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The Origin and Evolution of Amorphous Silica Coatings on Young Hawaiian Basalts
Get PDFYoung basaltic lavas on the Big Island of Hawaii frequently feature brightly colored surface coatings. These coatings, the product of interaction of volcanically-derived acidic fluids with basaltic substrates, provide an opportunity to study the rates and mechanisms of early onset chemical weathering in a natural setting. Lava flows of various ages, from hours to ~40 years, at sites along Kilauea's southwest and east rift zones and at Mauna Loa were visited and sampled to determine the nature and extent of this alteration phenomenon. The coatings are composed of a layer of amorphous silica, 1-80 μm thick, capped in some cases by a 1 μm layer of Fe-Ti oxide. Raman, infrared, and 29Si nuclear magnetic resonance (NMR) spectra indicate that the coating is structurally identical to hydrous silica gel and contains unusually high structural Si-OH contents for a natural silica sample (5.4 wt% as H2O). Opaque coatings were observed on surfaces as young as one year old, and incipient siliceous alteration was observed to begin within days. Coating thickness varies with flow age, proximity to acid sources such as volcanic plumes emanating from Kilauea Caldera and Pu'u O'o, and climate. Coatings form preferentially on lavas with glassy surface layers, such as dense pahoehoe and spatter ramparts.
The silicon isotope compositions of silica coatings and basalts were measured to determine the degree of Si mobility during coating formation. Coatings are enriched in 30Si/28Si by 1-1.5‰ relative to their basalt substrates. This fractionation is opposite in direction to that previously reported for opal precipitation, suggesting that aqueous Si speciation may strongly affect the sign and magnitude of the fractionation factor. Experiments in which fresh basalt glass was partially dissolved in dilute hydrochloric or hydrofluoric acid reproduced Hawaiian silica coating morphologies. Fluids collected from all experiments displayed δ30Si fractionations, but the direction of fractionation depended on fluid chemistry.
The morphologic, spectroscopic and geochemical observations presented here are most consistent with a dissolution-reprecipitation mechanism for silica coating formation. Acidic solutions dissolved near-surface basalt, then precipitated in situ a portion of the dissolved Si as amorphous silica.</p
Phototriggering Nitric Oxide Synthase from Geobacillus stearothermophilus
Get PDFNitric oxide synthases (NOS) produce L-citrulline and nitric oxide (NO) in two turnovers from L-arginine via the bound intermediate, N-hydroxy-L-arginine. NO is an important biological signaling molecule, and NOS-like enzymes have been identified in all kingdoms of life. NOS enzymes utilize electrons from a reductase domain as well as a unique redox-active cofactor, tetrahydrobiopterin, in the activation of dioxygen. The NOS catalytic mechanism is only partially known, with proposed hihg-valent oxygenating intermediates similar to those of other monooxygenases. In the continued effort to understand the mechanism by which NOS catalytically produces NO, we have chosen to study NOS from the thermostable, nonpathogenic bacterium Geobacillus stearothermophilus (gsNOS).
In this work, covalently modified gsNOS with a ruthenium(II) diimine photosensitizer has been prepared to circumvent the need for an external reductase domain, while maintaining access to the substrate-binding channel. In this way, we hoped to produce the NOS ferrous state by rapid electron injection and to be able to access intermediates that form downstream. Chapter two describes the engineered gsNOS for selective cysteine labeling with [Ru(bpy)2(IA-phen)]2+ (IA-phen = 5-iodoacetamido-1,10-phenanthroline) to form the conjugate Ru(II)K115C-gsNOS. The labeled protein was characterized by mass spectrometry, UV-visible absorbance, and circular dichroism spectroscopy. Ru(II)K115C-gsNOS was crystallized and its structure solved to 2.6 Å resolution. Chapter three details phototriggered reduction by laser flash-quench methodology using the reversible, reductive quencher p-methoxy-N,N-dimethylanaline. Transient absorption studies have shown that rapid phototriggered heme reduction occurs on the order of 625 ns. Binding of substrates and/or cofactor is known to alter the heme reduction potential in NOS. However, these observed reduction rates are independent of substrate/cofactor, suggesting that the system is driving force optimized. Studies performed in the presence of oxygen were complicated by side-reactions with the ruthenium label and small molecule quencher. Excitingly, enzymatic turnover was achieved by steady-state LED illumination at 470 nm using the irreversible reductive quencher diethyldithiocarbamate, and is described in chapter four. NO produced from light-driven Ru(II)K115C-gsNOS catalysis was measured by the Griess Assay and L-citrulline production confirmed by liquid chromatography-mass spectrometry. In chapter five, we show how phototriggered heme reduction can be used to monitor CO binding and potential studies of gas diffusion pathways, and substrate/cofactor effects are discussed. In all, the development of this ruthenium-modified gsNOS system has enabled preliminary studies of reduction kinetics, diatomic ligand binding, and light-driven catalysis and may provide a useful platform for further investigation into the catalytic cycle of NOS.</p
Deep Tissue Fluorescence Imaging with Time-Reversed Light
Get PDFAdvances in optical techniques have enabled many breakthroughs in biology and medicine. However, light scattering by biological tissues remains a great obstacle, restricting the use of optical methods to thin ex vivo sections or superficial layers in vivo. In this thesis, we present two related methods that overcome the optical depth limit—digital time reversal of ultrasound encoded light (digital TRUE) and time reversal of variance-encoded light (TROVE). These two techniques share the same principle of using acousto-optic beacons for time reversal optical focusing within highly scattering media, like biological tissues. Ultrasound, unlike light, is not significantly scattered in soft biological tissues, allowing for ultrasound focusing. In addition, a fraction of the scattered optical wavefront that passes through the ultrasound focus gets frequency-shifted via the acousto-optic effect, essentially creating a virtual source of frequency-shifted light within the tissue. The scattered ultrasound-tagged wavefront can be selectively measured outside the tissue and time-reversed to converge at the location of the ultrasound focus, enabling optical focusing within deep tissues. In digital TRUE, we time reverse ultrasound-tagged light with an optoelectronic time reversal device (the digital optical phase conjugate mirror, DOPC). The use of the DOPC enables high optical gain, allowing for high intensity optical focusing and focal fluorescence imaging in thick tissues at a lateral resolution of 36 µm by 52 µm. The resolution of the TRUE approach is fundamentally limited to that of the wavelength of ultrasound. The ultrasound focus (~ tens of microns wide) usually contains hundreds to thousands of optical modes, such that the scattered wavefront measured is a linear combination of the contributions of all these optical modes. In TROVE, we make use of our ability to digitally record, analyze and manipulate the scattered wavefront to demix the contributions of these spatial modes using variance encoding. In essence, we encode each spatial mode inside the scattering sample with a unique variance, allowing us to computationally derive the time reversal wavefront that corresponds to a single optical mode. In doing so, we uncouple the system resolution from the size of the ultrasound focus, demonstrating optical focusing and imaging between highly diffusing samples at an unprecedented, speckle-scale lateral resolution of ~ 5 µm. Our methods open up the possibility of fully exploiting the prowess and versatility of biomedical optics in deep tissues
Mathematical Study of Complex Networks: Brain, Internet, and Power Grid
Get PDFThe dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.
Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.
Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.
Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.
Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.
Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.</p
Thin Metastructures with Engineered Thermal Expansion
Get PDFThe geometry and constituent materials of metastructures can be used to engineer the thermal expansion coefficient. In this thesis, we design, fabricate, and test thin thermally stable metastructures consisting of bi-metallic unit cells and show how the coefficient of thermal expansion (CTE) of these metastructures can be finely and coarsely tuned by varying the CTE of the constituent materials and the unit cell geometry. Planar and three-dimensional finite element method modeling is used to drive the design and inform experiments, and predict the response of these metastructures. We demonstrate computationally the significance of out-of-plane effects in the metastructure response. We develop an experimental setup using digital image correlation and an infrared camera to experimentally measure full displacement and temperature fields during testing and accurately measure the metastructures’ CTE. We experimentally demonstrate high aspect ratio metastructures of Ti/Al and Kovar/Al which exhibit near-zero and negative CTE, respectively. We demonstrate robust fabrication procedures for thermally stable samples with high aspect ratios in thin foil and thin film scales. We investigate the lattice structure and mechanical properties of thin films comprising a near-zero CTE metastructure. The mechanics developed in this work can be used to engineer metastructures of arbitrary CTE and can be extended to three dimensions
Algorithmic Challenges in Green Data Centers
Get PDFWith data centers being the supporting infrastructure for a wide range of IT services, their efficiency has become a big concern to operators, as well as to society, for both economic and environmental reasons. The goal of this thesis is to design energy-efficient algorithms that reduce energy cost while minimizing compromise to service. We focus on the algorithmic challenges at different levels of energy optimization across the data center stack. The algorithmic challenge at the device level is to improve the energy efficiency of a single computational device via techniques such as job scheduling and speed scaling. We analyze the common speed scaling algorithms in both the worst-case model and stochastic model to answer some fundamental issues in the design of speed scaling algorithms. The algorithmic challenge at the local data center level is to dynamically allocate resources (e.g., servers) and to dispatch the workload in a data center. We develop an online algorithm to make a data center more power-proportional by dynamically adapting the number of active servers. The algorithmic challenge at the global data center level is to dispatch the workload across multiple data centers, considering the geographical diversity of electricity price, availability of renewable energy, and network propagation delay. We propose algorithms to jointly optimize routing and provisioning in an online manner. Motivated by the above online decision problems, we move on to study a general class of online problem named "smoothed online convex optimization", which seeks to minimize the sum of a sequence of convex functions when "smooth" solutions are preferred. This model allows us to bridge different research communities and help us get a more fundamental understanding of general online decision problems
The Optoelectronic Swept-Frequency Laser and Its Applications in Ranging, Three-Dimensional Imaging, and Coherent Beam Combining of Chirped-Seed Amplifiers
Get PDFThis thesis explores the design, construction, and applications of the optoelectronic swept-frequency laser (SFL). The optoelectronic SFL is a feedback loop designed around a swept-frequency (chirped) semiconductor laser (SCL) to control its instantaneous optical frequency, such that the chirp characteristics are determined solely by a reference electronic oscillator. The resultant system generates precisely controlled optical frequency sweeps. In particular, we focus on linear chirps because of their numerous applications. We demonstrate optoelectronic SFLs based on vertical-cavity surface-emitting lasers (VCSELs) and distributed-feedback lasers (DFBs) at wavelengths of 1550 nm and 1060 nm. We develop an iterative bias current predistortion procedure that enables SFL operation at very high chirp rates, up to 10^16 Hz/sec. We describe commercialization efforts and implementation of the predistortion algorithm in a stand-alone embedded environment, undertaken as part of our collaboration with Telaris, Inc. We demonstrate frequency-modulated continuous-wave (FMCW) ranging and three-dimensional (3-D) imaging using a 1550 nm optoelectronic SFL.
We develop the technique of multiple source FMCW (MS-FMCW) reflectometry, in which the frequency sweeps of multiple SFLs are "stitched" together in order to increase the optical bandwidth, and hence improve the axial resolution, of an FMCW ranging measurement. We demonstrate computer-aided stitching of DFB and VCSEL sweeps at 1550 nm. We also develop and demonstrate hardware stitching, which enables MS-FMCW ranging without additional signal processing. The culmination of this work is the hardware stitching of four VCSELs at 1550 nm for a total optical bandwidth of 2 THz, and a free-space axial resolution of 75 microns.
We describe our work on the tomographic imaging camera (TomICam), a 3-D imaging system based on FMCW ranging that features non-mechanical acquisition of transverse pixels. Our approach uses a combination of electronically tuned optical sources and low-cost full-field detector arrays, completely eliminating the need for moving parts traditionally employed in 3-D imaging. We describe the basic TomICam principle, and demonstrate single-pixel TomICam ranging in a proof-of-concept experiment. We also discuss the application of compressive sensing (CS) to the TomICam platform, and perform a series of numerical simulations. These simulations show that tenfold compression is feasible in CS TomICam, which effectively improves the volume acquisition speed by a factor ten.
We develop chirped-wave phase-locking techniques, and apply them to coherent beam combining (CBC) of chirped-seed amplifiers (CSAs) in a master oscillator power amplifier configuration. The precise chirp linearity of the optoelectronic SFL enables non-mechanical compensation of optical delays using acousto-optic frequency shifters, and its high chirp rate simultaneously increases the stimulated Brillouin scattering (SBS) threshold of the active fiber. We characterize a 1550 nm chirped-seed amplifier coherent-combining system. We use a chirp rate of 5*10^14 Hz/sec to increase the amplifier SBS threshold threefold, when compared to a single-frequency seed. We demonstrate efficient phase-locking and electronic beam steering of two 3 W erbium-doped fiber amplifier channels, achieving temporal phase noise levels corresponding to interferometric fringe visibilities exceeding 98%.</p
Coupled Effects of Mechanics, Geometry, and Chemistry on Bio-Membrane Behavior
Get PDFLipid bilayer membranes are models for cell membranes--the structure that helps regulate cell function. Cell membranes are heterogeneous, and the coupling between composition and shape gives rise to complex behaviors that are important to regulation. This thesis seeks to systematically build and analyze complete models to understand the behavior of multi-component membranes.
We propose a model and use it to derive the equilibrium and stability conditions for a general class of closed multi-component biological membranes. Our analysis shows that the critical modes of these membranes have high frequencies, unlike single-component vesicles, and their stability depends on system size, unlike in systems undergoing spinodal decomposition in flat space. An important implication is that small perturbations may nucleate localized but very large deformations. We compare these results with experimental observations.
We also study open membranes to gain insight into long tubular membranes that arise for example in nerve cells. We derive a complete system of equations for open membranes by using the principle of virtual work. Our linear stability analysis predicts that the tubular membranes tend to have coiling shapes if the tension is small, cylindrical shapes if the tension is moderate, and beading shapes if the tension is large. This is consistent with experimental observations reported in the literature in nerve fibers. Further, we provide numerical solutions to the fully nonlinear equilibrium equations in some problems, and show that the observed mode shapes are consistent with those suggested by linear stability. Our work also proves that beadings of nerve fibers can appear purely as a mechanical response of the membrane. </p
Identification of Fucose-α(1-2)-Galactose Binding Proteins in the Mammalian Brain
Get PDFFucose-α(1-2)-galactose (Fucα(1-2)Gal) carbohydrates have been implicated in cognitive functions. However, the underlying molecular mechanisms that govern these processes are not well understood. While significant progress has been made toward identifying glycoconjugates bearing this carbohydrate epitope, a major challenge remains the discovery of interactions mediated by these sugars. Here, we employ the use of multivalent glycopolymers to enable the proteomic identification of weak affinity, low abundant Fucα(1-2)Gal-binding proteins (i.e. lectins) from the brain. End-biotinylated glycopolymers containing photoactivatable crosslinkers were used to capture and enrich potential Fucα(1-2)Gal-specific lectins from rat brain lysates. Candidate lectins were tested for their ability to bind Fucα(1-2)Gal, and the functional significance of the interaction was investigated for one such candidate, SV2a, using a knock-out mouse system. Our results suggest an important role for this glycan-lectin interaction in facilitating synaptic changes necessary for neuronal communication. This study highlights the use of glycopolymer mimetics to discover novel lectins and identify functional interactions between fucosyl carbohydrates and lectins in the brain
Synthesis and Biological Activity of Anticoagulant Heparan Sulfate Glycopolymers
Get PDFHeparin has been used as an anticoagulant drug for more than 70 years. The global distribution of contaminated heparin in 2007, which resulted in adverse clinical effects and over 100 deaths, emphasizes the necessity for safer alternatives to animal-sourced heparin. The structural complexity and heterogeneity of animal-sourced heparin not only impedes safe access to these biologically active molecules, but also hinders investigations on the significance of structural constituents at a molecular level. Efficient methods for preparing new synthetic heparins with targeted biological activity are necessary not only to ensure clinical safety, but to optimize derivative design to minimize potential side effects. Low molecular weight heparins have become a reliable alternative to heparin, due to their predictable dosages, long half-lives, and reduced side effects. However, heparin oligosaccharide synthesis is a challenging endeavor due to the necessity for complex protecting group manipulation and stereoselective glycosidic linkage chemistry, which often result in lengthy synthetic routes and low yields. Recently, chemoenzymatic syntheses have produced targeted ultralow molecular weight heparins with high-efficiency, but continue to be restricted by the substrate specificities of enzymes.
To address the need for access to homogeneous, complex glycosaminoglycan structures, we have synthesized novel heparan sulfate glycopolymers with well-defined carbohydrate structures and tunable chain length through ring-opening metathesis polymerization chemistry. These polymers recapitulate the key features of anticoagulant heparan sulfate by displaying the sulfation pattern responsible for heparin’s anticoagulant activity. The use of polymerization chemistry greatly simplifies the synthesis of complex glycosaminoglycan structures, providing a facile method to generate homogeneous macromolecules with tunable biological and chemical properties. Through the use of in vitro chromogenic substrate assays and ex vivo clotting assays, we found that the HS glycopolymers exhibited anticoagulant activity in a sulfation pattern and length-dependent manner. Compared to heparin standards, our short polymers did not display any activity. However, our longer polymers were able to incorporate in vitro and ex vivo characteristics of both low-molecular-weight heparin derivatives and heparin, displaying hybrid anticoagulant properties. These studies emphasize the significance of sulfation pattern specificity in specific carbohydrate-protein interactions, and demonstrate the effectiveness of multivalent molecules in recapitulating the activity of natural polysaccharides.</p