VictorJuiz/thesis huggingface dataset:
Fundamental study and materials design on lithium metal anodes
Keywords: Chemical Engineering) degree committee member
Materials Science and Engineering.

Commercialized nearly three decades ago, the lithium-ion (Li-ion) battery has completely transformed the portable electronics industry and enabled the modern conveniences of social connectivity and mobile services. Nonetheless, current Li-ion batteries are quickly approaching their practical energy density limits. To make a lasting impact on emerging applications such as electric vehicles and grid-scale energy storage, an intimate understanding of materials chemistry in both existing and emerging batteries ---- such as those containing metallic Li ---- needs to be developed. In particular, metallic Li offers the largest specific capacity of all Li-based anodes, however, significant safety hazards caused by its high reactivity and dendritic growth during charge and discharge are major issues that prevent its practical applications, and need to be addressed. The ultimate tool for probing the atomic structure and chemistry of battery materials is the transmission electron microscope (TEM). Unfortunately, most high-energy battery materials such as metallic Li are extremely reactive in air, and unstable upon irradiation of high-energy electrons necessary for high-resolution imaging, causing them to quickly degrade during sample preparation and observation. In this thesis, I will not only present my study on using nanoscale engineering approaches to address the problems of the lithium metal anode, but also demonstrate the successful development of new tools to discover fundamental understandings. In Chapter 1, the working mechanisms and limitations of the state-of-the-art Li-ion battery chemistries will be introduced. An overview of promising new battery chemistries based on metallic lithium anode will also be provided. In Chapter 2, I report a novel synthesis method by reacting clean molten lithium foil directly with pure nitrogen gas to generate instantaneously a pinhole free and ionically conductive alpha-Li3N film directly bonded onto Li metal foil. This Li3N coating is chemically stable, isolating the reactive metallic lithium from liquid electrolyte, prevents continuous electrolyte consumption during battery cycling and promotes dendrite-free uniform lithium plating/stripping underneath. In Chapter 3, I introduce the basic imaging and working principles of the transmission electron microscope (TEM). In Chapter 4, I discuss the nanoscale corrosion process of lithium metal inside an environmental transmission electron microscope, allowing for high resolution monitoring of gas reactions in real time with chemical and structural information. In Chapter 5, I highlight the successful application of cryogenic electron microscope (cryo-EM) techniques on battery research for the rst time, demonstrating that cryo-EM is able to preserve Li metal in its native state after battery operation and stabilize the beam-sensitive material for atomic-resolution imaging. In Chapter 6, I will present my perspectives and outlooks for the future application of cryo-EM on battery research.
GaAs based long wavelength vertical cavity surface emitting lasers
Keywords: Materials Science and Engineering.

Long wavelength GaAs-based vertical-cavity surfaceemitting lasers that operate in continuous wave mode at and above room temperature are demonstrated.The VCSELs employ a dilute-nitride GaInNAsSb/GaNAs multiple quantum well active region, two n-doped Al- GaAs/GaAs distributed Bragg reflectors and a tunnel junction. Typical devices have threshold current densities of 2 kA/cm2. Single mode operation was achieved from a 7 mm aperture device. The devices have 3 dB frequencies above 4 GHz.
Gender Disparities and District-Level Distribution Shifts in Lung Cancer Rates in Beijing, China from 2000-2013
Keywords:  Department of Medicine
Community Health and Prevention Research
Department of Medicine
Stanford University
lung cancer
China
Beijing
gender
suburban
urban
district
disparity
Thesis

Background – Cancer has become the leading cause of death in China since 2010; with lung cancer, specifically, the most common incident cancer and leading cause of cancer death in the country. While prior research has focused on lung cancer rates and trends for men and women on a national and provincial scale within China, there has been little attention focused at the city- and district-level lung cancer rates, particularly in suburban areas.
Objective – This research examines whether trends in lung cancer incidence rates from 2000-2013 in Beijing indicate gender and district-level disparities.
Methods – Lung cancer incidence rates were determined and analyzed using data from the Beijing Cancer Registry. The data were analyzed for differences in rate changes over time after linear regressions for age-standardized incidence rates were determined.
Results – A total of 86,822 incident cases of lung cancer were identified. Substantial gender differences were observed: men had significantly higher age standardized lung cancer incidence rates than women in all 16 districts at every time point. Age-standardized lung cancer incidence rates increased over time in most districts, with evidence of a widening gender disparity, and the effects were more pronounced in suburban districts compared to urban districts.
Conclusion – The findings replicate a strong gender effect in lung cancer incidence in Chinese adults and reveal a particularly pronounced and growing effect in suburban districts. With attention to the very high smoking prevalence among Chinese men and concerns with air pollution as leading risk factors for lung cancer, these findings can inform preventive guidelines and public health policies for lung cancer prevention and treatment in Beijing to address this growing epidemic.
Gendered Agentic Language Patterns in Evaluative Text
Keywords: gender
language
symbolic systems
agentic
computational
performance
evaluation
Thesis

Differences in the way men and women are described in textual evaluations have been documented in letters of recommendation, professor evaluations, and performance evaluations. To this point, most studies have been done qualitatively. Several studies show that there are differences in the way men and women are described with agentic language, or language describing individual accomplishment with terms like execute, drive, or ambitious. These gendered differences can be consequential in terms of overall performance assessment. A recent study showed that agentic language increases with performance for men but only does so to a point for women before decreasing at the highest levels. Here, we apply computational techniques to show gendered differences in agentic language patterns hold at the scale of an entire technology company for the first time. We construct a lexicon based on relevant literature to obtain frequencies of agentic language terms in the corpus. We find that our analysis of agentic language patterns conceptually replicates a similar study’s findings using entirely new data and methods. We model the findings and find robust significance regarding a positive increase in agentic language for men rising to the top of the organization, but a decrease in agentic language in the reviews of top-performing women. We discuss the implications of a simple computational technique’s ability to capture this phenomenon. We consider potential future applications of this technique to other companies and discuss future research directions.
Gendering generations : redefining masculine life stages in modern China
Keywords: History.

This dissertation, drawing on archives and collections in China, Hong Kong, and Taiwan, is a cultural history of how Chinese masculine life stages changed and coexisted over the course of the tumultuous twentieth century. In four case study-based chapters, it shows how new ideas of age- and gender-appropriate behavior for Chinese men at differing life stages in disparate historical moments emerged in tandem. New life stages were created in dialogue with longstanding traditions, international debates, and emerging problems of modernity. Each chapter centers on a life stage that proved key to the formation of a new understanding of masculinity, beginning with boyhood in the early twentieth century and closing with old manhood at the turn of the twenty-first century. This life-cycle structure overlays the historical timeline on the biological timeline and reveals how gender norms interacted with ideas about age-appropriate behavior. It also illustrates how generationally-divided understandings of gender and life stages existed simultaneously. Rather than provide a comprehensive taxonomy of age-specific masculinities, Gendering Generations emphasizes the life stage as a category of analysis and identity in China's gender history.
Generalization of Anderson's theorem for disordered superconductors
Keywords: Physics.

The real world is imperfect, and disorder is an inherent feature of condensed matter systems. Whether or not the associated physical effects are of consequence for the properties we are interested in is a separate question. For example, conventional superconductors exhibit a robustness of the critical temperature and energy gap to non-magnetic impurities. This can be understood through Anderson's "theorem" of pairing exact time-reversed states; however, the theorem is not applicable to unconventional superconductors, such as the cuprates, with a sign-changing order parameter where the dirty limit is not well-defined. Moreover, the perturbative and effective medium approximations typically employed to treat the suppression of superconductivity are only valid under certain assumptions about the disorder ensemble and coherence length. While the simultaneous treatment of disorder and interactions typically requires numerical methods without uncontrolled approximations, there are interesting questions that emerge if we restrict ourselves to an exact treatment of disorder within BCS theory. The first part of the thesis focuses on the effect of disorder on the mean-field transition temperature Tc. In particular, we argue that mean-field Tc is always increased in the presence of disorder independent of order parameter symmetry, disorder strength, and spatial dimension. This can be understood through an analogy with Lifshitz tails is disordered semiconductors where rare regions conducive to bound states produce exponential tails in the density of states. While this is valid as a strict mathematical statement, the physical content only becomes relevant for short-coherence length superconductors. We then revisit the conventional wisdom that the overdoped cuprate phase diagram can be described entirely by dirty d-wave BCS theory. An extensive mutual inductance experiment probing the superconducting dome and overdoped quantum critical point has provided compelling evidence for a vanishing superfluid stiffness as Tc --> 0 in the ultra-clean limit. The drop in superfluid density without the usual signatures of pair-breaking disorder suggests a simple mean-field approach is at least partially incomplete. To address the applicability of dirty d-wave BCS theory in the overdoped regime, we compute the superfluid density for various disorder ensembles that are microscopically motivated by the chemistry of the cuprates. We find that the disorder models can capture some features observed the experiments, but typically require unrealistically high impurity concentrations. The latter part of this thesis involves other projects on strongly correlated systems including computations for thermal conductivity and spin susceptibility for chiral p-wave models of strontium ruthenate 214, a DMRG study of the t1-t2-J1-J2 model on a 4-leg ladder, and a phenomenological model of twisted bilayer graphene.
Generative Bayesian networks for conceptual aircraft design
Keywords: Aeronautics and Astronautics.

Conceptual aircraft design, with its basis in engineering design, is an open-ended problem in which human designers synthesize solutions to meet a set of requirements. This open-ended prob- lem inherently necessitates an iteration process combining creation and testing. Designers approach these problems with their intuition, experience, and knowledge of physics to achieve this iteration process. However, future aircraft design requirements break away from traditional norms, leaving the seasoned human designer with little intuition. This work devises an architecture by taking cues from how human designers lead design pro- cesses. This architecture also becomes an iterative design loop with creation and testing. A prob- abilistic model, the generative Bayesian Network, suggests candidate designs for the architecture. The generative Bayesian Network decomposes the problem into physical components and finds the interactions between them, as a systems design. The generative Bayesian Network learns examples from a combination of historical data and generations analyzed with SUAVE, an aircraft conceptual design tool. SUAVE is especially suited for this process since it possesses the ability to analyze and optimize numerous types of aircraft. This architecture enables a human designer to consider concepts and configurations they might have otherwise not considered. Four test cases examine the effectiveness of this architecture that combines SUAVE with a gen- erative Bayesian Network. First, a simple beam design illustrates how multiple valid solutions may be found. Next, are two cases, that design with differing levels of complexity to compare against an existing medium-range airliner. Finally, an ultra-long-range aircraft is designed with mission requirements unprecedented today. The architecture returns feasible design concepts prepared for more in-depth design studies and development.
Genomic characterization of CHD8 with implications for autism spectrum disorder
Keywords: Stem Cell Biology and Regenerative Medicine.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by restricted social interaction, impaired verbal and non-verbal communication, and repetitive behavior. ASD is estimated to affect 24.8 million people worldwide and is diagnosed in about 1.7% of children in the United States. It is well established that ASD has a strong genetic component with evidence of allelic and locus heterogeneity. Yet, the underlying genetic cause of ASD is unknown for at least 70% of cases. Recently, largescale exome sequencing studies of ASD patients from unaffected parents have led to the discovery of candidate genes based on de novo loss-of-function mutations that carry large biological effects and high risk for ASD. Currently, mutations in several chromatin regulators have been causally linked to human neurodevelopmental and psychiatric disorders, such as ASD and schizophrenia. One such chromatin remodeler, chromodomain helicase DNA binding protein 8 (CHD8), is associated with 12 mutated alleles, consisting of nonsense mutations or frameshift insertions/deletions that confer a haploinsufficient phenotype. CHD8 has been established as one of the most frequently mutated genes in ASD. CHD8 is thought to use the energy of ATP hydrolysis to catalyze structural changes in chromatin, allowing transcription factors to access their cognate binding sites, replace histones with histone variants, and reposition nucleosomes on a DNA template to tightly control gene expression. CHD8, a member of the CHD6-9 subfamily of CHD chromatin remodelers, exhibits a diverse range of functions in transcriptional regulation. Ectopic expression studies have indicated that CHD8 suppresses p53-dependent activation and apoptosis. It has also been found to regulate the Wnt signaling pathway by repressing β- catenin target genes. Previous chromatin immunoprecipitation (ChIP) experiments have shown that CHD8 binds to the promoters of approximately 2000 active genes that are enriched for H3K4me2 and H3K4me3 marks. In addition, CHD8 has been shown to interact with CTCF, with members of the MLL1 transcription activation complex, and with elongating RNA Polymerase II (RNAPII). CHD7, which causes CHARGE syndrome, a condition characterized by abnormal development of the neural crest, has also been shown to interact with CHD8. This thesis covers a brief overview of where the field of autism is now, an in-depth analysis of the genomic characterization of CHD8 and the role that it plays during the early stages of neurogenesis, and characterization of a CHD8 haploinsufficient mouse model that is able to recapitulate some of the autism phenotypes in vivo.
Geometric and structural inference on shape collections
Keywords: Electrical Engineering.

Shapes are all around us, and relationships between them are understood intuitively. These relationships are often analyzed by means of using different similarity metrics. These similarity metrics provide understanding about the salient features of a set of shapes, providing pointers to what the similarities on a set of shapes are, and how they are different from other shapes. With increased availability of three-dimensional data, the need for understanding different shape modalities and unifying information obtained from them becomes crucial. This thesis delves deep into how shape geometry and shape structure can be used as similarity metrics to analyze shape relationships. This is followed by real-world applications of obtaining these similarity-based shape relationships. The similarity of shape geometry is shown to be useful in obtaining shape correspondences on pairs of shapes and shape collections. Structural similarity on shape collections, provide different kinds of structural priors, which are useful in completing partial shapes. This thesis work has pioneered shape correspondences between nonisometric shapes. While shape matching on isometric pairs of shapes is a well-studied problem, most real-world shape pairs and collections are nonisometric in nature, and this is a crucial problem to solve. An novel consideration that we introduce on computing maps on shape collections, is the notion of modularity. While consistency is an important consideration that is already in use, coupling it with modularity makes the correspondence computation process much quicker. While these two problems involve using shape geometry as a cornerstone to solve real world correspondences, we also shape structure as an important similarity metric, and use it to complete real scans. Here, we discuss two different paradigms in shape completion. We introduce structure-aware shape templates, that can be useful in performing shape completion. To this effect, we provide a template-based optimization approach, which is coupled with a multi-view CNN to infer the structure of complete and partial point clouds. This is shown to be useful in partial scan completion, scene completion and segmentation tasks. In addition to this retrieval-based shape completion technique, we also provide a surface reconstruction technique on point clouds that utilizes topological structure of the shape. This surface completion technique is unique in the fact that it provides a handle on solving the hard combinatorial topology-aware optimization problem. As these techniques are more general in nature, they can be useful in spheres which are even removed from shape similarity understanding. This is discussed in the concluding segment of the thesis, along with directions for future research.
Geometric sensitivity, wake dynamics, and machine learning turbulence modeling on a skewed bump
Keywords: Mechanical Engineering.

A flow is considered geometrically sensitive if a slight perturbation to the geometry results in a major change to the flow structure. This work examines the flow over a wall-mounted, skewed bump, which exhibits geometric sensitivity. The bump is three-dimensional and has elliptical cross-sections with axis ratio of 4/3, and the geometry is modified by placing the bump at different angles with respect to the freestream. A combined experimental and computational approach is used to study the bump flow. The distinguishing features are a large separation bubble and longitudinal vortex structures in the wake. The wake has a quasi-periodic shedding cycle that is examined with Spectral Proper Orthogonal Decomposition (SPOD) and conditional averaging. Experiments are done to examine how the flow changes when the bump surface is rough. Reynolds Averaged Navier-Stokes (RANS) simulations have poor accuracy in this flow, and a method is developed to improve RANS accuracy using machine learning.
Geospatial Analysis of Near-Term Potential for Bioenergy with Carbon Capture and Storage (BECCS) in the United States
Keywords: School of Earth Energy &amp; Environmental Sciences
Department of Energy Resources Engineering
Thesis

Bioenergy with carbon capture and storage (BECCS) is a negative emissions technology (NET) that may play a crucial role in climate change mitigation. BECCS relies on the capture and sequestration of carbon dioxide (CO2) following bioenergy production to remove and reliably sequester atmospheric CO2. Previous BECCS deployment assessments have largely overlooked the potential lack of spatial co-location of suitable storage basins and biomass availability, in the absence of long-distance biomass and CO2 transport. These conditions could constrain the near-term technical deployment potential of BECCS due to social and economic barriers that exist for biomass and CO2 transport. This study combines published biomass production data, published storage capacity data, and newly calculated injectivity estimates at high spatial resolution to assess the near-term deployment opportunities for BECCS in the U.S.
If the total biomass resource available in the U.S. was mobilized for BECCS, an estimated 370-400 Mt CO2 yr-1 of negative emissions could be supplied in 2020. Of the total available biomass, the technical potential of negative emissions from biomass that has co-located biomass and suitable storage sites is 100-110 Mt CO2 yr-1. In 2040, under the assumption that significant quantities of dedicated energy crop production materialize, the total BECCS potential increases to 360-630 Mt CO2 yr-1. Meeting this technical potential would require large-scale deployment of BECCS technology. Over 1000 counties have the technical potential for near-term BECCS, although approximately half of the technical potential is available in the 200 counties with the highest biomass potential across the U.S. If efficient methods for collecting and transporting biomass are developed, this could result in fewer and larger projects, thus decreasing the number of injection wells by nearly a fifth. Specifically, the Illinois basin, Gulf region, and western North Dakota have the greatest potential for near-term BECCS deployment. The high-resolution spatial assessment conducted in this study can inform near-term opportunities that minimize social and economic barriers to BECCS deployment.