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Analysis of Metal-Oxide Protected Photoelectrochemical Systems for Water Splitting
Get PDFThe photoelectrochemical splitting of water into oxygen and hydrogen gas is one pathway toward the renewable and economic generation of a fuel which is sufficiently scalable to power a large fraction, or even a majority, of the power requirements of
modern society. In order to make such a device economically promising, it must be sufficiently cheap, have sufficiently high efficiency, or some combination thereof. In this work, two primary routes toward such a device are discussed; the first is the use of a cheaply prepared photoanode material, BiVO4, the interactions of this material with cobalt oxide based catalysts, and the use of such structures in more extreme pH ranges than have previous been reported. The second route details the application of a protective layer, TiO2, on otherwise unstable materials such as GaP and CdTe when operated as
photoanodes in alkaline media. The further work herein applies operando ambientpressure x-ray photoelectron spectroscopy (AP-XPS) to understand the nature of the energetics which allow conduction in the aforementioned TiO2, as well as other
energetics in the electrochemical double layer in the adjacent electrolyte. Further experiments using Raman spectroscopy on associated III-V photoanode devices are also described
Finding Clementia - Excerpt
No full textThe night is dark. The clouds hide the moon. In a small, quiet town, every man has returned home and fallen into deep, dreamless sleep. Affairs lately have been uneventful, but the citizens are weary.
It is the fifth year of the reign of the Emperor Domitian. Prosperity appears to settle over the lands, yet paranoia permeates beneath the peaceful surface. While the citizens sleep, a reign of terror
steadily marches on.</p
Achieving Higher Fidelity Building Response through Emerging Technologies and Analytical Techniques
Get PDFThe integration of sensor technology into the built environment has created an opportunity for a new approach to infrastructure development and management. Using collected data and principles of general physics, we discuss means and methods of using low cost dense instrumentation to perform damage detection, structural identification, and the benefits of cyber physical systems to community resilience. A nonlinear damping strategy for braced frame structures is introduced incorporating capped levels of damping forces. The study shows the effect of having control of damping forces in nonlinear analysis and the importance of limiting energy dissipation to rational levels. The issue of sliding mass is also studied to determine the contribution to energy loss and the effect to overall response. The results indicate a need to incorporate this effect in stiff structures with intentionally decoupled mass such as data centers. Finally, a discussion on dual system structures under plastic deformation in a post event deformed configuration is presented. A suggested displacement based method for design is suggested for implementation into future editions of the building code
Development of Synthetic Strategies for the Total Synthesis of Ent-Kauranoid and Diterpenoid Alkaloid Natural Products
Get PDFAs part of an ongoing synthetic effort directed towards biologically active ent-kauranoid natural products, the preparation of two structurally unique natural products, (–)-trichorabdal A and (–)-longikaurin E, is presented. The syntheses intercept an early intermediate from the synthetic route towards the rearranged natural product (–)-maoecrystal Z, and thus, represents a unified synthetic strategy to access structurally unique ent-kauranoids. Specifically, the syntheses are enabled by a palladium-mediated oxidative cyclization of a silyl ketene acetal to install a key quaternary center within the bicyclo[3.2.1]octane unit, as well as a reductive cyclization of an aldehyde-lactone to construct the oxabicyclo[2.2.2]octane motif of (–)-longikaurin E.
A synthetic strategy to access C19-diterpenoid alkaloids, specifically of the aconitine type, is presented. These highly bridged polycyclic natural products are generally characterized by a substituted piperidyl ring bridging a hydrindane framework that is further attached to a bicyclo[3.2.1]octane. The synthetic strategy relies on the enantioselective synthesis of two bicyclic fragments, which are coupled in a convergent fashion through a 1,2-addition/semipinacol rearrangement sequence to forge a sterically hindered quaternary center. Efficient access to late stage intermediates has enabled the synthesis of the aconitine carbocyclic core, with appropriate functionality for advancement to a selective voltage-gated K+ channel blocker, talatisamine. Additionally, the synthetic strategy described herein is well applicable to the synthesis of related denudatine and napelline type C20-diterpenoid alkaloids.</p
Controlling the Flow of Light Using High-Contrast Metastructures
Get PDFA new class of planar optical components and devices has emerged using subwavelength metastructures with a strong contrast in refractive indices. High-contrast metastructures have shown promises to manipulate optical fields in an extraordinary way and to replace conventional bulky optical elements by their low-profile analogs, typically with subwavelength-scale features. We elucidate the underlying principle, how these seemingly low-profile geometries render unique optical responses, using the coupled-mode analysis in a multimode waveguide. Moreover, strong field localization in high-index structures allows us to interpret each single element in the metastructures as a low-quality-factor resonator (or a localized scatterer), permitting us to realize designer surface that shapes phase, amplitude, and polarization of light in free space, also known as an optical metasurface. The remainder of the thesis is devoted to explore novel applications in optics using high-contrast metastructures. One of the particularly interesting applications is to use them in an optical resonator. Specifically, we demonstrate to incorporate high-contrast subwavelength grating reflectors and dielectric metasufaces in a vertical Fabry–Perot cavity, and show that we can flexibly tune the resonance frequency by the subwavelength patterning. With this technique, we envision the realization of compact, on-chip spectrometers when integrating them on a photodetector array. Secondly, we investigate the use of high-contrast subwavelength gratings in visible wavelengths. We perform the optimization of their geometries and demonstrate a set of RGB color filters, down to near a micrometer in the pixel size. This platform exhibits unique performances such as high efficiency, angular insensitivity, and color tunability by the design. A novel device concept is also explored, where a high-contrast subwavelength grating reflector is integrated on a silicon platform to constitute an active resonant antenna, enabling high-speed, phase-dominant modulation by means of thermo-optic effect of silicon. We demonstrate an array of such active antennas, yielding a beam deflection capability. This justifies the robustness of our device design, enabling a large-scale integration of high-speed, phase-dominant spatial light modulators. Finally, we introduce a disorder-engineered metasurface in the context of wavefront shaping. Recently, wavefront shaping with disordered media has demonstrated optical manipulation capabilities beyond those of conventional optics, but translating this class of technology into a practical use has remained challenging due to enormous amounts of information needed to be characterized as the input-output responses. As a paradigm shift, we propose the use of disorder-engineered metasurface in wavefront shaping, where the disorder is programmatically designed and makes the system characterization-free prior to use. With this approach, we demonstrate high numerical aperture focusing in an extended volume as well as wide-field fluorescence imaging with unprecedented performances.</p
The Hydrodynamics of Active Particles Inside of a Porous Container and the Galerkin Boundary Element Discretization of Stokes Flow
Get PDFIn this thesis I formulate and present a novel and new framework for simulating the dynamics of arbitrarily shaped active or passive particles immersed in a Stokesian fluid and evolving under confinement by a porous container or in free space. I use a completed double layer boundary integral equation to model the particle's dynamics and combine this with a new formulation that uses a second kind integral equation for describing the motion of the porous container. This newly formulated porous container model permits fluid to pass through the container's surface at a velocity in proportion to a discontinuous jump in stress across the container's surface. This jump in stress is induced by the active particle's motion. The proposed porous container model is general in the sense that it allows fluid to pass through the membrane with finite tangential and normal velocity components. I obtain the exact analytical solution to this model when the active particle and porous container are perfectly concentric. In addition, I numerically solve this system of boundary integral equations for arbitrary particle positions, and fully characterize the particle and container dynamics by performing a vast number of trajectory studies. Both the container and particle are seen to move in complicated ways owing to their self and pairwise hydrodynamic interactions. This system is studied over a vast parameter space, for multiple container to particle size ratios, multiple types of active particles, and various permeability parameterizations. This coupled set of particle and container boundary integral equations is discretized using a novel interpretation and new extension of the Galerkin Boundary Element discretization to multi-body particle systems in Stokes flow. I also implement and extend an h-adaptive conformal mesh refinement algorithm to accurately resolve near-contact particle and container interactions. In addition, I perform all Galerkin BEM calculations on CUDA enabled GPUs, allowing for these simulations to be run on modern desktop computers in seconds. I combine all of these techniques in a modern C++ Galerkin Boundary Element Method computational framework called GPUGBEM.</p
Value-Based Decision Making and Learning as Algorithms Computed by the Nervous System
Get PDFHow do we do what we do? Casting light on this essential question, the blossoming perspective of computational cognitive neuroscience gives rise to the present exposition of the nervous system and its phenomena of value-based decision making and learning. As justified herein by not only theory but also simulation against empirical data, human decision making and learning are framed mathematically in the explicit terms of two fundamental classes of algorithms--namely, sequential sampling and reinforcement learning. These counterparts are complementary in their coverage of the dynamics of unified neural, mental, and behavioral processes at different temporal scales. Novel variants of models based on such algorithms are introduced here to account for findings from experiments including measurements of both behavior and the brain in human participants.
In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. In Chapter 2, connectionist models are proposed at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.
Decision making in any brain is imperfect and costly in terms of time and energy. Operating under such constraints, an organism could be in a position to improve performance if an opportunity arose to exploit informative patterns in the environment being searched. Such an improvement of performance could entail both faster and more accurate (i.e., reward-maximizing) decisions. Chapter 3 investigated the extent to which human participants could learn to take advantage of immediate patterns in the spatial arrangement of serially presented foods such that a region of space would consistently be associated with greater subjective value. Eye movements leading up to choices demonstrated rapidly induced biases in the selective allocation of visual fixation and attention that were accompanied by both faster and more accurate choices of desired goods as implicit learning occurred. However, for the control condition with its spatially balanced reward environment, these subjects exhibited preexisting lateralized biases for eye and hand movements (i.e., leftward and rightward, respectively) that could act in opposition not only to each other but also to the orienting biases elicited by the experimental manipulation, producing an asymmetry between the left and right hemifields with respect to performance. Potentially owing at least in part to learned cultural conventions (e.g., reading from left to right), the findings herein particularly revealed an intrinsic leftward bias underlying initial saccades in the midst of more immediate feedback-directed processes for which spatial biases can be learned flexibly to optimize oculomotor and manual control in value-based decision making. The present study thus replicates general findings of learned attentional biases in a novel context with inherently rewarding stimuli and goes on to further elucidate the interactions between endogenous and exogenous biases.
Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. For Chapter 4, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models--namely, "actor/critic" models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.</p
Development of a Method for the Copper-Catalyzed Asymmetric Propargylation of Oxime Esters
Get PDFAlkynes represent a significant motif in natural products and pharmaceutical drugs, and the wide variety of reactions they can undergo makes them a handy tool in total synthesis. They can be introduced readily in various manners, including via propargylations of ketones and aldehydes. However, one reaction that remains to be examined is the propargylation of oximes to give a propargyl hydroxylamine. Current enantioselective propargylations of oximes typically require a chiral auxiliary and/or rare metals such as palladium or indium. Having an enantioselective propargylation of oximes which could use an external ligand and more commonly available metals would facilitate use of the product in total synthesis, as well as potentially as an unnatural amino acid. Unusual amino acids including alkynes are desirable for their use in copper(I)-catalyzed azide-alkyne [3+2] dipolar cycloadditions, a common bioorthogonal reaction.
Herein, the development of a copper-catalyzed propargylation of oxime esters is described. Initial efforts to induce enantioselectivity using a zinc nucleophile-based system proved fruitless. Although some Lewis acids could raise the yield, the enantioselectivity remained very low. Therefore, new reaction conditions using a boronate nucleophile were investigated. The use of a copper catalyst with a diphosphine ligand gave the desired product in high enantioselectivity, albeit low yield.</p
Quantitative Dissection of the Allosteric and Sequence-Dependent Regulatory Genome in E. coli
Get PDFTranscriptional regulation of gene expression is one of the most ubiquitous processes in biology. But while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. One of the ways genes are regulated is through external signals. To that end, we begin by presenting a general theory of allosteric transcriptional regulation using a statistical formulation of the Monod-Wyman-Changeux model, which we rigorously test using the ubiquitous simple repression motif in Escherichia coli. We then move to consider the consequence of the regulatory sequences themselves on gene expression. Here we apply a massively parallel reporter assay, Sort-Seq, to build models that describe the sequence-dependent binding energies of transcription factors and RNA polymerase to DNA. By coupling such models to our thermodynamic models of regulation, we construct a genotype to phenotype mapping that predicts gene expression as a function of regulatory sequence. We first demonstrate this approach in the context of the allosteric simple repression motif, and then show how it can be applied broadly across a bacterial genome, in conjunction with mass spectrometry, to uncover how genes are regulated.</p