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The Role of Small-Scale Cloud, Aerosol, and Radiation Processes for Earth's Climate
Get PDF What makes clouds ethereal and beautiful also makes them complex and challenging to understand and to model. The important (thermo)dynamical processes of clouds occur at scales from microns (cloud-aerosol interactions), to meters (turbulence), to thousands of kilometers (synoptic weather patterns), and every scale in between. In this thesis, I explore several facets of how clouds interact with, respond to, and shape Earth's climate. I focus on small-scale processes, using high-resolution models and theory, to understand phenomena that can have large-scale impacts.
In the first three chapters of this thesis, I explore the idea of stratocumulus-cumulus transitions. Chapters 1 and 2 develop and demonstrate a conceptual model of a cloud-topped atmospheric boundary layer, which is rooted in mixed-layer theory. This model is able to concisely explain both the spatial stratocumulus-cumulus transition observed in the historical period, as well as a transition that has only been hypothesized by models, which may occur in the future as the direct effect of extreme concentrations of atmospheric CO2, or which may have occurred in the past. I use this conceptual model to show the importance of sea surface temperature variations for driving the climatological transition, and on sea surface warming as a positive feedback for the CO2-induced transition. Chapter 3 extends this work to understand the global response to CO2-induced stratocumulus-cumulus transitions and the role for spatial teleconnections by embedding this conceptual model of the boundary layer into a global climate model (GCM). In the GCM we see both a fast adjustment in low cloud cover to CO2, as well as a slower surface temperature-mediated feedback. Under CO2 quadrupling, the stratocumulus cloud regions shrink in extent as the cloud-top longwave cooling is inhibited by CO2 and surface temperatures also increase.
The final two chapters diverge from the previous theme to present two studies using very high-resolution models to explore how clouds interact with i) aerosols and ii) radiation. In Chapter 4, using a particle-based cloud microphysics model, I find that aerosol hygroscopicity, determined by the chemical composition of the particles, can alter stratocumulus cloud macrophysical properties, like liquid water path by up to 25% (in the regime of small aerosol sizes). I compare these results to a more standard moment-based microphysics model and find that this model is overly sensitive to aerosol hygroscopicity in the regime of small aerosol sizes, but realistically represents the negative sensitivity for large aerosol sizes. Finally, in Chapter 5, I use a Monte Carlo 3D radiative transfer solver to estimate the global albedo bias introduced in models which make the standard assumption that photon fluxes in the horizontal are zero (the so-called Independent Column Approximation). I extrapolate globally from a set of resolved tropical cloud fields, using a learned empirical relation between top-of-atmosphere flux bias and cloud water path. I conclude that in a global model that resolves clouds at small-enough spatial scales, the tropical-mean, annual-mean bias may be on the order of 3 W m-2. </p
The Genetic and Neuronal Substrates of Melatonin Signaling in Zebrafish Sleep
Get PDFSleep is hypothesized to be regulated by two processes: a circadian drive, which communicates time of day to ensure that sleep is timed to the appropriate day/night phase, and a homeostatic drive, by which the propensity for sleep becomes stronger over the course of prolonged wakefulness. While studies suggest that adenosine and serotonin signaling in part mediate the homeostatic sleep drive, factors that act downstream of the circadian clock to promote sleep were unidentified until recently. Previous work in the Prober lab has shown that the nocturnal hormone melatonin acts downstream of the circadian rhythm to promote sleep in zebrafish. The downstream processes by which melatonin promotes sleep is poorly understood across all animal models. This is likely because melatonin research has been primarily conducted using nocturnal laboratory rodent models, in whom melatonin does not seem to play a role in sleep, and because of the widely held view that melatonin informs the circadian clock and does not promote sleep directly. In Chapter 1 of this thesis, I review some of the research conducted over the last 50 years that has informed our current understanding of melatonin and its role in sleep. In Chapter 2, I describe our efforts to use the zebrafish, in which melatonin is both potently sedating and essential for nightly sleep, to uncover some of the mechanisms by which melatonin might promote sleep. We found that melatonin acts through a particular melatonin receptor family called MT1, whereas melatonin receptors belonging to other families were dispensable for sleep. We show that MT1 receptors are expressed broadly throughout the zebrafish brain and are enriched in brain regions involved in sensory processing, particularly in those related to vision. We tested the hypothesis that melatonin promotes sleep, at least in part, by dampening visual responsiveness at night. We show that, separable from sleep, exogenous melatonin suppresses behavioral responses to light stimuli, and loss of endogenous melatonin results in day-like behavioral responses to light stimuli during the night. We are using whole brain imaging in live zebrafish to corroborate our behavioral results with neuronal GCaMP recordings. We hope that the findings presented here contribute to a greater understanding of melatonin’s role in sleep, which may help enhance its value as a natural therapeutic aid
Numerical Simulations of Cavitating Bubbles in Elastic and Viscoelastic Materials for Biomedical Applications
Get PDFThe interactions of cavitating bubbles with elastic and viscoelastic materials play a central role in many biomedical applications. This thesis makes use of numerical modeling and data-driven approaches to characterize soft biomaterials at high strain rates via observation of bubble dynamics, and to model burst-wave lithotripsy, a focused ultrasound therapy to break kidney stones.
In the first part of the thesis, a data assimilation framework is developed for cavitation rheometry, a technique that uses bubble dynamics to characterize soft, viscoelastic materials at high strain-rates. This framework aims to determine material properties that best fit observed cavitating bubble dynamics. We propose ensemble-based data assimilation methods to solve this inverse problem. This approach is validated with surrogate data generated by adding random noise to simulated bubble radius time histories, and we show that we can confidently and efficiently estimate parameters of interest within 5% given an iterative Kalman smoother approach and an ensemble- based 4D-Var hybrid technique. The developed framework is applied to experimental data in three distinct settings, with varying bubble nucleation methods, cavitation media, and using different material constitutive models. We demonstrate that the mechanical properties of gels used in each experiment can be estimated quickly and accurately despite experimental inconsistencies, model error, and noisy data. The framework is used to further our understanding of the underlying physics and identify limitations of our bubble dynamics model for violent bubble collapse.
In the second part of the thesis, we simulate burst-wave lithotripsy (BWL), a non- invasive treatment for kidney stones that relies on repeated short bursts of focused ultrasound. Numerical approaches to study BWL require simulation of acoustic waves interacting with solid stones as well as bubble clouds which can nucleate ahead of the stone. We implement and validate a hypoelastic material model, which, with the addition of a continuum damage model and calibration of a spherically- focused transducer array, enables us to determine how effective various treatment strategies are with arbitrary stones. We present a preliminary investigation of the bubble dynamics occurring during treatment, and their impact on damage to the stone. Finally, we propose a strategy to reduce shielding by collapsing bubbles ahead of the stone via introduction of a secondary, low-frequency ultrasound pulse during treatment.</p
Additive Manufacturing of Batteries and IR-Active Microparticles: Polyborane-Based Electrolytes for Solid State Batteries and Additively Manufactured, TiN-Coated Microbridges
Get PDFAdvances in additive manufacturing (AM) processes are continuously opening up the material design space, providing scientists with opportunities to explore the relationship between structure, processing, and materials properties in new contexts. The first project presented in this thesis presents the design and refinement of a novel, polyborane-based solid electrolyte, whose design and investigation were motivated by the advent of additively manufactured, 3D electrodes, which could play a pivotal role in enabling next-generation batteries that can store more energy without sacrificing power. The first iteration of this electrolyte was synthesized by hydroborating polybutadiene with 9-borabicyclo(3.3.1)nonane (9-BBN). The resultant poly(9-BBN) was then reacted with precise amounts of n-butyllithium (n-BuLi), an organolithium reagent, to create the final polymer electrolyte. The polymer electrolyte films were assembled into a custom apparatus for impedance measurements, and though found to be ionically conductive, these measurements were not consistent, even within films made from the same batch of polymer in solution.
This necessitated the modification of the electrolyte into a UV-cured version, which was achieved by hydroboration of polybutadiene using 9-BBN. The resulting poly(9BBN)-co-polybutadiene is treated with lithium tert-butoxide (LiOtBu) and crosslinked to produce a precursor resin, which is then drop cast onto PTFE spacers, UV-cured for 5 minutes, dried, and assembled into coin cells for electrochemical impedance spectroscopy (EIS) and into pans for differential scanning calorimetry (DSC). The ionic conductivity of the PBEs as measured by EIS as a function of molar salt ratio, r = molLi/molB, does not track with their measured glass transition temperatures, Tg or the activation energies, Ea, extracted from fitting the Vogel-Tammann-Fulcher (VTF) equation to the conductivity data. Beyond r = 0.33, values for Tg and Ea demonstrate insensitivity to increasing concentration, while conductivity continues to change with concentration and reaches a maximum at r = 0.75. Moreover, measurement of ionic conductivity of control PBE films without boron on the polybutadiene backbone confirms that the presence of Lewis-acidic boron groups is necessary for ionic solvation and conduction. Further analysis that compared the PBEs to a well-studied PEO-based electrolyte in the literature through the calculation of a reduced conductivity to control for polymer viscosity and segmental motion revealed that PBEs obtain optimal conductivity at higher salt concentrations than PEO, and that their ionic conductivities are far below that of PEO. We posit that we are observing a mechanism of ionic conduction in a glassy regime partially decoupled from the relaxation of the polymer host. We attribute these effects to the strong interaction between the Lewis-acidic boron centers and the strongly Lewis-basic tert-butoxide anions, which limits ionic conductivity by suppressing motion of the anions and presenting a large activation barrier for motion of Li+, which is optimized at high concentrations where the distance between the boron-anion centers is sufficiently small to increase the probability of a hopping event from one center to another.
Nanorods fashioned from noble metals are ideal for maximizing extinction of electromagnetic radiation, which is necessary for plasmonically active materials in numerous applications, from contrast agents for biological imaging to effective obscurants. Key challenges that prevent nanorods from being employed for these technological applications include the prohibitively expensive cost of Au and Ag, their lack of requisite thermal and chemical stability, and the limitations in resolution and attainable feature sizes produced by existing wet chemistry techniques. The second project in this thesis focuses on the development of an AM process to create arrays of TiN-coated microbridges with lengths of 4.749 microns, cross-sections with dimensions of 0.692 by 2.256 microns, and effective aspect ratios of 3.368, that are capable of attenuating light reflected from a TiN-coated sapphire substrate by more than 80% in the mid-infrared (mid-IR), as measured by Fourier Transform Infrared (FTIR) spectroscopy. FTIR spectroscopy measurements further reveal attenuation of light transmitted through the same TiN-coated structures by up to 35% in the near- to mid-IR. These results indicate a promising pathway for AM of plasmonically active microparticles with broad reflectance and transmittance attenuation of light in the near- and mid-IR.</p
Nonlinear and Multidimensional Terahertz Spectroscopy of Liquids and Crystalline Solids
Get PDFThe delocalized and correlated nuclear degrees of freedom in the terahertz (THz) regime strongly influences the room temperature chemical and physical properties of condensed matter systems, yet detailed understanding of the photo-induced dynamics and anharmonicities of the vibrational modes have remained elusive. In hydrogen-bonded liquids, these information facilitates the development of accurate force field models to aid simulations of biological processes of proteins and DNAs. In the field of nonlinear phononics, anharmonic lattice vibrations form the foundation for ultrafast coherent control of material properties, which has become an indispensable technique in the engineering toolbox for quantum materials. In this thesis, we demonstrate the development and application of nonlinear 1D THz Kerr effect (TKE) and 2D THz-THz-Raman (2D-TTR) ultrafast THz spectroscopies, which are specially designed to induce resonant coherent excitations of the correlative nuclear degrees of freedom in liquids and crystalline solids. By analyzing the temporal evolution of the nuclear THz-driven dynamics, insights into the excitation mechanisms, nonlinear coupling interactions, and the dominant source(s) of anharmonicity may be determined. Specifically, we developed a nonlinear imaging method based on the third-order response of electro-optic crystal GaP, which significantly improved the alignment consistency and the signal strength of 2D-TTR spectroscopy. Further, we extended an echelon-based single-shot detection scheme, originally developed in 1D TKE spectroscopy, to 2D-TTR spectroscopy, which led to up to two orders-of-magnitude reduction in acquisition time. Armed with these instrument advancements, we measured 2D-TTR spectra of liquid halogenated methanes with significantly improved signal-to-noise and a larger temporal window, which led to the identification of a novel competing sum-frequency THz excitation pathway. On the other hand, we investigated resonant driven-dynamics of the phonon-polariton modes in semiconductor LiNbO, which revealed nonlinear coupling interactions between two phonon branches that are attributed to mechanical anharmonicity. In addition, we directly observed photo-induced coherent phonon wavepackets for the layered semiconductors transition metal dichalcogenide using 1D TKE spectroscopy, which are attributed to the sum-frequency excitation pathway. These works highlight the rigorous experimental considerations and careful spectral analysis required to extract essential insight into excitation mechanisms and anharmonic contributions, while avoiding spectral artifacts due to the instrument response function. In order to provide clarity to these often misunderstood spectroscopies in the THz regime, this thesis further summaries the theories behind 1D TKE and 2D-TTR spectroscopies and the lessons we have learned from experimental realization of these exotic instruments and the analysis of complex spectral features
Enforcing Constraints in Learning-Augmented Online Optimization: Theory and Applications to Energy Systems
Get PDFIncreasing renewable penetration into the power grid is critical for combating climate change. To implement this successfully, it is crucial to design real-time dispatch algorithms that are robust to the uncertainty that renewable sources present. It has proven difficult to produce effective large-scale dispatches on the fly using traditional methods; as such, this has motivated research into incorporating modern machine learning (ML) methods into economic dispatch. In order for ML-based dispatch algorithms to be effectively deployed, they must have the level of performance guarantees necessary for a safety-critical setting like the grid, and also be able to enforce strict operational constraints. In the first part of this work, we consider the problem of designing learning-augmented algorithms for online optimization in the presence of ramp and feasibility constraints, and provide some of the first results in this space to our knowledge. We use these insights to develop learning-augmented algorithms that adhere to these constraints, and demonstrate how they can effectively balance between algorithm performance and the potential for constraint violations. In the second part of this work, we consider the complementary problem of training an ML model to perform economic dispatch in the face of complex operational constraints. In particular, we utilize a plant model and historical data from a real-world co-generation plant, and develop methods to enforce constraints in our ML model. Our results demonstrate that ML models can simultaneously achieve good performance and minimize constraint violations in a real-world dispatch setting
Polarization-Resolved, Oblique Incidence Terahertz Spectroscopy of Highly Uniform 2D Hybrid Perovskite Films
Get PDFThis thesis details the development and optimization of thin film THz transmission measurements to extract spectrally resolved vibrational anisotropy in high quality layered hybrid perovskite materials. After an introduction in Chapter 1, Chapter 2 details the design, construction, and characterization of a terahertz time-domain spectrometer from scratch. Generalized THz propagation models are presented which enable accurate and diverse implementation of THz analysis. In Chapter 3, hybrid perovskite materials are introduced and our efforts towards reliably synthesizing high quality thin film perovskites using spin coating techniques are discussed. We find that optimized thin films are achieved from tailored synthetic conditions which depend on perovskite composition. In Chapter 4, we present our investigation into the elusive yet highly influential THz vibrational properties of 2D hybrid perovskite systems. A novel implementation of oblique-incidence THz transmission measurements reveals previously unseen vibrational excitations which provide valuable insight into the fundamental photodynamics that govern perovskite optoelectronics. We conclude in Chapter 5. This thesis serves to enhance the accessibility of powerful THz spectroscopic techniques as well as support the realization of promising perovskite renewable energy technologies
Reconfigurable Metasurfaces in Nanoelectromechanical and Silicon-Organic Systems
Get PDFOver the past decade, metasurfaces, a technology referring to 2D or 3D engineered nanostructures, has demonstrated itself as a groundbreaking solution for creating compact and multifunctional optical devices. Moreover, the integration of metasurfaces with various modulation techniques enables compact yet high-performance active optical systems. In this thesis I explore various optical modes in engineered nanostructures and apply different design techniques to improve the amplitude and phase response of free-space modulators.
In Chapter 1 and 2, we first briefly introduce the concept of reconfigurable metasurfaces and its state of art. Then we introduce several nanophotonic concepts that will be used frequently in later projects and discuss the potential directions to improve modulator's performance.
In Chapter 3, we find that the dual-mode resonant metasurfaces could improve the phase response in the nanoelectromechanical system(NEMS). The interaction between the quasi-bond state in the continuum and guided mode resonance boosts the phase response up to 144 degrees.
In Chapter 4, the design target is to utilize the high-Q mode to decrease the driving voltage of the NEMS system to CMOS level. Motivated by the low-index confinement property of the slot mode, the device achieves over 10% reflection amplitude modulation with only 1.5V in the experiment. In addition, by adding a bottom gold mirror, 1.8π phase response is numerically observed. Based on the success of this device, we propose a design that could achieve subwavelength wavefront control. As a example, we show a 3-pixel optical beam deflector with 75% diffraction efficiency.
In Chapter 5, we extend the use of the slot mode into silicon-organic hybrid devices. The utilization of the slot mode achieves efficient electro-optic tuning under 17V in free space with a MHz modulation speed. We also explored various methods to enhance its phase response and discuss its feasibility. The spatial phase modulation design is also proposed with a 12-period supercell pixel. The beam deflector achieves 70% diffraction efficiency numerically.
In Chapter 6, we bring this dissertation to a close and outline potential directions for future research.
This thesis provides a foundation for the development of high-resolution and power-efficient one-dimensional spatial light modulators and showcases the potential of reconfigurable metasurfaces.</p
An Experimental and Theoretical Investigation of Decision-Making Under Risk
Get PDFThis dissertation comprises three chapters related to the fields of decision theory, game theory, and experimental economics. Chapters 1 and 2 use experimental and structural methods to study individual decision-making in the domain of risk, while Chapter 3 examines decision-making under risk in settings of strategic interaction.
In Chapter 1, co-authored with Shunto Kobayashi, we conduct the first experiment that studies two classical behaviors under risk inconsistent with Expected Utility together: the common ratio effect and preferences for randomization. We show that these two behaviors are strongly positively correlated in a manner inconsistent with the predictions of leading economic models and machine learning algorithms. Motivated by this observation, we develop a novel empirical approach which, unlike machine learning algorithms, imposes some basic assumptions on preferences but does not rely on specific decision models. We further demonstrate that this approach provides more accurate predictions---both inside and outside laboratory settings---compared to leading economic models and machine learning algorithms.
In Chapter 2, I design an experiment testing Expected Utility's central independence axiom and contemporaneously eliciting measures of decision confidence. Recent theoretical work implicates decision confidence as a central component of decision-making under risk, attributing failures of Expected Utility to a lack of confidence. I find that choices characterized by high self-reported levels of decision confidence and low response times are more likely to comply with the independence axiom. Contrary to the common certainty effect rationale for independence violations, I show that subjects predominantly violate Expected Utility by choosing risky lotteries over certain amounts when they are unconfident in their choices.
In Chapter 3, co-authored with Marco Loseto, we study static games in which players have convex preferences. Under convexity, players' preferences admit a conservative multi-utility representation: each utility generates an evaluation for each action, and actions are ranked according to the lowest evaluation. We characterize the set of optimal actions for players with convex preferences and propose an efficiency criterion to rank them. Next, we derive a new class of mixed Nash equilibria that we call ``strict'' because players strictly prefer randomization. In general, convexity may lead to a multiplicity of mixed Nash equilibria. However, we show that when they exist, only strict equilibria ensure that all mixed actions are efficient.</p
Scalar Vortex Coronagraphs for Imaging Habitable Exoplanets
Get PDFOf the over 5,600 exoplanets detected to date, less than 2% have ever been directly imaged. Direct imaging is crucial for the study of habitable exoplanets around Sun-like stars because it offers the potential to characterize their atmospheres and detect biosignatures. However, the extreme contrast between star and planet light poses immense challenges which coronagraphs aim to address. Future telescopes, like NASA's upcoming Habitable Worlds Observatory, necessitate coronagraphs capable of suppressing starlight to contrast levels of 10-10 and operating in broadband light to directly image and characterize habitable planets. To meet these ambitious goals, innovations in focal plane mask technologies and wavefront sensing and control strategies are imperative.
This thesis investigates the viability of scalar vortex coronagraphs for direct imaging of habitable exoplanets. The first part of this thesis focuses on simulation efforts for modeling various coronagraph mask topographies and laboratory testing. Analysis of current scalar vortex topographies found phase wrapping is favorable over classic vortex designs. The chromatic performance of one such design — the wrapped staircase scalar vortex coronagraph — is investigated and a laboratory demonstration is presented.
Next, this thesis explores the behavior of different wavefront sensing and control methods combined with the wrapped staircase scalar vortex coronagraph. Three techniques were implemented on a high contrast imaging testbed and competitive performance between model-free and model-based techniques was found, particularly with increasingly complex mask designs.
Lastly, new scalar vortex mask designs which combine radially and azimuthally varying features are investigated. Specifically, the benefits of adding central phase dimples to scalar masks to improve broadband performance are explored. Hybrid designs incorporating phase dimples are found to suppress chromatic leakage and show substantial improvement in broadband contrast over current scalar vortex designs.
Overall, this thesis advances the understanding and development of scalar vortex coronagraphs for exoplanet direct imaging, explores their potential for future space telescopes and highlights avenues for further research and experimentation.</p