UC Santa Barbara

This thesis focuses on the design, fabrication, and characterization of gold microelectrode array (MEA) devices for applications in electrochemical aptamer-based (EAB) sensing. EAB sensors leverage target-induced conformational changes in surface-bound aptamers to transduce molecular recognition phenomena into measurable electrochemical signals, enabling real-time, reversible, and reagentless detection of target molecules in complex biological environment. Such sensors are highly necessary for pharmacokinetic measurements, where continuous monitoring of target concentrations is required.Motivated by the need to extend EAB sensing beyond single-point measurements toward spatially resolved target monitoring, this work develops planar, multi-site gold microelectrode arrays fabricated using standard microfabrication techniques. The MEAs were designed to support dense packing of sensing sites while maintaining well-defined electrode geometry and compatibility with aptamer functionalization. A custom PCB interface was developed to enable reliable electrical connections to external instrumentation.Electrochemical characterization of the fabricated devices was performed using cyclic voltammetry and square-wave voltammetry to assess electrode quality, surface area, and stability before and after aptamer immobilization. Sensor performance was evaluated using kinetic differential measurements (KDM) to enhance signal robustness and suppress common-mode drift. The effects of electrode geometry, square wave frequency, and biological media on signal stability were analysed.This thesis demonstrates that MEA based EAB sensors exhibit comparable electrochemical behavior and sensing performance to conventional gold wire electrode, while additionally enabling multi-site, spatially resolved measurements.Importantly, this work also shows that planar gold microelectrode arrays can be functionalized with aptamers without electrochemical surface roughening while still achieving kinetic differential measurement (KDM) responses comparable to electrochemically roughened gold wire control electrodes. This simplifies sensor fabrication while preserving robust EAB signaling, supporting the use of planar, microfabricated platforms for scalable EAB sensor implementations. Overall, this thesis lays the foundation for reproducible and scalable MEA-based platform for EAB sensing and for the future implementation of densely packed, minimally invasive sensor arrays capable of spatially resolved pharmacokinetic measurements real-time continuous in vivo monitoring.

The human genome endures insults from a variety of biological, chemical, and physical sources. Some of these insults result in severe lesions. One such lesion is the DNA double-strand break (DSB), in which the two strands of the DNA double helix are broken apart. This lesion can result from endogenous DNA damaging agents but can also be created during precision genome editing by targeted nucleases like CRISPR-Cas9. Regardless of the cause, human cells have multiple, competing DNA repair pathways by which to resolve these lesions; however, the cellular inputs that cells use to decide between these competing repair pathways remains elusive. My research objective was to monitor DNA repair factor recruitment to lesions in order to understand how the localization of DNA repair factors influences repair outcomes. In this work, I measure recruitment of both targeted nucleases and downstream repair factors by ChIP-seq, and I monitor changes to chromatin status and gene expression resulting from these activities using ATAC-seq and RNA-seq, respectively. In Chapter I, I describe the motivation behind the research projects and the development of a strand-specific ChIP-seq protocol to facilitate the measurement of the recruitment, localization, and polymerization of DNA repair proteins at DSBs. In Chapter II, I use this method to investigate the role of the FA-BRCA pathway during nuclease-induced DSB repair. I identify that the central player of the pathway, the FANCD2-FANCI heterodimer, localizes to DSBs and other open chromatin substates in a manner dependent on the activity of the FA Core Complex and ATM Kinase. I also find that FANCD2 coordinates chromatin remodeling, alters the spatial organization of other DNA repair factors such as BRCA1, and influences overall cell cycle progression. In Chapter III, I investigate the role of SFPQ during nuclease-induced DSB repair, and together with my co-authors, I identify that SFPQ does not localize to DSBs, but instead binds to the 5’ UTR of mRNA transcripts of RAD51 and its paralogs. In Chapter IV, I analyzed off-target transcriptional regulation events during CRISPRi screens, and I developed a methodology I termed POCKET-seq to characterize these binding events using gene ontology. In Chapter V, I discuss the implications of the work. Collectively, this work begins to untangle the molecular mechanisms underscoring the genetic, topological, and transcriptomic changes that occur during DNA repair and precision genome editing, which both rely on host DNA repair factors, chromatin remodelers, transcription factors, RNA-binding proteins, and splicing factors. Ultimately, this work has important implications for the development of cancer therapeutics and gene therapies for genetic disorders.

The high energy density of lithium batteries is ideal for electric vehicles and spacecraft, which operate in extreme temperature environments. While the performance of lithium-ion and lithium metal batteries has been studied at moderate and elevated temperatures, the impact of low temperatures on lithium batteries is not well understood. This dissertation clarifies the effects of moderately low to cryogenic temperatures on lithium metal anodes, lithium-ion cathodes, and lithium organic electrolytes.We first consider the impact of moderately low temperature environments on lithium metal anodes. Using magnetic resonance imaging, we investigate lithium dendrite formation in a series of organic lithium electrolytes. We demonstrate that modification of a commercial lithium carbonate electrolyte with the addition of a diglyme cosolvent improves the low temperature performance of lithium metal anodes. This hybrid electrolyte reduces the evolution of unfavorable lithium microstructures through improved ionic transport properties and a modified SEI.We next consider the effect of ultralow temperature exposure on lithium-ion full cells. Relevant state-of-the-art lithium-ion batteries often consist of a nickel manganese cobalt oxide (NMC) cathode, a graphite anode, and an organic electrolyte. Cells with this chemistry are currently exposed to cryogenic temperatures in space; however, the impact of such extreme conditions is poorly understood. Freezing processes may cause physical degradation and cracking within electrodes and may disrupt the cation solvation structure. We consider the impact of exposing high-nickel NMC cathodes to cryogenic temperatures during cell rest. We observe that in NMC811|graphite coin cells, a cryogenic rest period has negligible impact on the NMC811 cathode structure, the chemistry of the cathode electrolyte interphase (CEI), and the cell performance. Finally, we investigate the fundamental phase behavior of a binary carbonate electrolyte system during freezing. Using magnetic resonance, diffraction, and spectroscopic techniques, we track long range and local structural evolution of eutectic and non-eutectic electrolytes from room temperature to cryogenic temperatures, demonstrating that the electrolytes undergo both freezing and vitrification while the lithium cation remains solvated.The following dissertation clarifies the effects of low temperatures on certain highly relevant lithium battery materials, which will contribute to more reliable technologies for use in extreme environments.

Rechargeable lithium-ion batteries (LIBs) are a critical component of global renewable energy infrastructure. However, increased reliance on LIBs requires improvements to their component materials’ performance and longevity. Typical graphitic anode materials suffer from inherent capacity limitations and low-voltage degradation, which reduces usable power and charging speeds. Meanwhile, energy density in state-of-the-art LIBs remains limited by the capacity of its cathode materials. This dissertation first investigates a high-rate LIB anode material, the Wadsley-Roth-derived NaNb13O33 phase, and examines its lithium insertion behavior and mechanisms for the first time. Following this, the structural and kinetic ramifications of lightly doping the energy-dense, layered transition-metal oxide cathode, LiNiO2, are explored in depth. Owing to their exceptionally high rate-capabilities, high volumetric capacities, and long cycle lives, Wadsley-Roth compounds are promising anode materials for high-performance lithium-ion batteries. Structural insights from neutron and synchrotron diffraction, as well as solid-state nuclear magnetic resonance (NMR), reveal sodium disorder and the presence of open, pseudo-2D channels that evolve minimally with cycling. Using electrochemical, magnetic resonance and spectroscopic techniques, supported by computational modeling, the high rate-performance and capacity of NaNb13O33 is demonstrated and rationalized as the result of multi-electron redox, fast multi-channel Li diffusion, and an insulator-to-metal transition upon lithiation. These results place NaNb13O33 within the ranks of promising new high-rate lithium anode materials that warrant further research. Next, we compare the effects of doping LiNiO2 with, separately, 3% Al and Mg ions. LiNiO2 experiences rapid capacity decay due to cycling-induced structural transformations that degrade Li extraction and insertion kinetics. Using long-range and local structural techniques, we examine the impacts of each dopant on the pristine structure and demonstrate that both planar and point defects can be modulated by dopant selection. We then show the impact of such structural changes to first cycle irreversibility and long-term structural and kinetic degradation. Insights from ex situ X-Ray diffraction, NMR, and transmission electron microscopy (TEM) reveal the importance of minimizing high-voltage cathode volume changes, as well as twin boundary defects, in reducing strain and kinetic hindrance accumulation with cycling. We show that twin boundaries functionally reduce the densified surface area, which is a key factor affecting kinetic capacity degradation.

This thesis presents a measurement of the cross section for the production of two W bosons and one Z boson. The measurement is performed using data collected by the CMS experiment at the CERN LHC at center-of-mass energies √s = 13 and 13.6 TeV, corresponding to an integrated luminosity of 200 fb−1. Events with four charged leptons (electrons or muons) are selected for this analysis. Both nonresonant W W Z production and ZH production, with the Higgs boson decaying into two W bosons, are reported. For the first time, the two processes are measured separately in a simultaneous fit. Combining the two modes, signal strengths relative to the standard model (SM) predictions of 0.75+0.34 −0.29 and 1.74+0.71 −0.60 are measured for √s = 13 and 13.6 TeV, respectively. The observed (expected) significance for the triboson signal is 3.8 (2.5) standard deviations for √s = 13.6 TeV, thus providing the first evidence for triboson production at this center-of-mass energy. Combining the two modes and the two center-of-mass energies, the inclusive signal strength relative to the SM prediction is measured to be 1.03+0.31 −0.28, with an observed (expected) significance of 4.5 (5.0) standard deviations. The focusing of collider beams for collider experiments is crucial for maximizing the luminosity and thus the discovery potential of these machines. In recent years, plasma wakefield acceleration has emerged as a leading candidate for achieving higher energy collisions with smaller facility footprints due to the large accelerating gradients in the plasma. This higher beam energy poses significant challenges for the final focusing system of the collider. Here, we discuss the various challenges of final focusing for TeV-scale plasma accelerators and propose possible solutions. Finally, we present the first design of a final focusing system for a 10 TeV linear wakefield collider, evaluate its performance, and discuss its shortcomings as well as improvements for future designs.

This thesis examines the structural barriers that constrain renewable energy investment in developing countries in general and then shifts focus to examine why renewable energy investment and deployment in Bangladesh lags behind that of comparable lower-middle-income economies. The research on structural barriers is based on a quantitative analysis of a panel of 103 low- and middle-income countries from 2000 to 2022. Pooled ordinary least squares with year fixed effects is paired with a two-way fixed effects specification across five outcomes covering renewable energy investment and the share of solar, wind, and total renewables in electricity generation. Regulatory quality is found to be positively and significantly associated with renewable energy investment. Land pressure, measured as people per square kilometer of non-agricultural land, is negatively associated with the renewable share of generation. Political stability is positively associated with investment per capita.The qualitative component applies George and Bennett's (2005) structured, focused comparison method to Bangladesh, Vietnam, and Pakistan. The case studies explain how environmental constraints, governance arrangements and institutional path dependence operate in practice. Vietnam's feed-in-tariff regime added 16.5 gigawatts of solar capacity within three years through a credible price signal and a centralized governance. Pakistan's rooftop solar boom developed largely outside the formal utility-scale sector, driven by abundant land, rising retail tariffs, and consumer-led adoption. Bangladesh faces all three barriers: extreme land pressure raises siting costs, weak regulatory quality undermines investor confidence, and capacity-payment obligations to legacy fossil-fuel plants consume the fiscal space required for renewable procurement. The interaction of barriers, rather than any single condition, explains the divergent outcomes observed across the three cases.The thesis proposes a sequenced reform agenda for Bangladesh that addresses capacity-payment lock-in, distributed solar enablement, institutional consolidation under the Sustainable and Renewable Energy Development Authority, competitive auctions, and pilot deployment of agrivoltaics and floating solar. The framework also generalizes to other lower-middle-income countries where land scarcity, governance fragmentation, and fossil-fuel lock-in interact to constrain renewable energy investment.

Research has noted that rural Latine students rely on their familial, social, and community capital to cultivate college-going aspirations and provide college-related information. However, rural Latine students’ college-going rates continue to lag behind those of their white, urban, and suburban counterparts. The lower attainment rates have been attributed to increased barriers to the college information that rural students receive. Therefore, this qualitative study draws on the nepantla stage of the college-conocimiento framework (Acevedo-Gil, 2017), a model that accounts for the non-linear Latine college-choice processes, to explore the social media and online sources of college information and support that rural Latine students from California’s San Joaquin Valley rely on to make decisions about their college application processes and choices. Data for this thesis were collected through pláticas (Fierros & Delgado Bernal, 2016) with eight rural first-generation Latine high school seniors. The findings of this thesis reveal that students used social media to streamline college information and application processes, learn about campus culture, and access digital peer mentorship.

Eye movements are an important part of human vision. We constantly make them, directing our foveal processing to different locations. Research has shown eye movements to optimize accuracy in various tasks, such as search and navigation, implying that human eye movements are an active process, constantly seeking information that could aid decision-making. But what happens when there is no task to guide eye movements (free viewing task)? Is there any purpose to those eye movements? A prevalent idea is that during free viewing, humans make eye movements to low-level visually salient regions. However, decades of research have shown that humans fixate on people in scenes, on objects, on gaze, and on text, and, more recently, on local regions judged to be meaningful. The goal of this thesis is to understand which perceptual tasks humans engage in during free viewing and to assess whether free-viewing eye movements reflect the goal of optimizing task accuracy (optimal eye movements). Based on the findings, I propose that an important, general human default task during free viewing is to comprehend scenes, and that humans plan near-optimal eye movements, actively seeking information that maximizes comprehension. The first part of this thesis focuses on experimental evidence from eye-movement measurements suggesting that scene comprehension is an important default task for humans during free viewing. Eye movements were measured under four task instructions: free viewing, scene description, object search, and counting objects. The stimuli were image pairs, called Winograd images, containing minor visual alterations that drastically change scene interpretation without altering low-level saliency, thereby isolating the semantic factors guiding eye movements. Results indicate that free-viewing fixations closely resemble those of observers explicitly instructed to describe a scene, differing significantly from fixations during object search or counting. Furthermore, free-viewing fixations are disproportionately directed toward people and objects most critical to understanding the scene (objects that maximally impact scene descriptions when removed), rather than solely toward low-level visual saliency or locally meaningful regions. I also show that human fixations on these critical elements improve their understanding of the scene, demonstrating a causal influence of these fixations in accurate scene comprehension. The second part of this thesis evaluates whether human fixations during free viewing approximate the optimal strategy for maximizing scene comprehension. The challenge in this objective is to create a model that estimates optimal fixations for real-world scenes and high-level goals such as scene comprehension. Classical methods based on Bayesian ideal searchers have a strong mathematical foundation but cannot be applied to real-world scenes. I implemented a model that simulates human foveated vision and sequential eye-movement exploration of scenes. Leveraging state-of-the-art vision-language models (VLMs) capable of human-level scene comprehension, the model generated descriptions of the actively explored foveated scenes. I subsequently trained a reinforcement learning (RL) agent that uses a convolutional neural network (CNN) to optimize visual exploration (Q-network), systematically executing eye movements to maximize the semantic accuracy of the VLM’s descriptions at each step. By measuring free-viewing eye movements on images carefully curated to depict complex social interactions, actions, or implied actions, I categorized the elements present in these images and counted the human fixation frequencies for these categories (people, objects relevant and irrelevant to the understanding of the scene, text, gazed and grasped objects, salient regions). The optimized RL agent matched the fixation patterns observed in human data without any prior training on human fixation data, significantly outperforming the same RL model optimized for search or image classification tasks, as well as saliency prediction models. Furthermore, I found that VLM descriptions generated by simulating foveation at human-fixated locations, recorded during the free-viewing task, achieved semantic accuracy comparable to that obtained via fixations from an RL agent specifically optimized for scene understanding. The agreement between the RL model and human fixation frequencies also decreased when the model was trained with very low or extreme foveation, suggesting that human free viewing eye movements are an emergent property of an interaction between the goal to optimize scene comprehension and the specific foveated properties of the human visual system. I assessed the generalization of the RL model's results to a recently published data set on eye movements from 6720 observers aged 5-72. Together, this research demonstrates that eye movements during free viewing are an actively optimized, task-driven behavior aimed at comprehending the visual world. Fixations to people, text, objects relevant to understanding, and gazed/grasped objects are an emergent property of an interaction between the goal of optimizing scene understanding and the foveated properties of human sensory processing.

In F-theory, a branch of string theory, the geometry of an elliptically fibered variety determines important features of the associated physical theory. In particular, the singular fibers of the elliptic fibration give rise to Lie-theoretic data that determine the nonabelian part of the gauge group. This connection between singular fibers and Lie theory suggests the possibility of a similar construction in arithmetic geometry.Motivated by this analogy, we introduce arithmetic gauge algebras and arithmetic gauge groups associated to an elliptic curve E/K, where K is the fraction field of a Dedekind domain R. These objects are constructed from the Mordell–Weil group of E together with the geometric special fibers of a minimal proper regular model. The action of the absolute Galois group on the irreducible components of the geometric special fibers gives rise to arithmetic dual graphs and associated abstract Cartan matrices, from which semisimple Lie algebras and groups of Lie type are constructed. This provides an arithmetic analogue of the gauge group construction appearing in F-theory. 

The rapid scaling of artificial intelligence computation has exposed electrical interconnects as a critical bottleneck in modern data centers, driving the industry toward silicon photonics and high-speed wavelength division multiplexing links. As networking standards have evolved to demand >100G per lane, the architectural paradigm has shifted from massively parallel, moderate-speed microring arrays to fewer, high-baud-rate channels. Despite this aggressive scaling, existing literature remains heavily focused on isolated device-level demonstrations, lacking systematic parametric studies that connect fundamental microring geometry to system-level Bit Error Rate performance. To address this gap, this thesis presents a comprehensive, multi-physics numerical modeling framework for high-speed Silicon Microring Modulators (MRM) and Microring Resonators (MRR) on a 160 nm standard platform. Utilizing an end-to-end simulation flow (MODE, FDTD, HEAT, CHARGE, and INTERCONNECT), the fundamental trade-offs between optical bandwidth, insertion loss, and extinction ratio are systematically evaluated. For the receiver MRR, transient step-response characterization reveals that the optical cavity behaves as a low-pass filter, dictating that wider optical bandwidths are strictly required to mitigate Inter-Symbol Interference at speeds exceeding 100 Gbps. For the transmitter MRM, realistic PN junction parameters are benchmarked from literature to evaluate the complex trade-off between optical modulation amplitude and cavity bandwidth. Through rigorous multi-dimensional parameter sweeps of active doping concentrations and drive voltages, an optimal operating regime is identified. The optimized silicon MRM successfully demonstrates a 100 Gbps transmission rate satisfying the concatenated forward error correction limit at a 2 V peak-to-peak drive voltage. Ultimately, this thesis establishes a robust device-to-system co-simulation methodology while revealing the fundamental, rigid speed limits of standard silicon-on-insulator microrings, highlighting the necessity for advanced junction engineering and the eventual transition to highly efficient electro-optic materials.