VictorJuiz/thesis huggingface dataset:
Modeling, Designing, and Measuring EUV Photomasks

We present a selection of topics relating to modeling, designing, and measuring EUV (Extreme Ultraviolet) photomasks, with implications for high-volume nanofabrication of integrated circuits. These EUV photomasks must be accurately designed, but rigorously modeling large domains is extremely computationally intensive; we introduce an approximateFresnel Double Scattering model which is 10,000x faster. This approximation can predict the trend of phase vs pitch, which is critical to designing EUV phase shift masks (PSMs). We also explore novel mask architectures to improve efficiency and contrast, such as an etched multilayer PSM (up to 6x throughput but restrictive applicability), aperiodic multilayers (up to +22% throughput and more general applicability), and multilayers with minimal propagation distance at certain angles (lower throughput but higher contrast with minimized 3D effects). Finally we explore computational metrology with EUV reflectometry, scatterometry, and imaging for probing the phase and amplitude response of an EUV mask, with experimental demonstrations at the Advanced Light Source synchrotron. We perform reflectometry experiments on 3 masks with different architectures to infer approximately 25 physical film parameters each. Another reflectometry application to contamination monitoring achieved single-picometer precision for thickness (3σ < 6pm) and sub-degree precision for phase (3σ < 0.2deg). We compare two implementations of phase scatterometry, either applying nonlinear optimization with approximate scattering, or linearizing the rigorous scattering relationship between intensity and phase; linearization is shown to generally be more accurate, but both methods have similar precision. We apply novel software and hardware for phase imaging, using PhaseLift convex phase retrieval, combined with a set of custom Zernike Phase Contrast (ZPC) zone plates. We perform hyperspectral ZPC phase imaging on 3 masks, where we see promising agreement with reflectometry in the trend of phase vs wavelength.

Advisor: Waller, Laura
Neureuther, Andrew R
The Law of the Sea and the Resolution of the South China Sea Dispute under International Relations Theories

This dissertation examines the legal resolution of the South China Sea dispute in light of theories of international relations. One of the purposes of international law of the sea is to control both present and future state behavior at sea. However, the South China Sea dispute still remains one of the most difficult conflicts of our time despite the UN Convention on the Law of the Sea (UNCLOS) and international lawyers’ efforts to suggest a peaceful resolution. As the US-Chinese rivalry increases in size and weight in East Asia, the possibility of peaceably resolving the dispute decreases. Given that international law functions within international politics, any legal suggestions should be tested against the reality of international relations. In this respect, a legal resolution for the South China Sea dispute needs to be discussed and advanced within the context of the analysis of political scientists. The dissertation begins by reviewing the formal law regarding territorial and maritime disputes in the South China Sea, followed by exploring the different legal perspectives between China and the West on the international legal system as a whole, the law of the sea regime, and the South China Sea dispute. The utility and fertility of the law of the sea system and the urgent need to clarify core UNLOS institutions are examined. The dissertation also surveys how political scientists evaluate the South China Sea dispute in accordance with three theoretical lenses: realism, liberalism, and constructivism. Each theory’s analysis and prediction regarding the South China Sea dispute may inform the legal consideration of international lawyers. Realism urges international law to reflect the shift of power distribution, and at the same time, warns international lawyers to proactively come up with measures to avoid hegemonic war between China and the United States. On the other hand, liberalism and constructivism call on international law to consider ways to boost cooperation in the region. A well-designed regional maritime regime has been suggested by both theorists as an efficient way of managing and resolving the territorial and maritime disputes in the South China Sea. Proposals how international law of the sea can mitigate the South China Sea dispute follow in two aspects: (1) the law of the sea regime should reflect the power shift between China and the United States by agreeing on bilateral declarations or agreements, or using the mode of modification under the in-built UNCLOS mechanism; and (2) the disputants and stake-holders should consider establishing a soft-law regime (the South China Sea Council), as is the case with the Arctic Council for the territorial and maritime dispute in the Arctic Ocean.

Advisor: Yoo, John C.
Millimeter-Wave Receiver and Package Design Close to the Device Activity Limits

For several decades, rapid improvements in the semiconductor industry, particularly the scaling of CMOS processes, have enabled high-speed wireless communications. However, the scaling of CMOS processes seems to be paying off less and less. Moreover, as the carrier frequency increases, the limited power of the CMOS chip can be quickly dissipated by passive elements or at the edges of the chip. The next generations of high-speed radios will require co-design and co-optimization of the chip and package to ensure that the highest data rates are achieved.This work addresses the design of a packaged wideband millimeter-wave radio. The fun- damental limitations of the CMOS process for millimeter-wave applications are examined. Noise measure theory is used to design low-noise amplifiers near the device activity limits. New techniques for minimizing the insertion loss of passive matching networks are proposed. The challenges of a package design are investigated, and an optimized transition structure is proposed. Finally, a 140GHz wideband receiver operating at half the transit frequency of the technology is implemented.

Advisor: Niknejad, Ali M
Development of an Enzymatic Oxidative Coupling Bioconjugation and its Application in the Synthesis of Immunoconjugates

The ability to construct site-specific protein bioconjugates has a range of applications in basic and applied science. Many biorthogonal chemistries have been developed to modify proteins at well-defined sites, but these often require the introduction of artificial functionality into a protein sequence, a laborious process that comes at the cost of protein expression. An alternative approach targets native functionality present in a protein sequence, such as the N- or C-terminus, for which most proteins have one. Herein I developed a suite of enzymatic methods for the modification of protein termini all using the enzyme tyrosinase. In an initial demonstration I showed that tyrosinase can oxidize small molecule phenols, generating a reactive o-quinone intermediate, which covalently modifies protein N-termini. This strategy has a number of key advantages, including the use of catalytic amounts of commercially available enzyme and easily accessible reagents. This work laid the foundation for a new research area in the lab focused on the development of tyrosinase-mediated bioconjugations. I then worked in a collaborative team effort to extend this approach to protein C-termini, where tyrosinase could be used to generate site-specific o-quinones at introduced tyrosine-tags. These could couple to free thiols on a different protein, allowing for the rapid and facile synthesis of protein-protein conjugates. I ultimately applied this method towards the modification of the cell surface, where I used tyrosinase to synthesize nanobody-natural killer conjugates that could elicit targeted cell killing. Together, these methods have enabled the synthesis of complex bioconjugates that were previously difficult to access.

Advisor: Francis, Matthew B.
Fully Integrated Electronic-Biophotonic System-on-Chip for Real-Time Label-Free Molecular Sensing

Label-free miniaturized optical sensors can have a tremendous impact on highly sensitive and scalable Point-of-Care (PoC) diagnostics by monitoring in real-time molecular interactions without any labels. However, current biophotonic platforms are limited by complex optical and external readout equipment, precluding their use in a PoC setting. In this research, we aim to address this challenge by developing a first of its kind fully integrated electronic-photonic real-time label-free molecular sensor utilizing micro-ring resonators (MRRs) co-integrated with on-chip electronics in a high volume advanced electronic process. This technology will reduce cost and enable self-contained and miniaturized Point-of-Care devices that are needed in healthcare applications./nThis thesis introduces an arrayed electronic-photonic system-on-chip (EPSoC) in GlobalFoundries (GF) 45nm RFSOI with 60 5μm radius MRRs connected to on-chip receivers, approaching a limit of detection (LoD) equivalent to a single 140nm viral particle. In order to deliver multiple fluidic solutions and enable multi-analyte sensing, we propose an efficient packaging strategy for fabricating multi-channel microfluidic networks interfacing with mm-scale chips. Leveraging co-integration of planar MRRs with on-chip receivers, we eliminate the need for a tunable laser and external readout equipment by shifting the requirements of resonance tuning and readout processing to the electronic domain. To further enhance the LoD we propose a dual-ring phase-based sensing architecture, boosting the system’s sensitivity by 3.7x compared to intensity-based single MRR schemes. The inherent intrinsic limitations of MRRs due to environmental variations are addressed with an on-chip differential scheme using sensing and reference rings to cancel common mode errors. We demonstrate the sensing capabilities of the EPSoC by monitoring in real-time binding events of proteins and nanoparticles, unlocking the door towards self-contained fully integrated Lab-on-Chip (LoC) photonic sensors for PoC applications.

Advisor: Stojanovic, Vladimir
Statistical Learning Methods to Identify Latent Patterns in Sequential and High-dimensional Biological Data

Rapid advances in biological technology have resulted in a wealth of data. One intriguing topic mixes large-scale data from the current era with traditional small-scale data. That is, when laboratory experiments are unable to generate true labels at a rate that matches the rate of data synthesis, it raises the need for new statistical methods to detect latent patterns and predict large volumes of unlabelled data using the information contained in the existing labels, which are of relatively small size. We studied two problems of this kind. To extract latent patterns and identify functionally similar polymer sequences in unsupervised sequential datasets, we developed a scalable probabilistic graphical model and efficient stochastic variational methods. It provides consistent results on proton transport performance compared to wet lab experiments, and exhibits the potential to aid in predictable synthesized polymer performance. To extract latent patterns and identify functionally similar genes in semi-supervised high-dimensional datasets, we proposed a computational framework involving dimension reduction, clustering, sub-sampling and bagging-inspired aggregation, named GeneFishing. It successfully identified genes relevant to certain biological processes in a context-specific manner. This thesis shows efforts to integrate classic statistical concepts and modern large-scale machine learning techniques to estimate and predict from rapidly growing datasets, and to extract hidden patterns from a variety of data types and problem formulations.

Advisor: Huang, Haiyan
A Group Theoretic Framework for Neural Computation

How do networks of neurons compute stable representations of continually transforming sense data? This thesis aims to provide a mathematical foundation for this question based in group theory -- the mathematics that describes much of the transformation structure in natural visual signals. The primary contribution of this thesis is a framework that ties group theory to neurophysiologically plausible computational mechanisms by way of generalized Fourier analysis and its roots in group representation theory. I demonstrate mathematically and computationally how group representations may be instantiated in biological neurons to achieve robust invariance and equivariance to signal transforms. I further demonstrate how complete, selective group invariance can be achieved in a third-order generalization of the classical energy model of complex cells, based on the bispectrum. This perspective offers a reframing and generalization of canonical models of receptive fields in visual cortex, explains extra-classical results, and makes novel empirical predictions. I additionally demonstrate the utility of this mathematical framework for building artificial neural networks with improved robustness and invariance and apply these architectures to the problems of learning latent transformation structure from data and group-invariant denoising of signals in associative memory networks.

Advisor: Piantadosi, Steve
Get a Hold of Yourself! Links between Valuing Emotion Control, Responses to Others’ Emotions, and Relationship Quality

We frequently encounter other people’s emotions, and how we respond to them should have important implications for the quality of our relationships. Individuals who value emotion control (i.e., think emotions should be controlled versus expressed) may respond more negatively to others’ emotional expressions, and in turn, experience lower-quality relationships. We tested this proposition across six samples using multi-method designs. Valuing emotion control was associated with lower relationship quality in three diverse samples: US undergraduates, US community adults, and US Chinese-American adolescents (Study 1; N total=780). Furthermore, valuing emotion control was associated with more negative judgments of romantic partners’ emotions during a laboratory conflict conversation (Study 2; N=376; 187 couples), and more negative responses to a friend’s or romantic partner’s emotions, which in turn accounted for lower relationship quality (Studies 3a, 3b; Ns = 226, 353). In sum, these results suggest that valuing emotion control is linked with crucial drawbacks for people’s relationships.

Advisor: Mauss, Iris
Neural Circuit Dynamics Estimation and Control

We present a high-throughput, scalable, and biophysically informed effective connectivity mapping method for a population of neurons via two photon holography optogenetics. Specifically, we derive a simple neural circuit dynamics model from basic biophysical principles and introduce a fast algorithm that best estimates the connectivity among the neurons in a network given the observed neural population activity. The algorithm leverages the state-of-the-art two photon holography optogenetic technique and calcium trace imaging as a proxy for neuron membrane potential to optimally estimate the connectivity of neurons residing inside a three-dimensional volume with dimensions spanning hundreds of microns. Using 3D-SHOT, a two photon holography optogenetics technique capable of stimulating custom ensembles of neurons with cellular resolution and millisecond-order time precision, combined with GCaMP6, a contemporary genetically encoded calcium indicator, imaging, we observe the activity of both stimulated and neighboring neurons inside the neocortex of both awake and anesthetized mice in vivo. With these modern technologies at hand, we use the derived deterministic and linear autoregressive model of an arbitrary order with a feed-forward optogenetic stimuli input to describe the population-level time evolution of neural activities in a network. We utilize the ideas in causal inference, compressed sensing, and parallel computing to efficiently estimate the aforementioned model parameters, which directly translate to the connectivity matrices that characterize the effective interactions among the observed neurons. Furthermore, interference framework in experimental design and network control algorithm based on a graph-theoretic centrality measure are applied to provide a higher fidelity summary statistics of the connections among a subset of selected neurons and to artificially drive the network to specific brain states, respectively. With the estimated biophysical model describing the partial dynamics of neuronal interactions, inferences regarding both the spatial and temporal signatures of a local region of the brain can be made.

Advisor: Liu, Chunlei
Prediction’s Role in Perceptual Selection

Perception is influenced by predictions about the sensory environment. These predictions are informed by past experience and can be shaped by exposure to recurring patterns of sensory stimulation. Predictions can enhance perception of a predicted stimulus, but they can also suppress it by favoring novel and unexpected sensory information that is inconsistent with the predictions. Here we investigate the role of prediction on visual perception by measuring how different types of predictions affect perceptual selection. We measure perceptual selection using binocular rivalry, a bistable phenomenon in which incompatible images presented separately to the two eyes result in perceptual alternation between the two images over time./nIn one study, we show that by creating predictive priors through repeated exposure to arbitrary sequence of orientation gratings, subjects were more likely to perceive the grating that matched the orientation that was consistent with the predictive context. That is, observers were more likely to see what they expected to see, compared to the likelihood of perception of the unexpected stimulus./nIn another study, we examine how other studies in the literature have reported the opposite effect of prediction on visual perceptual selection when the predictive prior is created with natural image sequences. We investigate if a relationship exists between these opposing effects of prediction. We measure this by studying effects of prediction from orientation gratings generated in our first study compared with predictions from natural images within the same individuals. We found no relationship between these two types of prediction. One possible explanation of these results is that the weighting of visual predictions differs between stimuli of different complexity. Unfortunately, although we found no correlation between these two types of predictions, we also did not replicate the effects of prediction seen previously for either type of stimuli./nFinally, we describe how binocular rivalry can be adapted for experiments outside of the lab that will be used to investigate how the constraints on conscious perception guided by visual priors may be relaxed under the influence of psychedelics in a clinical setting.

Advisor: Silver, Michael A
Scalable Geometric Processing Techniques with Applications in Characterizing Additively Manufactured Composites

Fiber-reinforced polymer (FRP) composites are widely used in aerospace, marine, automotive, and other industries due to their superior strength-to-weight ratio and corrosion resistance. Analyzing FRP cross-sectional micrographs is one of the most widely used approaches for defect detection, quality inspection, failure analysis, and computational materials modeling. Although micrographs are widely used, a lack of specialized image and geometric processing techniques forces materials science researchers to manually analyze images, which makes the analysis process time-consuming and error-prone./nIn this research, efficient and scalable geometric processing algorithms are proposed in order to characterize FRP materials and inspect their microstructure from microscope images. We develop two methods to automatically identify a major defect as well as microstructural feature in FRP composites: the resin-rich areas, which refer to areas of reduced strength caused by the lack of fiber reinforcements. We apply the concept of alpha-shapes and alpha-hulls to formalize mathematical definitions of the boundaries of resin-rich areas, and design efficient and scalable algorithms to compute the defined boundaries. In addition, a fiber recognition algorithm that automatically identifies and evaluates the breakage of the fiber cross-sections, and a GPU-based algorithm that efficiently constructs Voronoi diagrams of spheres/circles, are designed./nThese methods enable us to provide statistical analyses to quantitatively characterize the identified resin-rich areas. The rigorous mathematical definition of resin-rich areas and ability to collect thorough statistics will facilitate better understanding and quantification of the relationship between resin-rich areas and material properties.

Advisor: McMains, Sara
Spatially Quasi-Periodic Gravity-Capillary Waves

In this thesis, we study the problem of two dimensional spatially quasi-periodic gravity-capillary waves on the surface of an ideal fluid of infinite depth. We formulate the water wave equations in a spatially quasi-periodic setting and present a numerical study of solutions of both the initial value problem and the traveling wave problem. We propose a Fourier pseudo-spectral discretization of the equations of motion in which one dimensional quasi-periodic functions are represented by two dimensional periodic functions on a torus. We adopt a conformal mapping formulation and employ a quasi-periodic version of the Hilbert transform to determine the normal velocity of the free surface. Two time-stepping schemes of the initial value problem are proposed, an explicit Runge-Kutta (ERK) method and an exponential time-differencing (ETD) scheme. We present an example of a periodic wave profile containing vertical tangent lines that is set in motion with a quasi-periodic velocity potential. We formulate the traveling wave problem as a nonlinear least squares problem that we solve using a variant of the Levenberg-Marquardt method. Two types of quasi-periodic traveling solutions are computed: small-amplitude solutions that bifurcate from the zero solution and large-amplitude solutions that bifurcate from finite-amplitude periodic traveling solutions. Solutions of the first type are identified by two bifurcation parameters. We also compute the leading terms of the asymptotic expansion of the solution using these parameters. For solutions of the second type, we apply the Fourier-Bloch decomposition to study the linearization around periodic traveling solutions and obtain a one-parameter family of quasi-periodic solutions bifurcating from the branch of periodic solutions. As an example, we compute a branch of quasi-periodic overturning traveling solutions that bifurcate from a periodic overturning traveling solution.

Advisor: Wilkening, Jon