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.

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.

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.

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.

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. 

Ceramic matrix composites are an extreme-environment structural material poised to lightweight and improve the efficiency of next-generation aerospace and propulsion systems. As the use of CMC components continues to expand, there is a commensurate need for accurate models and ways to monitor their damage evolution. The transient ultrasonic waves generated during crack propagation, known as acoustic emission (AE), offer a powerful means of tracking the progression of damage. Among other non-destructive evaluation techniques, AE is unique in its sensitivity to damage and in its ability to temporally resolve the evolution of damage throughout the volume of a component. While frameworks to achieve this remain limited, AE has the potential to generate, in essence, a time-resolved video of evolving subsurface crack formation. Such a capability would supply CMC modeling efforts with information-rich datasets on damage evolution and establish a basis for quantifying damage during operation. To this end, this work unifies several elements from the CMC and non-destructive evaluation literature into an intuitive multimodal framework for AE-based imaging that uses waveform energy as a metric for damage, while using the content of the waveforms to determine the spatial position of the damage. We describe experiments to validate the linear relationship between cumulative energy and accumulated matrix cracking in idealized CMC specimens, both in-situ and post-mortem. Furthermore, we show proof-of-concept for an ultrasonic-based calibration methodology, illustrated through the use of pencil-lead break datasets, that would enable improved AE location resolution and depth identification in mechanical test specimens. Our work provides experimental mechanicians with a clear path for developing quantitative and translatable AE imaging capabilities in a given material system using a combined x-ray computed tomography, ultrasonics, and acoustic emission approach.

Recurrent neural networks (RNNs) are widely used both as practical architectures for machine learning tasks involving sequential data and as computational models that let neuroscientists study recurrent circuits in the brain, yet their training dynamics are only partially understood. A key reason is dimensionality: a small RNN can have thousands of parameters that interact nonlinearly through the recurrent dynamics, making the loss landscape difficult to analyse and the role of any single design choice difficult to isolate. This thesis takes a different approach. Rather than studying full-rank networks directly, we analyse a minimal model—the rank-1 RNN with connectivity W = mn⊤ trained on a one-bit flip-flop task. The training dynamics get reduced to a two-dimensional phase plane over effective connectivity parameters, allowing the network’s behaviour to be both derived mathematically and tested empirically.Using a model reduction we show that the rank-1 RNN is characterised by two effective scalar parameters, the recurrent gain Reff = n ⊤m and the input gain Meff = n ⊤Win. We also derive a formula for the “flip boundary” Mcrit(Reff) that separates inputs strong enough to “flip-flop” the network from one memory state to the other when a new input pulse arrives. We then use this framework to study three questions about training. First, we show that the bias vector b, although not mathematically required for bistability, is an extremely helpful term during base training. Under standard small-weight initialisation, removing it caused gradient descent to have difficulty converging to the bistable attractor; we further show that strong-synapse initialisation breaks the same symmetry and reaches the bistable target without any bias term, confirming that this failure is specific to the small-weight regime. We trace this failure to that the loss function treats positive and negative input gain identically and gradient descent sees no signal pushing it toward the correct solution from the start of training, as well as the fact that the readout direction n, which defines the (Reff, Meff) coordinate system, is itself free to rotate during training, so the optimiser cannot be relied upon to stay in the bistable region once found. After the base training, we show that retraining trajectories initialised above and below the flip boundary exhibit different behaviours. In agreement with the bifurcation prediction, below-boundary initialisations are more prone to “overwriting” existing bistable struction instead of “reusing” it, before recovering. Finally, we show that using separate learning rates for m and Win produces faster and more direct trajectories in the (Reff, Meff) plane by allowing Meff to climb away from the boundary before Reff drifts.These results give a quantitative, geometric account of when a network reuses an existing solution and when it must overwrite it, and provide hypotheses for future experiments on full-rank recurrent networks.

My dissertation, “Donne sulla soglia: A Critical Translation of Fourteen Prologues from the Plays of Giovan Battista Andreini and Domenico Bruni’s Fatiche comiche (1623),” investigates proto-feminism in Counter-Reformation Italy through various critical lenses and original translations of comedic prologues published between 1611 and 1627. My translations of four prologues in defense of women from Domenico Bruni’s Fatiche comiche, nine prologues from the comedies of Giovan Battista Andreini—three of which are authored by Giovan Paolo Fabri— and Andreini’s La Ferza: his defense of the actress, invite a discussion of male-authored defenses of women in the commedia dell’arte tradition by taking the paratextual instrument as my object of analysis. The theory and practice of translation further informs my project, which opens with an extensive critical introduction, while the resulting bilingual text doubles as a valuable resource for students and scholars of early modern Italian theater, gender and women’s studies, and Renaissance studies more broadly. Situated within the larger context of the querelle des femmes—a European literary, social, and cultural debate concerning women’s merits and their place in society—the theater in Counter-Reformation Italy occupies a unique place within this literary and theater history. It is simultaneously the site of an unprecedented leap in women’s agency through performance and a relentless effort by the Church to censor theatrical productions. As I argue, while the defense of women in this context was, on the one hand, a defense of comedy itself, the genre’s classical roots as rhetorical apologia anchor what Anne MacNeil identifies in Music and Women of the Commedia dell’Arte in the Late Sixteenth Century as the “central precept of the commedia dell’arte,” which is “the invocation of classical reasoning in order to justify women’s expression” (2). In the Counter-Reformation, male and female actors and authors of comedy manipulated classical models in order to navigate the complexities of religious tensions and shifting cultural norms, all grappling with the rapid, public unification of the actress with her own voice. My project traces the formation of female subjectivity from Renaissance literature to Baroque theater by analyzing and contextualizing this strategic use of classical reasoning in seventeenth-century comedic prologues. My critical introduction weaves genre, historical context, and methodology through the lens of a single prefix: para-. The paratext, which literary theorist Gérard Genette explores in Seuils (Paratexts) (1987), hinges on the Greek root of para-, meaning “beside,” “alongside,” “apart from,” or “beyond.” The prologue, as paratext, sits at the threshold between the world of the play and the “real” world: a concept Andreini explores in his prologue to La Centaura. An investigation of male-authored defenses of women within the context of commedia dell’arte and the rise of Italian improvised theater, which is indebted to actresses and their education as “meretrices honestae,” or “honest courtesans,” invokes a discussion of paradox. This trope, which appears in the Petrarchan verse of famed actress Isabella Andreini, becomes a way for the actress to gesture beyond patriarchal constructs of the feminine through performance. As I conclude, the threads of paratext and paradox form a lens through which to understand prologue as the threshold of identity formation—that the thing located “beside” becomes, in the Baroque, through a deconstruction of the “real,” the thing that gestures “beyond.”

The focus of this dissertation is the enhancement of prediction and quantization algorithms within the framework of the video-based point cloud compression (V-PCC) standard. The first line of research explores a transform domain prediction strategy specifically tailored for geometry video compression. Standard video codecs rely on simple pixel-copy operations after motion estimation. However, the presence of large homogeneous regions in geometry videos renders this existing prediction strategy sub-optimal. We overcome this limitation by shifting to a transform domain temporal prediction framework, that accounts for spatial as well as temporal block correlations. First, spatial decorrelation is largely achieved by applying the Discrete Cosine Transform (DCT) to source and reference blocks. Subsequently, we employ data-driven temporal correlation filters to predict each transform coefficient of a source block using the corresponding transform coefficient of the best-matching reconstructed reference block. While spatial domain temporal correlations along a motion trajectory appear close to one, true temporal correlations emerge in the frequency domain. Specifically, low frequency components remain highly correlated, whereas high frequency components exhibit significantly lower temporal correlation. This frequency-dependent temporal correlation variation is precisely captured by the trained correlation filters to yield improved predictions. Designing correlation filters is a challenging task due to the complex interdependence between predictions and reconstructions in a video coding system. This issue is addressed using the iterative asymptotic closed-loop (ACL) design paradigm. By fixing the reconstructions across design iterations within the ACL framework, the correlation filters are applied to the exact data statistics used during their optimization. This prevents statistical mismatch between filter design and application, thus ensuring a stable design procedure. The second line of research investigates prediction residual coding in V-PCC. Because V-PCC employs patch-based projection methods to generate geometry and attribute videos, the resulting frames contain large empty regions filled with unoccupied pixels that do not impact the quality of the reconstructed point cloud. While the transmitted binary occupancy map explicitly distinguishes occupied and unoccupied pixels, standard video codecs employing frequency domain transforms are unable to incorporate the spatial domain occupancy information during rate-distortion optimization (RDO). To achieve occupancy-aware compression, we propose an entropy-constrained vector quantization (ECVQ) based methodology as a powerful coding tool. By training an ECVQ based on an occupancy-switched distortion measure - an error metric that ignores the reconstruction quality of the unoccupied pixels - we can make occupancy-aware RD decisions during encoding. Furthermore, because conventional transforms followed by scalar quantization can be mathematically interpreted as a special case of VQ partitioning, our approach theoretically guarantees superior performance. By embedding the design of the proposed occupancy-aware ECVQ within the ACL framework, we ensure a stable system design and establish ECVQ as a highly competitive compression strategy. Finally, to mitigate the issues of exponential growth of codebook size and search complexity that occurs when applying ECVQ to high dimensional residual blocks, we demonstrate the efficacy of entropy-constrained multistage vector quantization (EC-MSVQ). Although this structural constraint introduces a modest drop in RD performance, it achieves significantly lower search and storage complexity. Substantial bitrate savings over the anchor codec illustrate the efficacy of the proposed methods.