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Measurement and Modeling of Detonation-Driven Shock Tube Flows
Get PDFThe detonation driver is a device for generating the strong shock waves used in high-enthalpy hypersonic flow research facilities. The dynamic production of high-pressure and high-temperature driver gas has several advantages for shock-tube performance, however the unsteady gas dynamics of detonation waves also introduces several challenges. These are investigated here analytically and experimentally.
For forward-mode operation, where the detonation propagates into the shock-tube diaphragm, the detonation Taylor wave attenuates the driven shock, and a model is needed to predict the resulting shock dynamics. This is accomplished by first analyzing the problem of plane shock decay generally. A new approximate solution is formulated for the classic piston start-stop problem and shown to be a significant advancement over predecessors. This result is applied to the shock decay from a detonation driver, and a two-parameter model is fit to simulation data, yielding a method for predicting shock trajectories from shock-tube initial conditions.
A small-scale shock tube is designed and constructed using a detonation driver that is operable in both the forward and reverse mode. A transparent driven section is used with large field-of-view shadowgraphy to perform novel time-resolved shock speed measurements. These are used to calibrate the decay model for a forward-mode driver and enable unique observations of shock-speed oscillations, resulting from diaphragm rupture and detonation initiation processes. Results are also obtained for shock tube operation with a conventional high-pressure helium driver.
The gradients and fluctuations in post-shock flows are characterized using a heterodyne focused laser interferometer, a new instrument with advanced capabilities for measuring large phase changes with high resolution. As a development upon the FLDI, spatial filtering characteristics are preserved, and both differential and absolute phase data are acquired simultaneously, enabling a new technique for measurement of gas densities. The instrument is developed, experimentally validated, and then used to probe detonation-driven shock tube flows, achieving phase measurements of over 100 radians with milliradian resolution in a 10 MHz bandwidth. Results from forward-mode operation find that a hydrogen-oxygen driver produces remarkably disturbance-free flows. For reverse-mode operation, the amplitude of flow oscillations is found to be positively correlated with the contact-surface sound-speed ratio, and frequencies are consistent with first-order lateral acoustic waves.</p
Beyond Li: Challenges in Moving Towards Earth-Abundant Battery Materials
No full textBatteries are a necessary component towards the advancement and proliferation of modern day technology, and are also an essential piece of the transition towards renewable energy. The lithium-ion battery (LIB) is the most common type of rechargeable battery, and the archetype relies on a traditional layered transition metal oxide cathode, organic electrolyte with a lithium salt, and a graphite anode. The design of these cells has been optimized to the point that the energy densities in these batteries are approaching their theoretical capacities. Combined with the supply chain challenges associated with many typical cathode elements and increasing energy demand, this highlights the need for new earth-abundant, high energy density battery technology. This thesis addresses challenges in two such systems: Mg-S and sodium-ion batteries (SIBs). Mg-S batteries suffer from capacity fade related to the polysulfide shuttle effect, which results in loss of active material and passivation of the anode. Here, we demonstrate that the rate of passivation is inversely proportional to the chain length of the polysulfides present in solution, and that passivation can be slowed or even reversed through addition of S₈ and the consequent perturbation of existing polysulfide speciation equilibria. SIBs are frequently touted as a "drop-in" technology for LIBs due to both systems relying on mobile alkali ions, but SIBs have inherently lower energy densities due to larger Na⁺ ion. In Chapters 3 and 4 we explore anion redox as a method of increasing energy densities in SIBs--Chapter 3 shows that in LiNaFeS₂, the charge compensation mechanisms from Li and Na cycling are identical. However, Na⁺ cycling is worsened compared to Li⁺ by structural degradation from the removal and insertion of the bulky Na⁺ ion, emphasizing the differences that exist between optimizing SIB cathode performance compared with that of LIBs. In Chapter 4, we aim to develop structure-property relationships that enable a stronger understanding of anion redox that can be leveraged to design high energy density, multielectron redox cathodes. Through the examination of the electrochemically inactive NaCu1.5Fe0.5S₂ and its vacancy-containing derivative NaCu1.125Fe0.625S₂, we show that vacancies in the transition metal layer enable redox although the redox is observed occurs on the transition metals. The study also demonstrates potential limitations of ideal model systems and bulk spectroscopic analysis techniques in materials with low degrees of redox.</p
Reductive Samarium Catalysis Enabled By A Thermochemical Roadmap
Get PDFSamarium diiodide is a versatile single-electron reductant. Its reactivity is modulated by recruitment of a wide range of additives to its large coordination sphere. Binding of strong Lewis bases produces more potent Sm(II) reductants, while polar protic donors promote net proton-coupled electron transfer to a variety of unsaturated substrates including intermediates of molybdenum-catalyzed nitrogen reduction. However, samarium(II) reagents are used (super)stoichiometrically in all but a few select cases because mild, tunable methods for selective reduction of oxidized samarium(III) products back to the active samarium(III) state were unavailable at the outset of the following studies. Chapter 1 frames the challenge of catalytic samarium turnover in the context of nitrogen fixation. Proton-coupled electron transfer and inner-sphere electron transfer are introduced as two potential catalytic roles for samarium(II), and a strategy for proton-coupled reduction of problematic samarium(III)-alkoxide intermediates to achieve turnover is outlined. Chapter 2 describes a well-defined model system used to construct extended quantitative thermochemical cycles mapping proton transfer, electron transfer, and ligand association at samarium. The samarium(II) complex binds a secondary amide to generate a remarkably potent net hydrogen atom donor. In Chapter 2, this driving force is leveraged in iron-catalyzed nitrogen reduction; the strongly reducing, weakly acidic nature of the samarium reagent leads to selective generation of hydrazine over ammonia (99:1). In Chapter 3, the benchmarked samarium(III)-alkoxide protonolysis thermodynamics inform selection of Brønsted acids that can be coupled with a mild reductant (zinc powder or an applied electrochemical potential) to achieve catalytic samarium turnover in reductive coupling of ketones and acrylates to form γ-lactones. Photodriven methods for this samarium-catalyzed transformation are reported in Chapter 5. Finally, in Chapter 6, the hypothesis that samarium(II) might serve as an inner-sphere reductant in nitrogen reduction with transition metal catalysts guides design of conditions for tandem samarium/molybdenum catalysis in electrocatalytic nitrogen reduction to ammonia with the lowest driving force and highest Faradaic efficiency (82%) reported to date for a nonaqueous system at atmospheric pressure
Catalytic Proton-Coupled Reductions of Dinitrogen and Cyanide
No full textThis thesis, directly and indirectly, focuses on mechanisms and strategies for the 6H⁺/6e⁻ reduction of N₂ to NH₃ (nitrogen reduction; N₂R) using well-defined molecular catalysts. In nature, nitrogenases reduce N₂ to NH₃, but nitrogenases can also reduce cyanide to CH₄ and NH₃, making CN⁻ and N₂ reduction interesting to compare. We describe the highly selective catalytic reduction of CN⁻ to NH₃ and CH₄ by a mononuclear Fe-catalyst related to Fe-based N₂R systems. Mechanistic studies suggest several intermediates, including iron isocyanides (FeCNH), aminocarbynes (FeCNH₂), and aminocarbenes (FeC(H)NH₂⁺), allowing a comparison to N₂R. We then show the 2H⁺/2e⁻ equilibration of iron cyanide to the iron aminocarbyne complexes of these early intermediates of catalysis. Such reversible triple bond activations are rare. We show that key to this transformation is the H-bond facilitated multisite proton-coupled electron transfer (MS-PCET).
Next, seeking alternative ways to drive N₂R, a photodriven approach is explored. The Hantzsch ester (HEH₂), a dihydropyridine, is utilized as a 2H⁺/2e⁻ photoreductant, and when partnered with a suitable catalyst (Mo) and an organic buffer (collidine/collidinium; Col/ColH⁺) under blue light irradiation allows for photodriven N₂R. Catalysis is enhanced by addition of a photoredox catalyst (Ir). This photodriven N₂R is thermodynamically comparable to the industrial hydrogenation of N₂, but light is used to drive the reaction. Mechanistic studies of the Ir-free conditions show that Col-buffer is essential for transferring H⁺/e⁻ from HEH₂ to N₂. An H-bonded pre-association can form between [ColH]⁺ and HEH₂, allowing for rapid oxidative quenching of the excited HEH₂. Subsequently, the base deprotonates HEH₂•⁺, circumventing back electron transfer. In net ColH• and HEH•, two potent H-atom donors are generated. This reagent combination is competent for the photoreduction of organic substrates as well. Lessons from this mechanistic study drove the development of photodriven methods for SmIII-to-SmII reduction, an appealing prospect given SmI₂ being a potent and selective reductant, including for N₂R. HEH₂ can serve either as a direct photoreductant or as the reductive quencher for an Ir photoredox catalyst. Both methods for SmI₂ generation translate to proof-of-concept photodriven, Sm-catalyzed reductive cross-coupling reactions.</p
The Enemy of my Enemy: How Disorder and Dissipation Can Be Your Friend in Quantum Systems
No full textIn many physical quantum systems, disorder and dissipation are a nuisance that must be actively countered or minimized, or something that the utility of the system must otherwise survive. In this thesis, we study how these typically harmful concepts can actually be helpful in the right circumstances.
We first study disorder-induced localization in quantum systems---so-called \textit{many-body localization}, or MBL. MBL suppresses the spreading of information, an otherwise ubiquitous phenomenon, and thus can be leveraged to preserve information and realize new types of protected quantum order. We discuss a novel mathematical technique to measure a localization length in MBL systems and connect this length scale to the conventional picture of the MBL-thermal transition. In doing so, we are able to probe the probability distribution of the coupling between distant degrees of freedom near the transition, which contains valuable information about the nature of the MBL phase and the transition to thermalization.
We then switch gears and study how to harness dissipation for autonomous quantum error correction of Gottesman-Kitaev Preskill (GKP) qubits in superconducting circuits. Typically, dissipation destroys quantum information via decoherence, but we show how, by appropriately constraining the dissipative dynamics, dissipation can actually \textit{prevent} decoherence and counteract the effects of noise. As a result, our proposed GKP qubit enjoys exponential robustness to extrinsic noise and imperfections in the circuit/protocol. We also demonstrate how to realize robust non-Clifford gates on our proposed qubit, granting our device universal, self-correcting single qubit logic. The experimental realization of such a setup, which we discuss in detail, would represent a major step forward for the field of quantum computation.</p
Probing Astrophysics, Cosmology, and Nuclear Physics with Gravitational Waves from Black Holes and Neutron Stars
No full textGravitational waves now serve as a powerful tool for studying physics of compact objects, including black holes and neutron stars.
When two compact objects merge, they emit gravitational waves that encode information about their masses, spins, and orbital dynamics.
Ground-based detectors capture these signals, allowing us not only to measure the properties of individual mergers but also to characterize the population properties of black holes and neutron stars. In this thesis, I present a collection of works using real and simulated gravitational wave observations of compact binary coalescences to study the physics of black holes and neutron stars, and the implications these observations have on our broader understanding of astrophysics and fundamental physics.
The first part of this thesis is background material reviewing some of the theory behind gravitational waves. The second part focuses on measuring the physical properties of a compact binary coalescence detected in gravitational wave data. This includes the methods and models used in parameter estimation and a presentation of the properties of detections in the fourth Gravitational Wave Transient Catalog (GWTC-4). The third part of this thesis turns to measuring and extracting astrophysical information from the population properties of compact binaries. This features the astrophysical distributions of binary black holes as inferred from GWTC-3 and GWTC-4. I also present studies measuring specific aspects of the binary black hole mass and spin distributions, and the implications these results have for understanding binary black hole formation channels and stellar astrophysics. This section additionally features applications of population inference to studies of large-scale structure and predictions for the gravitational wave stochastic background, as well as technical discussions of the methods and custom libraries used to implement population analyses and potential biases associated with commonly-used methods. The fourth part explores how properties of dense nuclear matter are encoded in observations of neutron stars. This section includes studies using our knowledge of the nuclear equation of state to classify low-mass compact binary mergers, and results from using gravitational waves and electromagnetic observations of neutron stars to measure the equation of state and neutron star population properties.</p
A Viral Toolkit for Ultrasound Imaging of Cellular Activity and Gene Expression
No full textObserving and manipulating cell dynamics in living organisms is essential for understanding biological processes and intervening when they malfunction. However, the lack of non-invasive, non-ionizing, and cost-effective imaging technologies limits our ability to study these processes in their native context. To address this gap, we developed a toolkit for ultrasound imaging of acoustic reporter gene expression in mammalian tissues using virally-delivered gas vesicle (GV) genes. We demonstrate the versatility of this toolkit across multiple applications, including tracking engineered cell-based therapies and imaging activity-dependent gene expression in the brain.
To track cell-based therapies, we developed lentiviral vectors encoding the eight genes necessary for GV expression, achieving robust ultrasound contrast in both cell lines and primary human T cells. By expressing GVs downstream of activity-dependent promoters, we monitor T cell activation in cytotoxic T cells engaged with tumor cells. In a mouse xenograft model, we then image the targeted accumulation and proliferation of GV-expressing T cells within tumors. These ultrasound measurements, which closely correlate with immunohistological analysis, provide real-time, in vivo insights into the spatial dynamics of therapeutic cells. This approach offers a powerful tool to accelerate the development and clinical translation of cell-based therapies.
We extend this technology to the brain by engineering an AAV-based system for GV expression in primary neurons. Following intracranial injection of the GV-encoding AAVs in mice, we demonstrate longitudinal imaging of in situ gene expression in the brain over several weeks. Moreover, by using immediate early gene promoters to drive GV expression, we track changes in neuronal activity in the hippocampus during seizure episodes, enabling repeated, longitudinal imaging of brain function within the same animal. Collectively, these advancements establish a robust platform for ultrasound imaging of cellular activity and gene expression in opaque tissues, with applications ranging from cancer immunotherapy to neuroscience.</p
Structure-Guided SCHEMA Recombination of VRC01-Class Antibodies for Reduced Polyreactivity
No full textThe therapeutic administration of monoclonal antibodies (mAbs) has revolutionized treatment options for many diseases over the last decade. Recent findings from clinical trials have demonstrated that broadly neutralizing antibodies (bNAbs) could have a potential role in the future treatment and prevention of HIV-1. There is a group of broad and potent bNAbs that target the CD4-binding site (CD4bs) on the envelope glycoprotein gp120. These VRC01-class antibodies are notable for both their breadth and potency. The Bjorkman lab has designed a remarkably broad and potent bNAb, 45-46m2, that unfortunately cannot currently be used clinically due to its increased polyreactivity and short in vivo half-life. In this study we designed a SCHEMA-guided recombination library composed of sequence fragments of the VRC01-class bNAbs 45-46m2 and 3BNC117, aiming to create a bNAb that is both potent and broad but not polyreactive. We endeavored to maintain the strong binding of 45-46m2 while gaining the low polyreactivity of 3BNC117. Our analysis of this family shuffled library of chimeric antibodies revealed the sequence elements that led to strong binding to gp120 for the chimeras in our library. We also identify three key framework regions that can be modified to significantly reduce polyreactivity. Furthermore, we report three novel chimeras from the family shuffled library that bind as strongly to gp120 as 45-46m2 but are significantly reduced in polyreactivity
The Compositional Diversity of Small Planets Orbiting Low-Mass Stars
No full textThe Kepler and TESS missions have revealed that planets between the size of Earth and Neptune dominate our galaxy, showing a bimodal radius distribution that suggests distinct formation and evolution pathways. M dwarf stars offer the ideal opportunity to characterize these small planets due to their favorable planet-to-star size ratios. But M dwarf planets may differ fundamentally from those around Sun-like stars. Their cooler disk temperatures may result in more water-rich planet compositions, while their higher stellar activity rates may result in higher atmospheric mass loss rates. I investigate these questions by measuring planetary masses, radii, and bulk compositions with the first systematic transit timing variation survey of M dwarf planets discovered by the ongoing TESS survey, utilizing observations from Palomar Observatory and other small- to mid-sized telescopes. In this thesis, I present studies of four key systems from this survey: Kepler-289, where I improved planetary mass constraints by more than twofold and constrained the formation location of the outer gas giant companion; TOI-1266, where I characterized a potentially tidally heated planet with an inflated radius and a candidate water-world; LP 791-18, where I measured the bulk density of an Earth-sized planet and made predictions for its tidal heating rate that will be tested by upcoming JWST observations; and TOI-2267, a binary M dwarf system where I statistically validated a new Earth-sized planet with important implications for planet formation and migration. These systems have expanded our understanding of small planets around low-mass stars and provide valuable case studies for studies of atmospheric mass loss, the search for planets with water-rich envelopes, and the role of tidal heating in compact multi-planet systems
Aligning and Comparing Vision Representations to Improve Understanding and Performance
No full textRecent advances in large artificial intelligence (AI) models have enabled these models to perform a wide range of real-world tasks with skill levels comparable to or surpassing those of humans. In this thesis, we develop methods to compare, analyze, and align data representations from these powerful models. In Part 1, we develop methods for estimating human knowledge during a learning task and for comparing various data representations. These methods are steps towards a system designed to help us learn from AI.
In Part 2, we show how aligning models can be useful in two separate domains. First, we discover and fix a misalignment in the inputs to a powerful foundation model and show how it improves performance. Second, we show that biologically inspired object manipulation tasks can be used as a training signal for learning human-aligned representations of number. Our results demonstrate the potential for alignment and comparison methods to improve the overall performance of AI models, improve our understanding of biological intelligence, and help us discover new patterns in the natural world.</p