various known benefits and predictors of employee engagement. The current study examined a new approach to promote employee engagement—1:1 meetings—which are commonly occurring, theoretically grounded, and understudied. Leveraging job-demands resources and self-determination theories, it was hypothesized that the quantity (i.e., frequency) and quality (i.e., presence of manager task- and relations-oriented behaviors) of 1:1 meetings promote direct report engagement by satisfying direct reports’ basic psychological needs. The proposed moderated mediation model was tested with data collected from two time-separated online surveys (N = 303). Results suggest that 1:1 meeting quality—particularly manager relations-oriented behaviors—plays a stronger role in promoting direct report engagement as compared to 1:1 meeting quantity—with the important caveat that these meetings happen at least monthly. Results also suggest that 1:1 meetings are conceptually distinct from and can promote direct report engagement above and beyond other manager-direct report meetings and interactions by better supporting direct reports in a synchronous and individualized manner. Together, the current study supports 1:1 meetings as a critical tool managers can leverage to promote their direct reports’ engagement, while also contributing to both the meeting science and engagement literatures.
With the evolution of gear design requirements for new applications, classical gear inspection based on a time-consuming line-oriented tactile measurement must be replaced with a more rapid, areal inspection that can capture complex modern gear modifications. Triangulation-based optical instruments provide a promising path to meet new gear metrology demands with respect to access to the gear flanks and having sufficient speed and accuracy. In triangulation sensor measurement, the image position of a laser line strip on the sensor is analyzed to find the measured geometry. This image of the line on the sensor is calculated through a peak detection algorithm that produces a 'ridge line,' which is the line in the x-y sensor domain with the highest light intensity.
The physics of optical measurement dictates that speckles and scattered light exist during an optical inspection. As a result, when a triangulation sensor is used, the deflection of the scattered light may cause inaccurate peak detection and, therefore, large form deviations in the reconstructed (measured) geometry. In addition, multiple light reflections that influence point calculations from an optical measurement must be detected, eliminated, or remedied. This research provides an improved mathematical approach to ridge line detection in each sensor frame, to detect the peak position of that frame even more accurately. This algorithm is used to measure four reference geometries to evaluate its influence on point clouds from surface measurements when compared to the embedded (OEM) algorithm.
This dissertation offers the improved fidelity of triangulation sensor measurements for optical inspection by developing a novel mathematical approach. It can be used in the future closed-loop control process where the new gear production processes require fast-optical measurement and evaluation processes to trace back from the produced gear geometry to the manufacturing process. This can be achieved by equipping the manufacturing machine with suitable optical measuring devices, an appropriate evaluation strategy, and an inline inspection.
All-solid-state batteries (ASSBs) are considered promising candidates for next-generation batteries due to their excellent safety performance guaranteed by inorganic solid electrolytes (SEs) with the non-flammability nature, as well as the greatly increased energy density enabled by the adoption of lithium metal anode. Unlike conventional lithium-ion batteries (LIBs) using liquid electrolytes, all the components within the ASSBs system, including the composite cathode, lithium anode, and solid electrolyte, are solid-state. Solid-solid interfacial contacts within ASSBs, such as the dendrite-electrolyte interface and electrode-electrolyte interface, are the origin of interfacial instability issues. The interfacial instability problems mainly exhibit in the form of lithium dendrite growth-induced short circuits and interfacial debonding failure inside composite cathode, which are the major hurdles on the road towards the large-scale commercialization of ASSBs. Experimental characterizations are limited by the coupling of the solid nature of SE (vision overlap), and ultrasmall length scale. Therefore, versatile and physics-based models to describe the electrochemical behaviors of the ASSBs are in pressing need.
Herein, considering the highly multiphysics nature of ASSB behaviors, fully coupled electrochemo-mechanics models at different scales are developed to investigate the underlying mechanism of dendrite growth and interfacial failure. From the energy conservation perspective, the electrochemical-mechanical phase-field model at the electrolyte scale is firstly established to explore the dendrite growth behavior in polycrystalline SE. The newly formed crack and the grain boundary are found to be the preferential dendrite growth paths, and stacking pressure affects the driving force for both dendrite growth and crack propagation. Next, the cell-scale multiphysics modeling framework integrating the battery model, mechanical model, phase-field model, and short-circuit model is developed to study the entire process from battery charging to dendrite growth and to the final short circuit. The governing effects from various dominant factors are comprehensively discussed. Further on, inspired by the “brick-and-mortar” structure, the strategy of inserting heterogeneous blocks into SEs is proposed to mitigate dendrite penetration-induced short circuit risk, and the overall dendrite mitigation mechanism map is given. Finally, the three-dimensional fully coupled electrochemical-mechanical model is developed to investigate the interfacial failure phenomena, taking into account the electrochemical reaction kinetics, Li diffusion within the particle, mechanical deformation, and interfacial debonding. The randomly distributed LiNi1/3Co1/3Mn1/3O2 primary particles result in the anisotropic Li diffusion and volume variation inside the secondary particle, leading to significant nonuniformity of the Li concentration, strain, and stress distributions. This also serves as a root cause for the internal cracks or particle pulverization. The particle volume shrinkage under the constraint of the surrounding SE triggers the interfacial debonding with increased interfacial impedance to degrade cell capacity. This study explores the dendritic issue and mechanical instability inside ASSBs from the multiphysics perspective at different scales, obtaining an in-depth understanding of the electrochemical-mechanical coupling nature as well as providing insightful mechanistic design guidance maps for robust and safe ASSB cells.
All-solid-state batteries (ASSBs) are considered promising candidates for next-generation batteries due to their excellent safety performance guaranteed by inorganic solid electrolytes (SEs) with the non-flammability nature, as well as the greatly increased energy density enabled by the adoption of lithium metal anode. Unlike conventional lithium-ion batteries (LIBs) using liquid electrolytes, all the components within the ASSBs system, including the composite cathode, lithium anode, and solid electrolyte, are solid-state. Solid-solid interfacial contacts within ASSBs, such as the dendrite-electrolyte interface and electrode-electrolyte interface, are the origin of interfacial instability issues. The interfacial instability problems mainly exhibit in the form of lithium dendrite growth-induced short circuits and interfacial debonding failure inside composite cathode, which are the major hurdles on the road towards the large-scale commercialization of ASSBs. Experimental characterizations are limited by the coupling of the solid nature of SE (vision overlap), and ultrasmall length scale. Therefore, versatile and physics-based models to describe the electrochemical behaviors of the ASSBs are in pressing need.
Herein, considering the highly multiphysics nature of ASSB behaviors, fully coupled electrochemo-mechanics models at different scales are developed to investigate the underlying mechanism of dendrite growth and interfacial failure. From the energy conservation perspective, the electrochemical-mechanical phase-field model at the electrolyte scale is firstly established to explore the dendrite growth behavior in polycrystalline SE. The newly formed crack and the grain boundary are found to be the preferential dendrite growth paths, and stacking pressure affects the driving force for both dendrite growth and crack propagation. Next, the cell-scale multiphysics modeling framework integrating the battery model, mechanical model, phase-field model, and short-circuit model is developed to study the entire process from battery charging to dendrite growth and to the final short circuit. The governing effects from various dominant factors are comprehensively discussed. Further on, inspired by the “brick-and-mortar” structure, the strategy of inserting heterogeneous blocks into SEs is proposed to mitigate dendrite penetration-induced short circuit risk, and the overall dendrite mitigation mechanism map is given. Finally, the three-dimensional fully coupled electrochemical-mechanical model is developed to investigate the interfacial failure phenomena, taking into account the electrochemical reaction kinetics, Li diffusion within the particle, mechanical deformation, and interfacial debonding. The randomly distributed LiNi1/3Co1/3Mn1/3O2 primary particles result in the anisotropic Li diffusion and volume variation inside the secondary particle, leading to significant nonuniformity of the Li concentration, strain, and stress distributions. This also serves as a root cause for the internal cracks or particle pulverization. The particle volume shrinkage under the constraint of the surrounding SE triggers the interfacial debonding with increased interfacial impedance to degrade cell capacity. This study explores the dendritic issue and mechanical instability inside ASSBs from the multiphysics perspective at different scales, obtaining an in-depth understanding of the electrochemical-mechanical coupling nature as well as providing insightful mechanistic design guidance maps for robust and safe ASSB cells.
Graphene is a monoatomic thick sheet of sp2-hybridized carbon atoms tightly packed in a honeycomb lattice structure. Since its discovery, it has drawn extensive attention to the science community for its unique 2D structure and has been studied for both basic science and commercial applications due to its extraordinary thermal, optical, and mechanical properties. In this research, we employed molecular dynamics simulations and machine learning methods to study mechanical and fracture properties of graphene-like two-dimensional materials (i.e.; C3N, bicrystalline graphene, and polycrystalline graphene). Molecular dynamics (MD) simulations are used to extract the traction-separation laws (TSLs) of symmetric grain boundaries of bicrystalline graphene. Grain boundaries with realistic atomic structures are constructed using different types of dislocations. The TSLs of grain boundaries are extracted by using cohesive zone volume elements (CZVEs) ahead of the crack tip. The areas under the traction-separation curves are used to calculate the separation energy of the grain boundaries. The results show that as the grain boundary misorientation angle increases the separation energy of the grain boundaries decreases. The impact of temperature on the traction separation laws is studied. The results show that, with an increase of the temperature from 0.1 K to 300 K, the separation energy first increases to reach its peak at around 25 K and then slightly decreases. Finally, a deep convolutional neural network model has been developed to predict the mechanical and grain properties of polycrystalline graphene. The data required for training our machine learning model is generated using molecular dynamics simulations by modeling the behavior of polycrystalline graphene under uniaxial tensile loading. More than 2000 data points are generated for graphene sheets of different grain sizes and grain orientations. The goal is to train the network such that it can predict the Young's modulus and fracture stress of graphene sheets by analyzing an image of the polycrystalline sheet.
Molecular dynamics simulations are also used to study the mechanical and fracture properties of C3N, a graphene-like two-dimensional material. The impact of initial crack orientation on the crack path is studied by applying tensile strain to C3N sheets containing initial cracks in the armchair and zigzag directions. The results show that the cracks grow by creating new surfaces in the zigzag direction. The impact of temperature and strain rate on Young's modulus and fracture stress of C3N are studied. The capability of Griffith theory, and quantized fracture mechanics (QFM) in predicting the fracture strength of C3N is studied. The molecular dynamic results indicate that Griffith theory cannot predict the fracture strength of C3N if the crack length is shorter than 9 nm. The notch effects on the fracture strength of C3N is studied and it is shown that notch effects are important in predicting the fracture strength of C3N. Using the Rivling-Thomas method, the molecular dynamics simulations predict a critical energy release rate of 10.982 Jm-2 for C3N.
