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Resolving Earthquake Source Complexities in the Heterogeneous Earth
Get PDFWhile the commonly used simple assumptions of sources and structures allows useful first-order approximation of earthquakes, they are increasingly insufficient in characterizing the complex earthquake ruptures and the seismic wave propagations. In this thesis, I present studies that address both the source and structural complexities, as well as their interactions, using flexible parameterizations and ideas.
For large earthquakes, I develop a subevent inversion framework to determine their spatiotemporal rupture complexities, and applied it to multiple significant earthquakes. Our method does not assume a fault geometry and kinematic history, and incorporates Bayesian analysis for uncertainty assessments. In Chapter 2, I discovered that the 2018 Fiji Magnitude 8 deep earthquake doublet actually ruptured two slabs, which demonstrates local slab temperature as the critical factor for deep earthquakes, and reveals complex interactions between slabs. In Chapter 3, I determined that the 2019 Ridgecrest Magnitude 7 sequence coseismically ruptured orthogonal faults, and has superficially complex but in-depth simple fault geometries, which illustrates the fault geometrical control of the rupture behaviors which challenges traditional seismic hazard mapping. In Chapter 4, I found the 2021 South Sandwich Island Magnitude 8 earthquake consists of deep regular ruptures connected by a slow tsunamigenic event, which highlights the tsunami potential for deep initiations of megathrust earthquakes.
For smaller earthquakes, I develop a Bayesian differential moment tensor inversion (diffMT) algorithm to remove the common earth structural effects, thus improving the earthquake focal mechanism resolvability. In Chapter 5, I demonstrated that diffMT reduces the moment tensor uncertainties substantially than traditional direct-inversion methods, and found that the North Korea nuclear tests in 2013-2016 are more dominated by explosive mechanism than previous understandings.
Towards high resolution mapping of the Earth structure, I expand the seismic tomography for high resolution basin structure by combining the wide aperture of seismic stations and high density of industrial arrays. In Chapter 6, I applied this approach on the densely populated Los Angeles Basin, and found improved mapping of small scale heterogeneities, which can potentially promote earthquake ground motion assessments.
In summary, I have developed research tools and applied novel ideas on complex seismic events and heterogeneous earth environments. The results illustrate the diverse controlling factors of complex earthquake ruptures, and reveal the complex interactions between earthquakes and earth structure.</p
Transformations and Functions of Neural Representations in a Subcortical Social Behavior Network
Get PDFThe brain functions by processing sensory information such as vision, smell, and touch, integrating it with internal states (hunger, fear, aggression) and memory to produce relevant motor outputs (eating, fleeing, or fighting). To understand the brain, neuroscientists study neural representations (patterns of neural activity that correlate with features of the outside world) to and perform perturbations (activate or silence groups of neurons) to determine its function. Past studies on neural representations gave us insights into how sensory regions filter complex inputs to retain relevant information and how coordinated activity in the motor regions produce complex motor actions. However, little is known about how information is processed in the inner brain (between sensory and motor) and how behaviors are controlled. Mating and aggression are innate social behaviors that are essential for animals’ survival. During social interactions, such as those preceding mating or fighting, the brain must determine the sex of a conspecific to produce sex-appropriate behaviors that are conducive to its survival. Functional studies demonstrated that they are controlled by deep subcortical circuits in the extended amygdala and hypothalamus. My thesis attempts to understand how the inner brain works by 1) showing that chemosensory cues encoding conspecific’s sex are transformed to neural representations of mating and aggression during social interactions by recording from a genetically defined group of neurons in different regions of the extended amygdala and hypothalamus. 2) Demonstrating that the neural activity representing conspecific’s sex is necessary for the emergence of behavioral representations in the hypothalamus.</p
High Contrast Nanophotonics for Scalable Photovoltaics and Solar Fuels
Get PDFAnthropogenic climate change is a massive threat to our planet’s stability and habitability. Carbon dioxide makes up the majority of the greenhouse gas emissions leading to rising global temperatures. In order to reduce the global temperature, it is imperative to reduce dependency on fossil fuels by mass adaptation of renewable energy with net-zero carbon emissions. In this work, we present designs to convert incident solar energy to power through scalable nanophotonic systems.
We first introduce a tandem luminescent solar concentrator (LSC). LSCs are of interest due to their ability to concentrate both direct and diffuse light expanding the regions in which LSCs can be deployed. The tandem LSC uses a novel architecture in which InGaP micro-cells lie co-planar and optically coupled to the waveguide as opposed to the traditional edge-lined LSC. The waveguide consists of highly efficient CdSe/CdS quantum dots with emissions tuned to the band edge of the InGaP cells. This LSC is then coupled to a Si sub-cell allowing the tandem LSC to effectively convert a greater portion of the incident solar spectrum. We fabricate and perform outdoor testing on the first co-planar tandem LSC demonstrating a path to high efficiency LSCs.
We then introduce two methods to more efficiently trap light within the LSC. The first is a high contrast grating spectrally selective reflector. By using a high contrast grating, we can achieve high reflectivity with a single layer of high index materially patterned at a sub-wavelength scale on a low index substrate. While we explore both AlSb and a-SiC:H as grating materials, we pursue a-SiC:H and fabricate such a spectrally selective reflector with over 94% reflectivity at 642 nm. We then move to eliminate the need for spectrally selective filters by using photonic crystal waveguides to trap quantum dot emission within the LSC. We present two designs in which over 90% of emission remains trapped in the photonic crystal waveguide and is therefore able to travel to the photovoltaic material. We demonstrate how such a design can be used for LSCs in terrestrial and space solar power applications.
Lastly, we expand on the photonic crystal waveguide and introduce a thermal concentrator for production of scalable solar fuels. The thermal concentrator absorbs incident sunlight and traps the generated heat within the photonic crystal. This elevates the temperature within the thermal concentrator creating conditions under which catalytic reactions producing solar fuels can occur. We design a thermal concentrator that can heat up to 507.3 Kelvin under 1 sun illumination and 729.4 Kelvin under 3 sun illumination.</p
3-Manifolds, Q-Series, and Topological Strings
Get PDFẑ is a 3d TQFT whose existence was predicted by S. Gukov, D. Pei, P. Putrov, and C. Vafa in 2017. To each 3-manifold equipped with a spinc structure, ẑ is supposed to assign a q-series with integer coefficients that is categorifiable and provides an analytic continuation of the Witten-Reshetikhin-Turaev invariants. In 2019, S. Gukov and C. Manolescu initiated a program to mathematically construct ẑ via Dehn surgery, and as part of that they conjectured that the Melvin-Morton-Rozansky expansion of the colored Jones polynomials can be re-summed into a two-variable series FK(x,q), which is ẑ for the knot complement. Following those developments, in this thesis we develop further and generalize the theory of ẑ. Some of the main results are:
1. Proof of Gukov-Manolescu conjecture for a big class of links, including all homogeneous braid links, which gives a mathematical definition of ẑ for the complements of those links;
2. Generalization of Gukov-Pei-Putrov-Vafa formula for ẑ for negative-definite plumbed 3-manifolds to general Lie algebra;
3. Various conjectures coming out of the interpretation of FK(x,q) in terms of topological strings, such as the HOMFLY-PT analogue (i.e., a-deformation) of FK(x,q) and the holomorphic Lagrangian generalizing the A-polynomial.</p
Development of Electrochemical Processes for More Practical and Effective Onsite Wastewater Treatment
Get PDFIn spite of the lack of safely managed sanitation and water supply systems, developing countries with rapid urbanization cannot afford to implement advanced treatment technologies that are highly centralized, calling for the development of practical onsite wastewater treatment. As effective yet practical solutions to the water crisis, I have developed high-performance earth-abundant electrocatalysts and an uncoupled electro-peroxone (E-peroxone) prototype reactor that can be applied in and as decentralized wastewater treatment systems. A series of conductive TiO₂ nanotube array electrodes are known to be effective for chlorine evolution reaction (CER) for wastewater treatment and oxygen evolution reaction (OER) for water splitting. In order to further enhance their electrocatalytic activities, an ultrathin layer of Al₂O₃ was deposited onto TiO₂ nanotube arrays via atomic layer deposition (ALD). Due to the facilitated formation of Ti³⁺ and oxygen vacancies by Al₂O₃ ALD, black TiO₂ nanotube arrays with 8 ALD cycles achieved up to 30% enhancement in CER and OER overpotentials in comparison to those without Al₂O₃ coating. Moreover, the ultrathin Al₂O₃ overlayer (~2 nm) reduced the charge transfer resistance and increased the electrochemical chemical surface area (ECSA) 3-fold for both reactions. Black TiO₂ nanotube arrays with 8 cycles were applied for toilet wastewater treatment and outperformed a dimensionally stable anode (DSA) in terms of chemical oxygen demand (COD) and ammonia reductions. The simplicity of the synthetic procedures and the use of inexpensive metal oxides suggest that Al₂O₃-deposited TiO₂ nanotube arrays can provide a promising approach to wastewater treatment and water splitting as practical alternatives for costly DSAs.
The uncoupled E-peroxone reactor system integrates ozonation with in situ hydrogen peroxide (H₂O₂) production to generate hydroxyl radicals for wastewater treatment. The E-peroxone process variables such as H2O2 concentration and ozone dose were optimized to maximize the treatment efficiency. Consequently, the system succeeded in reducing COD by 89%, total organic carbon (TOC) by 91%, biochemical oxygen demand (BOD) by 86%, and turbidity by 95% after 90-minute treatment of synthetic graywater. Moreover, the system reclaimed treated wastewater as an electrolyte for H₂O₂ production for subsequent treatment and maintained over 80% and 70% reductions in COD and TOC, respectively, over four consecutive treatment cycles. This system does not need any chemical additive, utilizes the energy-efficient E-peroxone process, and comprises inexpensive, accessible components. As a result, these advantages significantly reduce the system’s capital and operational costs. The promising results and cost-effectiveness show that it can provide a viable solution for the treatment of graywater and human wastewater in low-resource settings.</p
Safe Input Regulation for Robotic Systems
Get PDFThe safety of robotic systems is paramount to their continued emergence into our lives. From collaborative industrial manipulators to drone deliveries to autonomous vehicles, safety is the primary concern when it comes to the continued adoption of these technologies. While a number of techniques can be used to design safe controllers and planners that govern the actions of these robots, few are able to provide the type of safety guarantee needed to bring these technologies into reality.
The goal of this thesis is to provide a framework for regulating, or filtering, existing control inputs before they are applied by the robot, in order to ensure that safety is upheld. To illustrate this, consider one of the primary applications for this method: human-operated robotic platforms. For vehicles, this framework would modify the throttle, braking, and steering commands from a human driver to prevent him from driving off the road or into other cars. However, when the human is operating the vehicle safely, his commands should go unaltered. This illustrates the idea of a minimally invasive safety regulator: one that only engages when absolutely necessary to ensure safety.
Within the last decade, the mathematical framework that allows us to achieve this result, control barrier functions, was introduced. Its adoption among the nonlinear controls community has been rapid, and the method has been used to create controllers that guarantee safety on a large class of systems. Despite this, real-world implementations of control barrier functions are less common, since they require a very accurate model of the system, and they can be difficult to formulate properly. This work provides several major extensions, improvements, and modifications of control barrier functions that allow them to be utilized on a variety of real-world robotic systems.
The first major contribution of this thesis is a set of formulations for safety regulators that do not depend on complete knowledge of the underlying dynamical systems. Three unique formulations are proposed, whose usages depend on the level of knowledge of the underlying system. The resulting performance and safety guarantees are analyzed in real-world applications of quadrotor collision avoidance and fast-food frying with industrial manipulators. The second major contribution is a set of two safety filtering frameworks that utilize knowledge of the full-order dynamics, but allow for guaranteed safety in the presence of input constraints on high-dimensional systems. Two formulations are given, with one designed for use on microcontrollers with minimal computational resources. Both formulations utilize the knowledge of an existing "backup controller" that attempts to take the system into a small, safe "backup set". This method is demonstrated in simulation on a robotic manipulator and a Segway robot, and on hardware for collision avoidance and geofencing of single and multi-agent racing drones. The third major contribution is a novel discrete-time formulation of control barrier functions that allow for safety regulation of discrete-time systems. We show how safety constraints can be encoded as temporal logic specifications that are enforced over discrete-time models of the systems and their environments. The fourth and final major contribution is a unified, multi-rate control framework that guarantees safety at both the high-level, in discrete-time, and the low-level, in continuous-time. A mid-level Model Predictive Controller (MPC) is used to generate reference signals based on the high-level planner which are tracked by the low-level controller.
Together, these four major contributions result in safe input regulation on a wide variety of robotic systems. Since no single method can reliably enforce safety on such a wide range of systems with different requirements, this thesis provides the smallest collection of methods that applies to the largest classes of systems.</p
Innate Navigation: Magnetic Sensation and Maze Learning
Get PDFThis thesis aims to advance the understanding of the neurobiology of navigation through the investigation of two topics: magnetic sensation and maze navigation. The central question of this work may be framed as follows: how do animals find their way to key resources that are necessary for survival? Three projects are presented to address this.
Chapter II explores a sensory hypothesis that some animals may navigate long distances by directly sensing the earth’s magnetic field. Awake zebra finches were stimulated with magnetic fields that varied sinusoidally in time while electrical recordings were collected via multi-channel electrodes. Preliminary negative results are presented, along with a detailed statistical treatment indicating no significant effect of magnetic stimulation on neural activity.
Chapter III presents a novel approach to studying learning and navigation in animal subjects. Mice are allowed free passage between a normal home cage and a complex maze environment, coming and going as they please. Sated animals, with free access to food and water, spend significant portions of a given multi-hour experiment in the maze and display efficient exploration. Water-restricted animals show three additional phenomena: immediate knowledge of the route home, rapid learning of the location of a single water port among 64 similar locations, and a moment of "sudden insight" in which the rate at which long, direct routes to the water source, beginning from many locations, increases discontinuously.
Chapter IV offers a simple, biologically feasible circuit model that recapitulates and explains some of the rapid learning behaviors we observe in mice. This model suggests a mechanism that might allow mice to flexibly store and recall direct routes to different resources that are activated by different internal drives.
The final chapter outlines some potential directions for future inquiry, including potential maze experiments to conduct with wireless electrophysiology and expansion of the range of species tested for magnetic perception. The Appendix briefly describes some follow-up experiments and intriguing preliminary results. Similarities in the navigation deficit displayed by mice that have been experimentally perturbed in several disparate ways is noted briefly. These perturbations include whisker trimming, olfactory neuron ablation, genetic ablation of cortex and hippocampus, and opiate intoxication.</p
Engineering Tools to Probe and Manipulate the Immune System at Single-Cell Resolution
Get PDFMy thesis focuses on developing experimental and computational tools to probe and manipulate cellular transcriptomes in the context of human health and disease. Chapter 1 and 2 focus on published work where we leverage single-cell RNA sequencing (scRNA-seq) to understand human immune variability, characterize cell-type specific biases of multiple viral variants within an animal, and assess temporal immune response in the brain to delivery of genetic cargo via an adeno-associated virus (AAV). Chapter 3 and 4 present progress I have made on tools for exporting RNA extracellularly and engineering of a transcription factor for modulating macrophage state.
For probing cellular transcriptome states, we have developed a platform using multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to understand temporal and inter-individual variability of gene expression within immune cell types. Our platform enables simplified, cost-effective profiling of the human immune system across subjects and time at single-cell resolution. To demonstrate the power of our platform, we performed a three day time-of-day study of four healthy individuals, generating gene expression data for 24,087 cells across 22 samples. We detected genes with cell type-specific time-of-day expression and identified robust genes and pathways particular to each individual, all of which could have been missed if analyzed with bulk RNA-sequencing. Also, using scRNA-seq, we have developed a method to screen and characterize cellular tropism of multiple AAV variants. Additionally, I have looked at AAV-mediated transcriptomic changes in animals injected with AAV-PHP.eB three days and twenty-five days post-injection. I have found that there is an upregulation of genes involved in p53 signaling in endothelial cells three days post-injection.
In the context of manipulating cellular transcriptomic states, I demonstrate that a fusion between RNA targeting enzyme, dCas13, and capsid-forming neuronal protein, Arc, is able to form a capsid-like structure capable of encapsulating RNA. I also present methods and preliminary data for tuning macrophage states through mutations in transcription factor EB (TFEB) using scRNA-seq as a readout.</p
Future Microwave Arrays Take Shape
Get PDFPhased arrays provide high gain electronically steerable beams and are powerful systems for sensing and communication. Existing phased arrays are typically small, rigid, and planar which limits their possible use cases. This thesis describes the author's contributions to the creation of novel phased array architectures which can enable new phased array systems and applications. The first chapter describes the design, testing, and use of the scalable router. Scalable routers are a time delay array relay used to reroute signals a microwave frequencies. The second chapter describes the development of large scale flexible phased arrays, first in the context the Caltech Space Solar Power Project, and then in an exploration of a technique for determining the shape of arrays using only mutual coupling between elements. Finally, a guide for developing electronics for academic space payloads is included as an appendix.</p
Principles of Massively Parallel Sequencing for Engineering and Characterizing Gene Delivery
Get PDFThe advent of massively parallel sequencing and synthesis technologies have ushered in a new paradigm of biology, where high throughput screening of billions of nucleid acid molecules and production of libraries of millions of genetic mutants are now routine in labs and clinics. During my Ph.D., I worked to develop data analysis and experimental methods that take advantage of the scale of this data, while making the minimal assumptions necessary for deriving value from their application. My Ph.D. work began with the development of software and principles for analyzing deep mutational scanning data of libraries of engineered AAV capsids. By looking at not only the top variant in a round of directed evolution, but instead a broad distribution of the variants and their phenotypes, we were able to identify AAV variants with enhanced ability to transduce specific cells in the brain after intravenous injection. I then shifted to better understand the phenotypic profile of these engineered variants. To that end, I turned to single-cell RNA sequencing to seek to identify, with high resolution, the delivery profile of these variants in all cell types present in the cortex of a mouse brain. I began by developing infrastructure and tools for dealing with the data analysis demands of these experiments. Then, by delivering an engineered variant to the animal, I was able to use the single-cell RNA sequencing profile, coupled with a sequencing readout of the delivered genetic cargo present in each cell type, to define the variant’s tropism across the full spectrum of cell types in a single step. To increase the throughput of this experimental paradigm, I then worked to develop a multiplexing strategy for delivering up to 7 engineered variants in a single animal, and obtain the same high resolution readout for each variant in a single experiment. Finally, to take a step towards translation to human diagnostics, I leveraged the tools I built for scaling single-cell RNA sequencing studies and worked to develop a protocol for obtaining single-cell immune profiles of low volumes of self-collected blood. This study enabled repeat sampling in a short period of time, and revealed an incredible richness in individual variability and time-of-day dependence of human immune gene expression. Together, my Ph.D. work provides strategies for employing massively parallel sequencing and synthesis for new biological applications, and builds towards a future paradigm where personalized, high-resolution sequencing might be coupled with modular, customized gene therapy delivery.</p