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At least 289 records · Page 16

Polynuclear Aromatic Hydrocarbons with Curved Surfaces: Buckyballs

The discovery of a new allotropic form of elemental carbon – the fullerenes – and subsequently other novel forms of elemental carbon with pyramidalized surfaces, most notably single-walled and multi-walled carbon nanotubes, introduced a novel structural motif to the polycyclic aromatic hydrocarbons (PAHs) with nonplanar surfaces. Our research program supported by BES DOE grant DE-FG02-04ER15514 has dealt with the synthesis, structural studies, and chemistry of the novel curved-surface PAHs with carbon frameworks structurally related to fullerenes. They are referred to as “buckybowls”. We prepared several new buckybowls and, even more importantly, developed the efficient, gram-scale synthetic methodologies for the preparation of small buckybowls, most notably corannulene (C20H10) and its derivatives. In addition, the employment of the corannulene-based synthons previously developed in our laboratory led to a number of highly nonplanar molecular architectures with two or more corannulene subunits with a potential for the applications as novel materials in separation sciences, nanoelectronics, photovoltaics and catalysis. In collaboration with Professor Angelici (Iowa State) we prepared and characterized several transition metal complexes of corannulene, providing the first structural characterization of η6 metal complexes of buckybowls by a single crystal X-ray diffraction. In addition to the definitive structural characterization of the complexes we demonstrated that the (η6-C6Me6)Ru2+ unit in some relatively stable complexes activate the corannulene ligand to react with proper nucleophiles suggesting that such complexex may be used in catalysis. (Section C). We have explored the efficiency of the dispersion-based interactions of curved-surface conjugated carbon networks by high-level computational models. We showed that the curvature of such networks does not reduce the van der Waals attractions as compared to the planar systems of similar size. We than concentrated on the design, synthesis and testing of the previously unknown molecular receptors with corannulene pincers which are capable of forming the strong ball-and-socket inclusion complexes with fullerenes in solution and in the solid state. Buckycatcher I (a molecular receptor with two corannulene pincers preorganized on a tetrabensocyclooctatetraene tether) inclusion complexes with fullerenes provided the first experimental evidence for the importance of concave-convex π – π interactions in the supramolecular chemistry of fullerene carbon cages with buckybowls. C60@Buckycatcher I has become the prototypical supramolecular system formed by the relatively weak (on the atom-to-atom bases) and has been extensively used by the computational community to test the quality of the theoretical models. In addition, Buckycatcher I shows an exceptional ability to adopt other guest molecules and several its inclusion complexes and/or solvates have been structurally characterized. These unusual structures show the potential of the buckycatchers to be tested as novel organic materials. “Intelligent design” of molecular receptors with corannulene receptors using computational approach allowing for a priori prediction of their binding potentials led to the preparation of other buckycatchers. Both bi- and tridentate corannulene pincers were tested and two of the bidentate receptors (Buckycatchers II and III) exhibited the outstanding affinity toward fullerenes, significantly exciding Buckycatcher I performance. Careful tailoring of the tethers resulted in the optimization of binding energies of the receptors with guest carbon cages and in the reduction of the entropy/solvation penalties. Practical preparation of dicorannulenopentacene opens a new avenue for the synthesis of a pool of bis-corannulene receptors possessing polar groups on their dibenzobarrelene tether. The polar “anchors” can be used to attach these efficient fullerene receptors to solid supports in order to modify their surfaces with the potential applications in separation sciences, catalysis and photovoltaic materials. additionally, the presence of such groups will improve the solubility of the receptors in polar solvents, expanding the scope of their supramolecular chemistry in solutions. Rigorous studies of thermodynamics of host-guest association of molecular clips and tweezers in organic solvents with C60/C70 inclusion complexes with Buckycatcher I as a model system have provided a full set of thermodynamical data including ΔG, ΔH, and –TΔS, for the formation of the inclusion complexes over a range of temperatures and in several solvents. Both 1H NMR and Isothermal Calorimetry (ITC) titrations provide virtually identical association constants, confirming the reliability of the results. WE have shown that thermodynamics of the host-guest complex formation is more complicated than anticipated and proposed by the existing computational models. These data are of premium importance for the testing of the computational solvation models and for a deeper understanding of the supramolecular interactions in organic solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Empirical Radii and Masses of Planets and Their Host Stars with Gaia Parallaxes

We present empirical measurements of the radii of 116 stars that host transiting planets. These radii are determined using only direct observables—the bolometric flux at Earth, the effective temperature, and the parallax provided by the Gaia first data release—and thus are virtually model independent, with extinction being the only free parameter. We also determine each star’s mass using our newly determined radius and the stellar density, a virtually model independent quantity itself from previously published transit analyses. These stellar radii and masses are in turn used to redetermine the transiting-planet radii and masses, again using only direct observables. The median uncertainties on the stellar radii and masses are 8% and 30%, respectively, and the resulting uncertainties on the planet radii and masses are 9% and 22%, respectively. These accuracies are generally larger than previously published model-dependent precisions of 5% and 6% on the planet radii and masses, respectively, but the newly determined values are purely empirical. We additionally report radii for 242 stars hosting radial-velocity (non-transiting) planets, with a median achieved accuracy of ≈2%. Using our empirical stellar masses we verify that the majority of putative “retired A stars” in the sample are indeed more massive than ∼1.2 M{sub ⊙}. Most importantly, the bolometric fluxes and angular radii reported here for a total of 498 planet host stars—with median accuracies of 1.7% and 1.8%, respectively—serve as a fundamental data set to permit the re-determination of transiting-planet radii and masses with the Gaia second data release to ≈3% and ≈5% accuracy, better than currently published precisions, and determined in an entirely empirical fashion.

79 ASTRONOMY AND ASTROPHYSICS↗

Microbial degradation of parathion

An organism capable of utilizing parathion as the sole carbon and energy source was isolated by enrichment culture techniques. The bacterium was characterized and tentatively classified as Pseudomonas aeruginosa. A pH of 7.0 - 7.5 and temperature of 30 C were found to be optimum for the consumption of parathion. Virtually no oxygen utilization was observed with resting cell suspensions when nonsolubilized parathion was employed. The use of ethanol as solvent for parathion in resting cell studies or preincubation of cells in ethanol obviated this problem and rapid parathion oxidation was demonstrable. Approximately 80% of the parathion consumed by resting cells was present terminally as carbon dioxide. Permeability of the cell to parathion or its metabolites was contingent upon the use of ethanol as either solvent or denaturant. Metabolites were tentatively identified by thin layer chromatography.

Gibson, W. L.↗

Ion heating and containment in the NASA Lewis bumpy torus plasma

Experimental observations have been made during steady state operation of a torus experiment at input powers up to 150 kilowatts in deuterium and helium gas. The steady state ion heating method utilizes a modified Penning discharge operated in a bumpy torus confinement geometry. The bumpy torus plasma is acted upon by a combination of strong electric and magnetic fields. In a deuterium plasma, electron temperatures from 14 to 140 electron volts and ion kinetic temperatures from 160 to 1785 electron volts were observed. At least two distinct operating regimes exist, each of which is associated with a characteristic range of background gas pressure and electron temperature. Experimental data show that the average ion residence time in the plasma is virtually independent of magnetic field strength.

Roth, J. R.↗

Characteristics of the NASA Lewis Bumpy Torus plasma generated with positive applied potentials

Experimental observations have been made during steady-state operation of the NASA Lewis Bumpy Torus experiment at input powers up to 150 kW in deuterium and helium gas, and with positive potentials applied to the midplane electrodes. This steady-state ion heating method utilizes a modified Penning discharge operated in a bumpy torus confinement geometry such that the plasma is acted upon by a combination of strong electric and magnetic fields. Experimental investigation of a deuterium plasma revealed electron temperatures from 14 to 140 eV and ion kinetic temperatures from 160 to 1785 eV. At least two distinct modes of operation exist, each of which is associated with a characteristic range of background pressure and electron temperature. Experimental data show that the average ion residence time in the plasma is virtually independent of the magnetic field strength.

Roth, J. R.↗

Low noise buffer amplifiers and buffered phase comparators for precise time and frequency measurement and distribution

Extremely low noise, high performance, wideband buffer amplifiers and buffered phase comparators were developed. These buffer amplifiers are designed to distribute reference frequencies from 30 KHz to 45 MHz from a hydrogen maser without degrading the hydrogen maser's performance. The buffered phase comparators are designed to intercompare the phase of state of the art hydrogen masers without adding any significant measurement system noise. These devices have a 27 femtosecond phase stability floor and are stable to better than one picosecond for long periods of time. Their temperature coefficient is less than one picosecond per degree C, and they have shown virtually no voltage coefficients.

Eichinger, R. A.↗

On requirements for a satellite mission to measure tropical rainfall

Tropical rainfall data are crucial in determining the role of tropical latent heating in driving the circulation of the global atmosphere. Also, the data are particularly important for testing the realism of climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the effects of El Nino on climate could be addressed with a reliable, extended time series of tropical rainfall observations. A passive microwave sensor is planned to provide information on the integrated column precipitation content, its areal distribution, and its intensity. An active microwave sensor (radar) will define the layer depth of the precipitation and provide information about the intensity of rain reaching the surface, the key to determining the latent heat input to the atmosphere. A visible/infrared sensor will provide very high resolution information on cloud coverage, type, and top temperatures and also serve as the link between these data and the long and virtually continuous coverage by the geosynchronous meteorological satellites. The unique combination of sensor wavelengths, coverages, and resolving capabilities together with the low-altitude, non-Sun synchronous orbit provide a sampling capability that should yield monthly precipitation amounts to a reasonable accuracy over a 500- by 500-km grid.

Thiele, Otto W.↗

Extensional and compressional instabilities in icy satellite lithospheres

The plausibility of invoking a lithospheric instability mechanism to account for the grooved terrains on Ganymede, Encedalus, and Miranda is presently evaluated in light of the combination of a simple mechanical model of planetary lithospheres and asthenospheres with recent experimental data for the brittle and ductile deformation of ice. For Ganymede, high surface gravity and warm temperatures render the achievement of an instability sufficiently great for the observed topographic relief virtually impossible; an instability of sufficient strength, however, may be able to develop on such smaller, colder bodies as Encedalus and Miranda.

Herrick, David L.↗

GeoNEX-ML: A Machine Learning System for Geostationary Satellite Imagery

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), Himawari-8/9 (JAXA), and GK-2A (Korea), we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary satellites↗

GeoNEX-ML: A Machine Learning System for Earth Observations

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary↗

Process Modeling of Woven Textiles

Woven polymer matrix composites offer numerous advantages over traditional unidirectional laminates. Processing conditions affect residual stress that builds up during manufacturing. This work proposes the analysis of three curing parameters on the local residual stress distribution of a plain weave textile architecture, including chemical shrinkage, the temperature cool down, and the evolution of matrix properties as a function of curing. Virtual curing is applied to the inter-tow matrix material of the plain weave Repeating Unit Cell (RUC) modeled in TexGen. Curing is implemented through user-written subroutines within the commercial software suite Abaqus. Results from process modeling are compared with a linear-elastic thermal cool down in Abaqus. A boundary conditions study is also conducted to compare the residual stress build up predicted by Flat(FBCs) and Periodic Boundary Conditions (PBCs). Preliminary results indicate that a thermal cool down over-estimates the end-of-cure stresses in the matrix. Process modeling is conducted with and without chemical shrinkage, then compared with a thermal cool down. Results show that 11.32% of the final stress state is due to chemical shrinkage. Material property evolution during curing also has a non-negligible effect on the end stress.

woven composites↗

Atmospheric winds with deep optical flow

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Atmospheric winds↗

Recent advances in plasma control and physics research in the Large Helical Device

The Large Helical Device (LHD), the largest superconducting helical system in the world, is equipped with advanced heating and diagnostic tools, facilitating plasma control and physics research. Data assimilation was employed for electron temperature control using a real-time Thomson scattering system and real time prediction code. A virtual LHD environment enabled visualization of escaping high-energy tritium ions and demonstrated that these ions impact the rear side of the divertor plate. Pioneering results crucial to plasma control have also been achieved. Real-time wall conditioning using Lithium granule dropping improved bulk ion energy and particle transport while simultaneously enhancing the heavy impurity transport. Progress has also been made in the investigation of turbulence-driven transport. At the confinement bifurcation, ion-scale turbulence decreased, while electron-scale turbulence increased. A change in the anisotropy of turbulent eddies was also observed at the confinement bifurcation. Coexistence of local and non-local turbulence was identified in electron-scale turbulence. Non-local turbulence exhibited the rapid spatial propagation of perturbations throughout the plasma, while local turbulence followed the temperature gradient. A transition between drift-wave turbulence and magnetohydrodynamics (MHD) turbulence was observed with the turbulence minimized at the transition condition. Machine learning analysis was employed to evaluate the temperate and density conditions of this turbulence transition. Then, real-time control of fueling and heating was applied to maintain the turbulence transition condition, improving the energy confinement enhancement factor by 20%. In addition, evidence was obtained for collisionless ion heating by energetic-ion-driven geodesic acoustic modes and MHD bursts. These achievements represent unique contributions to the development of fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Coronal temperatures of unusually active K-dwarf binary systems

We report the results of a ROSAT pointed study of 4 BY Dra systems. Good quality pulse-height spectra are available from all four systems. Except for a required interstellar absorption component in HD 319139, the four systems have remarkably similar x-ray spectra; the two systems BD +22deg.669 and BD +23deg.635 look virtually identical in x rays. Analysis of the 4 x-ray spectra reveals that, in all cases, a single-temperature hot plasma (RS or Mewe) spectra is inadequate to fit the data, and two temperatures are required. We present examples of fitted pulse-height spectra and chi squared contours in kT(sub 1)-kT(sub 2) space.

Stern, Robert A.↗

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Srivastava, Ashok↗

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗

Tuning the ferromagnetic-antiferromagnetic interfaces of granular Co-CoO exchange bias systems by annealing

The low-temperature magnetic behavior of granular Co-CoO exchange bias systems, prepared by oxygen ion implantation in Co thin films and subsequent annealing, is addressed. The thermal activation effects lead to an O migration which results in virtually pure Co areas embedded in a structurally relaxed and nearly stoichiometric CoO phase. This yields decreased training and exchange bias shifts, while the blocking temperature significantly increases, coming close to the Néel temperature of bulk CoO for samples implanted to a fluence above 1 × 10{sup 17} ions/cm{sup 2} (15% O). The dependence of the exchange bias shift on the pristine O-implanted content is analogous to that of the antiferromagnetic thickness in most ferromagnetic/antiferromagnetic systems (i.e., an increase in the exchange bias shift up to a maximum followed by a decrease until a steady state is reached), suggesting that, after annealing, the enriched Co areas might be rather similar in size for samples implanted above 1 × 10{sup 17} ions/cm{sup 2}, whereas the corresponding CoO counterparts become enlarged with pristine O content (i.e., effect of the antiferromagnet size). This study demonstrates that the magnetic properties of granular Co-CoO systems can be tailored by controllably modifying the local microstructure through annealing treatments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗