VictorJuiz/thesis huggingface dataset:
Mechanistic Insights into Hole Transfer from Photoexcited Quantum Dots

Harnessing the energy in photoexcitations requires efficient and controlled charge separation whether to drive a photochemical reaction or to create electricity for a photovoltaic device. Semiconducting nanocrystals, or quantum dots, have shown particular promise as light absorbers for these applications. They possess large extinction coefficients, size-tunable band gaps, and an accessible and functionalizable surface. The accessibility of the surface not only enables efficient charge extraction, but it also allows for undesirable charge trapping on ill-defined surface states. This dissertation will explore the mechanism of charge transfer from photoexcited quantum dots in order to better understand both charge extraction and trapping. It is specifically focused on hole transfer by using hole-accepting moieties since this process tends to limit the efficiency of quantum dot based devices and is understudied compared to electron transfer./nA model system for studying hole transfer is presented that uses cadmium selenide/cadmium sulfide core/shell nanocrystals or quantum dots with high photoluminescence quantum yields, which therefore selects dots with relatively few traps. The surface of these quantum dots are functionalized with ferrocene-derived hole-accepting molecules and the effect of this functionalization on the photoluminescence is used to determine the rate constant for hole transfer. The rates are found to exponentially decay with increasing CdS shell thickness or increasing linker length between the ferrocene and the quantum dot surface. This is well modeled by a tunneling process./nThe relationship between driving force and rate in this system was investigated by using six distinct ferrocene acceptors with a range in driving force of 800 meV. The resulting relationship between rate and energetic driving force for hole transfer is not well modeled by the standard two-state Marcus model. Alternative mechanisms for charge transfer are posited, including an Auger-assisted mechanism that provides a successful fit to the results. The observed relationship can be used to design QD-molecular systems that maximize interfacial charge transfer rates while minimizing energetic losses associated with the driving force./nThe temperature dependence of the hole transfer rate in this model system is also explored. The observed Arrhenius slopes for these rates do not depend on driving force, which suggests that surface state mediated hole transfer may dominate direct hole transfer. A model for trap-mediated transfer via shallow and reversible hole traps is posited and matches well with the data./nFinally, the results presented within are used to inform the creation of a generalizable model for hole transfer through which previously published work on hole transfer to both engineered and native hole traps can be analyzed.

Advisor: Alivisatos, Paul
A Non-equilibrium Approach to Rangeland Riparian Management: A Study at Tejon Ranch, California

Riparian areas in arid rangelands provide a wide range of ecosystem services and are critical areas for conservation of landscape and regional biological diversity. Creeks and their associated riparian habitats also provide unique resources for livestock management, however these systems have proven to be sensitive to disturbance from livestock. Ecological site concepts and associated state-and-transition models are useful tools for understanding rangeland plant succession and the relative influence of management actions. These models have been widely developed for upland rangeland systems; however, extension of these models to rangeland riparian systems is still in its infancy. In this study I classified two ecological sites along four streams on the Tejon Ranch in the southern San Joaquin Valley, California. Using vegetation data gathered over four years at fifteen study reaches I identified three distinct vegetation states and plausible conditions precipitating transitions between states. I monitored large mammal and herpetofauna activity at each of the study reaches and compared the predictive power of the categorical ecological site and state-and-transition models in predicting wildlife activity to models based on continuous environmental variables. Finally I investigated the role of cattle and feral pig management on riparian vegetation and wildlife. Ecological sites proved to be a good predictor of observed wildlife community assemblages and was included in top models predicting activity of three of five mammal species: bobcat (Lynx rufus) deer (Odocoileus hemionus) and feral pig (Sus scrofa); and two of three reptile species: western fence lizard (Sceloporus occidentalis) and Gilbert’s skink (Plestiodon gilberti). In contrast, vegetation states proved to be a poor predictor compared to continuous variables. Cattle and feral pigs appear to have played a role in the one observed vegetation transition, and cattle and feral pig activity was correlated with increased cover of hydrophyllic vegetation and bare soil, and decreased cover of upland vegetation and forbs. Summer cattle activity and spring pig activity were the most strongly correlated with changes in vegetation attributes. Results from this study illustrate the utility of ecological sites to model riparian vegetation change and provide a framework for understanding the effect of rangeland management on riparian vegetation and wildlife.

Advisor: Bartolome, James
Two Models of Coagulation With Instantaneous Gelation

Two models of coagulation are presented: one, a system of coupled partial differential equations and the other microscopic Brownian particles. Both models feature a parameter that represents the tendency of two particles to coagulate at sufficiently close distances. Both models have a phase transition, viewed as the mass clumping together as a gel. Previous work has shown the models are connected, and in here we show that their phase transition to instantaneous gelation is connected as well.

Advisor: Rezakhanlou, Fraydoun
Two Dimensional Transistors with Non-volatile Functionalities

Two dimensional (2D) materials have gained much attention these years for their intrinsic physical properties and promising applications in the field of electronics, optics and mechanics. Those materials, especially the 2D transition metal dichalcogenides (TMD), are regarded as a potential replacement plan for silicon in the next generation semiconductor technology. The combination of 2D semiconductors and epitaxial grown single crystalline ferroelectrics enables the development of next generation emerging ferroelectric memory devices, and supplies a polarization controlled system to explore the fancy physical phenomena in the 2D crystals under high carrier density doping at the same time./nThis thesis talks about the researches on two dimensional transistors with non-volatile functionalities originating from different mechanisms. Chapter 1 briefly introduced the research topics as well as motivations. Chapter 2 and 3 discussed details of two main components in the research: lead zirconate titanate (PZT) and molybdenum disulfide (MoS2) respectively. The MoS2 flakes were integrated with single crystalline PZT films directly and trap related hysteresis loops were observed in chapter 4. In chapter 5, methods to minimize the effects of interface states in the 2D ferroelectric structure were carried out. Correct handedness hysteresis loops were detected, with large loop size (>20V) and high ON/OFF ratio (>106), exhibiting the promising future of 2D ferroelectric devices. The switchable metal-insulator phase transitions of MoS2 controlled by ferroelectric polarization were also detected. In chapter 6, the clockwise hysteresis loops induced by interface states in the MoS2 2D dielectric transistor were investigated. Then a pulse gating technique with self-designed pulse sequences was developed, which effectively minimized the hysteresis loops induced by adsorbates and the intrinsic electrical properties of tested devices were eventually extracted.

Advisor: Salahuddin, Sayeef
Siddiqi, Irfan
Wary Boldness: The Aesthetics of Political Agency in Renaissance England

This dissertation argues that foundational works of the English Renaissance, most notably the later books of Edmund Spenser’s The Faerie Queene, proleptically model a key ambiguity in modern aesthetic theory concerning the work of art’s relation to external reality. On the one hand, these texts lay claim to a vital social efficacy, inserting themselves unmistakably into contemporary public controversy and holding out the possibility that imaginative literature could bring about a reformation of political subjectivity more radical and lasting than other forms of expression. On the other hand, the texts also fail to set forth a positive political program that could be translated from aesthetic experience to social activity. Instead, they train readers in a mode of cautious and attentive critical reflection, an interpretive agency that Spenser and others regard as the necessary precondition for enlightened praxis, but that falls short of—and, in many respects, actively complicates and confounds—a politics in itself. Such a critical disposition thus maintains a pre- or proto-political character, in which artistic experience becomes the simultaneously enabling and disabling condition for reformative social action. The project thus seeks to complicate the longstanding insistence, in early modern literary criticism, on the directly political character of artistic experience. Associating Renaissance literature with immediate didactic and ideological aims, in contradistinction to the putatively de-politicizing tendencies of post-Enlightenment art and aesthetic theory, historicist scholarship in recent decades has perpetuated a reductive narrative about the relationship between the aesthetic and the Real, one that an earlier tradition of Kantian and Marxist philosophy treats with greater subtlety. This dissertation analyzes Renaissance literature from just such a perspective, making the case for the semi-autonomy of The Faerie Queene from within an Adornian framework, and stressing the profound but attenuated relationship between the literary and the extra-literary in the early modern period. Through fine-grained analysis of Spenser’s Legends of Justice and Courtesy, alongside a number of related texts, I argue that the political and historical content of The Faerie Queene—and, by extension, any literary work of sufficient formal complexity and extra-textual ambition—is accessible only through an attentive engagement with the text at the level of the individual word. Such an analytical process, moreover, becomes both the mechanism for training subjects in the critical judgment necessary for redeemed political action, as well as a mode of deliberative caution that re-directs the concentrated urgency required for such action back into the patient work of literary analysis.

Advisor: Picciotto, Joanna
Latino Identity Development and the Path to Blue- or White-Collar Occupations: Lessons for Policy Across the Pre-Adult Lifespan

The problem of youth unemployment continues to rise in countries around the world, and for many adolescents whose early working lives are marred with challenges and obstacles, such disadvantages are likely to have lifelong implications and to ensure cycles of poverty and inequality. Policy responses to the youth unemployment problem, particularly in the United States, have largely ignored the evidence that adolescents are a unique population that requires both a deeper understanding of the problem and bespoke policy interventions./nThis dissertation challenges policymakers to change their perceptions of the problem of youth unemployment to one of work disparities with the purpose of shifting the focus to the social and psychological nuances that are also a part of the problem. Doing so allows for the application to the study of the problem of psychosocial development theory, which posits that individuals develop an identification with work across their pre-adult lifespan, and that work roles, choices, and behaviors are extensions of this process. To understand youth work disparities thus requires examining their identity development experiences./nThe findings of the quantitative study provide some support for the relationship between psychosocial development predictors and young adult work outcomes. Furthermore, the examination of the identity development and employment trajectories of 20 Latino males in California revealed stark developmental differences between those who had attained at least a four-year college degree and white-collar employment compared to those who had attained neither and who struggled with unemployment. The findings provide a base from which to develop new policies that focus on supporting developmental pathways to healthy employment outcomes across the pre-adult lifespan.

Advisor: Gilbert, Neil
The effects of retinal image motion on the limits of spatial vision

Vision is not a static process. Our perception of the world is not merely a sequence of fixed snapshots but rather involves a dynamic process in which the visual input is synthesized over time to provide a more detailed and informative signal than would otherwise be possible using a fixed array of sensors. This dynamic signal is largely a result of fixational eye motion, or the constant ocular jitter that creates an ever-changing signal in each photoreceptor cell. It is not known how the visual system potentially exploits such transient signals to serve our finest spatial acuity, and how the relationship between visual acuity and the photoreceptor sampling limit can be muddled because of this fact. We used an adaptive optics scanning laser ophthalmoscope to precisely control the spatiotemporal input on a cellular scale in human observers to assess how acuity differed as a function of retinal image motion. Additionally, we investigated the purpose of fixational eye motion, and in particular microsaccades, in relocating stimuli to a preferred region within the central foveal region. Combined, these results show the utility of fixational eye movements in high spatial vision.

Advisor: Roorda, Austin
Combining Retrospective Optimization and Gradient Search for Supply Chain Optimization

In initial work, we found a version of Retrospective Optimization, in which we optimize over a single randomly generated long sample path, is often effective for optimizing policy parameters in relatively simple stochastic supply chains. In these applications, the optimization problem is frequently an integer program. However, preliminary efforts to directly extend this methodology to more complex supply chains, and to optimize risk mitigation strategies, were in many cases too slow to be effective./nTo address this limitation, we first develop a two-stage algorithm that uses Retrospective Optimization over a relatively short time horizon to provide starting points for stochastic approximation gradient search. We perform extensive computational experiments to compare this approach to Retrospective Optimization without gradient search on a sequence of increasingly complex supply chains./nIn a data-driven setting where the policy parameters are set using available past data rather than a randomly generated sample path, the resulting MILP formulation presents similar computational challenges to those found in our Retrospective Optimization approaches. This observation motivates us to modify and test our algorithm in a data-driven setting, using sales data from a major European grocery chain store. We focus on a setting in which policy paramters can be a function of exogenous factors such as the day of the week and the outside temperature. We examine complex inventory management models that involve perishable inventory. and show that with suitable modifications, the same two-stage algorithm is effective for determining the data-driven inventory policy parameters.

Advisor: Kaminsky, Philip M
Object Recognition in Spatial and Temporal Context: Crowding and Serial Dependence

Object recognition is a fundamental function of the human visual system. Our visual system must recognize objects under a wide variety of environmental conditions and despite inherent noise in the nervous system. How the brain accomplishes such accurate and reliable performance on object recognition tasks is widely studied but poorly understood. Less understood still is how the brain accomplishes object recognition in a broader spatial and temporal context, as many studies focus on studying the recognition of objects in isolation. Objects in the real world are more often seen and recognized in both a surrounding visual environment, and for more than one moment in a dynamic world. Here we address these questions by examining the phenomena of crowding and serial dependence. Crowding is an interaction of spatial context; it is the inability to recognize an object when it is surrounded by other similar objects, which would otherwise be resolved in isolation. Serial dependence is an interaction of temporal context; a target appears more similar to a previously seen stimulus. First, we ask what types of information survive crowding and what types of representations can crowd one another. Through computational modeling, we present evidence that crowding is a perceptual decision level phenomenon that occurs when we must make examine a distributed representation with limited attentional resources. Next, in a behavioral experiment, we show that lighting information in the context of a scene can influence how nearby object representations interact in crowding. Finally, we show that temporal context can influence the perception of even high level dynamic stimuli like point-light walkers through the mechanism of serial dependence. Together, these experiments show that both spatial and temporal context play an important role in object recognition and that the brain uses high level object representations that can interact in both space and time to accomplish recognition.

Advisor: Whitney, David
Exploiting Regulatory Heterogeneity to Systematically Identify Enhancers with High Accuracy

Enhancer discovery through computational means has long been a goal of the genomics community. The tools developed for this purpose, however, tend to underperform when tested on completely held out test sets. Here we use the pregrastrula patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held out data results from heterogeneity of functional signatures in enhancer elements. We show that at least two classes of enhancer are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, extremely high (>98%) prediction accuracy can be achieved in a balanced, held-out test set. The homogenous set is composed predominantly of enhancers driving multi-stage, large segmentation patterns in the early embryo, and hence we term them segmentation driving enhancers (SDE). Prediction is primarily driven by transcription factors DNA occupancy with almost no power derived from histone modifications, including H3K27ac, casting further doubt on the utility of histone modifications to demarcate enhancer elements. The transcription factors used in the prediction process constitute over half of the transcription factors identified in genetic screens as patterning the early embryo, and hence provide a remarkably expansive view of this process. Applying this method to a genome-wide scan, we predict 1,600 SDEs, 916 of which are novel, covering approximately 1.6% of the euchromatic genome. We verified these predictions by testing 41 novel SDEs using in situ whole embryo imaging of stably integrated reporter constructs. We confirmed 39 of these predictions, a 95% precision on a genome-wide scan with an estimated recall of 98%, indicating that our reported collection of SDEs may be close to comprehensive.

Advisor: Bickel, Peter J
Variability Analysis and Yield Optimization in Deep-Submicron Mixed-Signal Circuits

Scaling of CMOS technology into the deep-submicron regime has made superior device performance and high density possible. However, achieving extreme performance is often limited by an increase in variability due to the aggressive shrinking of dimensions. As variability continues to rise, statistical modeling methods like Monte-Carlo and corner simulation that have been extensively used to predict circuit yield in the past, now become insufficient. It is now evident that models can no longer be developed solely by device variation measurements, but they need to exhibit flexibility and tunability to a specific design./nIn this work, we address the problem of rising variability and insufficient variability modeling in two ways. Firstly, by characterizing variability in a deeply-scaled technology node, and secondly by developing a methodology for simple, fast model tuning for design specific yield optimization./nTechnology characterization is achieved by designing a set of dedicated test structures in a 28nm FDSOI technology. Test structures include both device characterization as well as high-speed comparator characterization, and focus on design-dependent, layout-dependent and topology-dependent sources of variation. Worst-case measured within-die device variation goes up to 11 % while a 46% of current variation is measured across different dies. Layout-dependent systematic effects do appear to be significant in this technology. Several comparator topologies are also measured, showing a direct link between comparator sensitivity and measured offset./nYield optimization is achieved by model customization to a specific design. A methodology that uses backward propagation of variance and sparse regression techniques is developed in order to achieve this. The methodology is shown to have the ability to tune models to variability structure measurements, decreasing the estimated prediction error from 30% to <4%.

Advisor: Nikolic, Borivoje