5 resultados para preliminary discovery
em CaltechTHESIS
Resumo:
This thesis presents recent research into analytic topics in the classical theory of General Relativity. It is a thesis in two parts. The first part features investigations into the spectrum of perturbed, rotating black holes. These include the study of near horizon perturbations, leading to a new generic frequency mode for black hole ringdown; an treatment of high frequency waves using WKB methods for Kerr black holes; and the discovery of a bifurcation of the quasinormal mode spectrum of rapidly rotating black holes. These results represent new discoveries in the field of black hole perturbation theory, and rely on additional approximations to the linearized field equations around the background black hole. The second part of this thesis presents a recently developed method for the visualization of curved spacetimes, using field lines called the tendex and vortex lines of the spacetime. The works presented here both introduce these visualization techniques, and explore them in simple situations. These include the visualization of asymptotic gravitational radiation; weak gravity situations with and without radiation; stationary black hole spacetimes; and some preliminary study into numerically simulated black hole mergers. The second part of thesis culminates in the investigation of perturbed black holes using these field line methods, which have uncovered new insights into the dynamics of curved spacetime around black holes.
Resumo:
The Daya Bay Reactor Antineutrino Experiment observed the disappearance of reactor $\bar{\nu}_e$ from six $2.9~GW_{th}$ reactor cores in Daya Bay, China. The Experiment consists of six functionally identical $\bar{\nu}_e$ detectors, which detect $\bar{\nu}_e$ by inverse beta decay using a total of about 120 metric tons of Gd-loaded liquid scintillator as the target volume. These $\bar{\nu}_e$ detectors were installed in three underground experimental halls, two near halls and one far hall, under the mountains near Daya Bay, with overburdens of 250 m.w.e, 265 m.w.e and 860 m.w.e. and flux-weighted baselines of 470 m, 576 m and 1648 m. A total of 90179 $\bar{\nu}_e$ candidates were observed in the six detectors over a period of 55 days, 57549 at the Daya Bay near site, 22169 at the Ling Ao near site and 10461 at the far site. By performing a rate-only analysis, the value of $sin^2 2\theta_{13}$ was determined to be $0.092 \pm 0.017$.
Resumo:
Past workers in this group as well as in others have made considerable progress in the understanding and development of the ring-opening metathesis polymerization (ROMP) technique. Through these efforts, ROMP chemistry has become something of an organometallic success story. Extensive work was devoted to trying to identify the catalytically active species in classical reaction mixtures of early metal halides and alkyl aluminum compounds. Through this work, a mechanism involving the interconversion of metal carbenes and metallacyclobutanes was proposed. This preliminary work finally led to the isolation and characterization of stable metal carbene and metallacyclobutane complexes. As anticipated, these well-characterized complexes were shown to be active catalysts. In a select number of cases, these catalysts have been shown to catalyze the living polymerization of strained rings such as norbornene. The synthetic control offered by these living systems places them in a unique category of metal catalyzed reactions. To take full advantage of these new catalysts, two approaches should be explored. The first takes advantage of the unusual fact that all of the unsaturation present in the monomer is conserved in the polymer product. This makes ROMP techniques ideal for the synthesis of highly unsaturated, and fully conjugated polymers, which find uses in a variety of applications. This area is currently under intense investigation. The second aspect, which should lend itself to fruitful investigations, is expanding the utility of these catalysts through the living polymerization of monomers containing interesting functional groups. Polymer properties can be dramatically altered by the incorporation of functional groups. It is this latter aspect which will be addressed in this work.
After a general introduction to both the ring-opening metathesis reaction (Chapter 1) and the polymerization of fuctionalized monomers by transition metal catalysts (Chapter 2), the limits of the existing living ROMP catalysts with functionalized monomers are examined in Chapter 3. Because of the stringent limitations of these early metal catalysts, efforts were focused on catalysts based on ruthenium complexes. Although not living, and displaying unusually long induction periods, these catalysts show high promise for future investigations directed at the development of catalysts for the living polymerization of functionalized monomers. In an attempt to develop useful catalysts based on these ruthenium complexes, efforts to increase their initiation rates are presented in Chapter 4. This work eventually led to the discovery that these catalysts are highly active in aqueous solution, providing the opportunity to develop aqueous emulsion ROMP systems. Recycling the aqueous catalysts led to the discovery that the ruthenium complexes become more activated with use. Investigations of these recycled solutions uncovered new ruthenium-olefin complexes, which are implicated in the activation process. Although our original goal of developing living ROMP catalysts for the polymerization of fuctionalized monomers is yet to be realized, it is hoped that this work provides a foundation from which future investigations can be launched.
In the last chapter, the ionophoric properties of the poly(7-oxanobornene) materials is briefly discussed. Their limited use as acyclic host polymers led to investigations into the fabrication of ion-permeable membranes fashioned from these materials.
Resumo:
Electronic structures and dynamics are the key to linking the material composition and structure to functionality and performance.
An essential issue in developing semiconductor devices for photovoltaics is to design materials with optimal band gaps and relative positioning of band levels. Approximate DFT methods have been justified to predict band gaps from KS/GKS eigenvalues, but the accuracy is decisively dependent on the choice of XC functionals. We show here for CuInSe2 and CuGaSe2, the parent compounds of the promising CIGS solar cells, conventional LDA and GGA obtain gaps of 0.0-0.01 and 0.02-0.24 eV (versus experimental values of 1.04 and 1.67 eV), while the historically first global hybrid functional, B3PW91, is surprisingly the best, with band gaps of 1.07 and 1.58 eV. Furthermore, we show that for 27 related binary and ternary semiconductors, B3PW91 predicts gaps with a MAD of only 0.09 eV, which is substantially better than all modern hybrid functionals, including B3LYP (MAD of 0.19 eV) and screened hybrid functional HSE06 (MAD of 0.18 eV).
The laboratory performance of CIGS solar cells (> 20% efficiency) makes them promising candidate photovoltaic devices. However, there remains little understanding of how defects at the CIGS/CdS interface affect the band offsets and interfacial energies, and hence the performance of manufactured devices. To determine these relationships, we use the B3PW91 hybrid functional of DFT with the AEP method that we validate to provide very accurate descriptions of both band gaps and band offsets. This confirms the weak dependence of band offsets on surface orientation observed experimentally. We predict that the CBO of perfect CuInSe2/CdS interface is large, 0.79 eV, which would dramatically degrade performance. Moreover we show that band gap widening induced by Ga adjusts only the VBO, and we find that Cd impurities do not significantly affect the CBO. Thus we show that Cu vacancies at the interface play the key role in enabling the tunability of CBO. We predict that Na further improves the CBO through electrostatically elevating the valence levels to decrease the CBO, explaining the observed essential role of Na for high performance. Moreover we find that K leads to a dramatic decrease in the CBO to 0.05 eV, much better than Na. We suggest that the efficiency of CIGS devices might be improved substantially by tuning the ratio of Na to K, with the improved phase stability of Na balancing phase instability from K. All these defects reduce interfacial stability slightly, but not significantly.
A number of exotic structures have been formed through high pressure chemistry, but applications have been hindered by difficulties in recovering the high pressure phase to ambient conditions (i.e., one atmosphere and room temperature). Here we use dispersion-corrected DFT (PBE-ulg flavor) to predict that above 60 GPa the most stable form of N2O (the laughing gas in its molecular form) is a 1D polymer with an all-nitrogen backbone analogous to cis-polyacetylene in which alternate N are bonded (ionic covalent) to O. The analogous trans-polymer is only 0.03-0.10 eV/molecular unit less stable. Upon relaxation to ambient conditions both polymers relax below 14 GPa to the same stable non-planar trans-polymer, accompanied by possible electronic structure transitions. The predicted phonon spectrum and dissociation kinetics validate the stability of this trans-poly-NNO at ambient conditions, which has potential applications as a new type of conducting polymer with all-nitrogen chains and as a high-energy oxidizer for rocket propulsion. This work illustrates in silico materials discovery particularly in the realm of extreme conditions.
Modeling non-adiabatic electron dynamics has been a long-standing challenge for computational chemistry and materials science, and the eFF method presents a cost-efficient alternative. However, due to the deficiency of FSG representation, eFF is limited to low-Z elements with electrons of predominant s-character. To overcome this, we introduce a formal set of ECP extensions that enable accurate description of p-block elements. The extensions consist of a model representing the core electrons with the nucleus as a single pseudo particle represented by FSG, interacting with valence electrons through ECPs. We demonstrate and validate the ECP extensions for complex bonding structures, geometries, and energetics of systems with p-block character (C, O, Al, Si) and apply them to study materials under extreme mechanical loading conditions.
Despite its success, the eFF framework has some limitations, originated from both the design of Pauli potentials and the FSG representation. To overcome these, we develop a new framework of two-level hierarchy that is a more rigorous and accurate successor to the eFF method. The fundamental level, GHA-QM, is based on a new set of Pauli potentials that renders exact QM level of accuracy for any FSG represented electron systems. To achieve this, we start with using exactly derived energy expressions for the same spin electron pair, and fitting a simple functional form, inspired by DFT, against open singlet electron pair curves (H2 systems). Symmetric and asymmetric scaling factors are then introduced at this level to recover the QM total energies of multiple electron pair systems from the sum of local interactions. To complement the imperfect FSG representation, the AMPERE extension is implemented, and aims at embedding the interactions associated with both the cusp condition and explicit nodal structures. The whole GHA-QM+AMPERE framework is tested on H element, and the preliminary results are promising.
Resumo:
The application of principles from evolutionary biology has long been used to gain new insights into the progression and clinical control of both infectious diseases and neoplasms. This iterative evolutionary process consists of expansion, diversification and selection within an adaptive landscape - species are subject to random genetic or epigenetic alterations that result in variations; genetic information is inherited through asexual reproduction and strong selective pressures such as therapeutic intervention can lead to the adaptation and expansion of resistant variants. These principles lie at the center of modern evolutionary synthesis and constitute the primary reasons for the development of resistance and therapeutic failure, but also provide a framework that allows for more effective control.
A model system for studying the evolution of resistance and control of therapeutic failure is the treatment of chronic HIV-1 infection by broadly neutralizing antibody (bNAb) therapy. A relatively recent discovery is that a minority of HIV-infected individuals can produce broadly neutralizing antibodies, that is, antibodies that inhibit infection by many strains of HIV. Passive transfer of human antibodies for the prevention and treatment of HIV-1 infection is increasingly being considered as an alternative to a conventional vaccine. However, recent evolution studies have uncovered that antibody treatment can exert selective pressure on virus that results in the rapid evolution of resistance. In certain cases, complete resistance to an antibody is conferred with a single amino acid substitution on the viral envelope of HIV.
The challenges in uncovering resistance mechanisms and designing effective combination strategies to control evolutionary processes and prevent therapeutic failure apply more broadly. We are motivated by two questions: Can we predict the evolution to resistance by characterizing genetic alterations that contribute to modified phenotypic fitness? Given an evolutionary landscape and a set of candidate therapies, can we computationally synthesize treatment strategies that control evolution to resistance?
To address the first question, we propose a mathematical framework to reason about evolutionary dynamics of HIV from computationally derived Gibbs energy fitness landscapes -- expanding the theoretical concept of an evolutionary landscape originally conceived by Sewall Wright to a computable, quantifiable, multidimensional, structurally defined fitness surface upon which to study complex HIV evolutionary outcomes.
To design combination treatment strategies that control evolution to resistance, we propose a methodology that solves for optimal combinations and concentrations of candidate therapies, and allows for the ability to quantifiably explore tradeoffs in treatment design, such as limiting the number of candidate therapies in the combination, dosage constraints and robustness to error. Our algorithm is based on the application of recent results in optimal control to an HIV evolutionary dynamics model and is constructed from experimentally derived antibody resistant phenotypes and their single antibody pharmacodynamics. This method represents a first step towards integrating principled engineering techniques with an experimentally based mathematical model in the rational design of combination treatment strategies and offers predictive understanding of the effects of combination therapies of evolutionary dynamics and resistance of HIV. Preliminary in vitro studies suggest that the combination antibody therapies predicted by our algorithm can neutralize heterogeneous viral populations despite containing resistant mutations.