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At least 703 records · Page 39

Timing of Crystallisation of the Lunar Magma Ocean Constrained by the Oldest Zircon

The presently favoured concept for the early evolution of the Moon involves consolidation of debris from a giant impact of a Mars sized body with Earth forming a primitive Moon with a thick global layer of melt referred to as the Lunar Magma Ocean1 . It is widely accepted that many significant features observed on the Moon today are the result of crystallisation of this magma ocean. However, controversy exists over the precise timing and duration of the crystallisation process. Resolution of this problem depends on the establishment of precise and robust key crystallisation time points. We report a 4417 6 Myr old zircon in lunar breccia sample 72215,195, which provides a precisely determined younger limit for the solidification of the Lunar Magma Ocean. A model based on these data, together with the age of the Moon forming giant impact, defines an exponential time frame for crystallisation and suggests formation of anorthositic crust after about 80-85% of the magma ocean was solidified. In combination with other zircon ages the 4417 +/- 6 Myr age also suggests that the very small (less than a few per cent) residual portion of the magma ocean continued to solidify during the following 300-500 m.y.

Nemchin, A.↗

Ethane Ices in the Outer Solar System: Spectroscopy and Chemistry

We report recent experiments on ethane ices made at temperatures applicable to the outer Solar System. New near- and mid-infrared data for crystalline and amorphous ethane, including new spectra for a seldom-studied solid phase that exists at 35-55 K, are presented along with radiation-chemical experiments showing the formation of more-complex hydrocarbons,

Hudson, R. L.↗

Ethane Ices in the Outer Solar System: Spectroscopy and Chemistry

We report recent experiments on ethane ices made at temperatures applicable to the outer Solar System. New near- and mid-infrared data for crystalline and amorphous ethane, including new spectra for a seldom-studied solid phase that exists at 35-55 K, are presented along with radiation-chemical experiments showing the formation of more-complex hydrocarbons

Hudson, R. L.↗

Carbon and Sulfur Isotopic Composition of Yellowknife Bay Sediments: Measurements by the Sample Analysis at Mars (SAM) Quadrupole Mass Spectrometer

Since landing at Gale Crater in Au-gust 2012, the Sample Analysis at Mars (SAM) instru-ment suite on the Mars Science Laboratory (MSL) “Curiosity” rover has analyzed solid samples from the martian regolith in three locations, beginning with a scoop of aeolian deposits from the Rocknest (RN) sand shadow. Curiosity subsequently traveled to Yellowknife Bay, where SAM analyzed samples from two separate holes drilled into the Sheepbed Mudstone, designated John Klein (JK) and Cumberland (CB). Evolved gas analysis (EGA) of all samples revealed the presence of H2O as well as O-, C- and S-bearing phas-es, in most cases at abundances below the detection limit of the CheMin instrument. In the absence of definitive mineralogical identification by CheMin, SAM EGA data can help provide clues to the mineralogy of volatile-bearing phases through examination of tem-peratures at which gases are evolved from solid sam-ples. In addition, the isotopic composition of these gas-es may be used to identify possible formation scenarios and relationships between phases. Here we report C and S isotope ratios for CO2 and SO2 evolved from the JK and CB mudstone samples as measured with SAM’s quadrupole mass spectrometer (QMS) and draw com-parisons to RN.

Franz, H. B.↗

TESS Data Release Notes: Sector 24, DR35

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel fi les, light curve fi les, collateral pixel fi les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml fi les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD). The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2019).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

TESS↗

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗

Assessing the Needs of NASA's Near Real-Time Earth Observation Products

"The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers who add value to the data [4]. NASA Earth Applied Sciences Program (ASP) is one of the primary users of LANCE, which collaborates with partner organizations and provides support to scientists to solve problems in applications of earth observations. ASP promotes the use of LANCE NRT data products to demonstrate applications in decision making, facilitates end-user feedback to the science team to improve data products, and provides information on future demands for research. LANCE supports applications that need a rapid response including detecting wildland fires and volcanic eruptions, tracking smoke, ash and dust plumes, monitoring air quality and tracking extreme weather events such as hurricanes, landslides, and floods. To gather feedback regarding the availability, accessibility and actionability of NASA's NRT data products for societal benefit, three surveys and a few discussions with experts involved in the topic within ASP were conducted from the perspective of users. Feedback has been collected from users who are interested in using low latency NASA data within application communities of agriculture, disasters, water resources, health and air quality, ecological conservation, wildland fires and capacity building. Analysis-ready NRT data products in a variety of formats have been mentioned many times in the collected feedback, especially for applied users with little to no experience using research-grade earth observation products. Users prefer to have products that can be easily integrated into their existing workflows and take their analysis to the data. HDF5 is a commonly used data format for research, but typically requires some conversion to a more friendly format for applications and regular use in decision-making. Users prefer the GeoTIFF data format that can be directly ingested into a GIS mapping software and platform for data analysis and visualization. For example, LANCE’s fire, flood, SO2 and Black Marble Nighttime Blue/Yellow Composite data products have been integrated into NASA Disasters Mapping Portal, which is an GIS-based open data portal, for users in the disaster management community. There are 291 LANCE NRT layers available through GIBS and Worldview, where users can download a snapshot in GeoTIFF format. Operational users expect data to be processed as close to the user as possible. The collected feedback indicates that LANCE fire products within 3 hours latency would meet the needs of the wildland fire community. The ideal latency for volcanic application is 10-15 minutes. Users in Volcanic Ash Advisory Centers (VAAC) reported that the first forecast volcanic product should be issued within 75 minutes from the volcano eruption [5]. Overall, for disaster applications, data latency within 3 hours is useful while latency greater than 12 hours is not timely enough for operational use. Capacity building and training are critical for users to be able to access, interpret and use data products and tools for their decision making, especially for applied users with limited experience using earth observation products. LANCE data products have been used in a number of capacity building projects domestically and internationally [6]. As LANCE continues to bring new products into the system, users request training to utilize LANCE new and upcoming data products and capabilities in their applications. Due to the limitation of bandwidth and downstream flow paths, users in some developing countries need tools to select and download data for a specific area of interest instead of bulk downloads. The collected feedback also shows the lack of available SAR satellite low latency data products. The advantages of SAR to monitor conditions and changes on the ground through darkness, clouds, volcanic ash, and other atmospheric conditions, are appealing to low latency users. For example, terabytes of low latency but cloudy optical images are not helpful in rapidly identifying the extent of flood or fire impacts. LANCE could be complemented with low latency measurements via the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission [7]. Requests for higher spatial resolution products are expressed. A user from the wildland fire management community reported that products with 30-m spatial resolution could be used to detect small fires. The 30-m Landsat OLI fire data is now part of NASA’s Fire Information for Resource Management System (FIRMS) US/Canada [8]. Within the open and free NASA resources, LANCE disseminates NRT data products in a manner that allows them to be accessible and understandable to both scientific and applied users. In many application areas, latency plays an important or even decisive role where low latency earth observations help people to observe areas of interest, detect and track changes in the environment and make timely decisions. NASA’s Earth Applied Sciences Program promotes the use of LANCE NRT products and builds a bridge between application users and research teams. The collected feedback indicates data latency within 3 hours is useful for most of the applications, and shows the needs of user-friendly, analysis-ready products, and requests training on LANCE’s new and upcoming data products. User feedback has been provided to LANCE UWG for guidance and recommendations, and for translating findings into something actionable.

Tian Yao↗

X-ray Binary Luminosity Function Scaling Relations for Local Galaxies Based on Subgalactic Modeling

We present new Chandra constraints on the X-ray luminosity functions(XLFs)of X-ray binary(XRB)populations, as well as their scaling relations, for a sample of 38 nearby galaxies(D = 3.4–29 Mpc). Our galaxy sample is drawn primarily from the Spitzer Infrared Nearby Galaxies Survey(SINGS)and contains a wealth of Chandra(5.8 Ms total)and multiwavelength data, allowing for star formation rates(SFRs)and stellar masses(M⁎)to be measured on subgalactic scales. We divided the 2478 X-ray-detected sources into 21 subsamples in bins of specific SFR(sSFR ≡ SFR/M⁎)and constructed XLFs. To model the XLF dependence on sSFR, we fit a global XLF model, containing contributions from high-mass XRBs(HMXBs), low-mass XRBs(LMXBs), and background sources from the cosmic X-ray background that respectively scale with SFR, M⁎, and sky area. We find an HMXB XLF that is more complex in shape than previously reported and an LMXB XLF that likely varies with sSFR, potentially due to an age dependence. When applying our global model to XLF data for each individual galaxy, we discover a few galaxy XLFs that significantly deviate from our model beyond statistical scatter. Most notably, relatively low-metallicity galaxies have an excess of HMXBs above≈10^(38)erg/s, and elliptical galaxies that have relatively rich populations of globular clusters(GCs)show excesses of LMXBs compared to the global model. Additional modeling of how the XRB XLF depends on stellar age, metallicity, and GC specific frequency is required to sufficiently characterize the XLFs of galaxies.

Bret D. Lehmer↗

Final Technical Report for "Cloud-based Low-Scaling Quantum Chemistry Simulations for Materials"

The objective of phase I was to develop the basic infrastructure for performing efficient hybrid DFT calculations on solid materials with a turnaround time amenable to the use in large-scale data-driven approaches. To fulfill the goal we have developed a novel algorithm that significantly reduces the cost of exchange matrix formation. The algorithm does so by making use of three ingredients (a) interpolative decomposition of the electron integrals (b) robust pseudospectral method and (c) occ-RI approach. Our published work demonstrates that the algorithm is orders of magnitude faster than any other hybrid-DFT method and is on the order of only 3-4 times slower than pure DFT. All steps of the algorithm developed during phase I can be accelerated to the point that, for large enough systems, the diagonalization of the Fock matrix will become the most expensive step. To treat such large systems we have created an interface to the ASCR-funded PEXSI library. The PEXSI method is used to compute the density matrix directly from the Fock matrix in a manner that preserves the sparsity of the local representation.

Shiozaki, Toru↗

The Pixel Anomaly Detection Tool : a user-friendly GUI for classifying detector frames using machine-learning approaches

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

47 OTHER INSTRUMENTATION↗

Isolated cold plasma regions: Observations and their relation to possible production mechanisms

Regions of enhanced cold plasma, isolated from the main plasmasphere along the Explorer 45 orbit on the equatorial plane, are reported using the sheath induced potentials seen by the electric field experiment. The occurrence of these regions has a strong correlation with negative enhancements of Dst, and their locations are primarily in the noon-dusk quadrant. The data support the concept that changes in large scale convection play a dominant role in the formation of these regions. Plasmatails that are predicted from enhancements of large scale convection electric fields in general define where these regions may be found. More localized processes are necessary to account for the exact configuration and structure seen in these regions and may eventually result in detachment from the main plasmasphere.

Maynard, N. C.↗

ALMA Detection and Astrobiological Potential of Vinyl Cyanide on Titan

Recent simulations have indicated that vinyl cyanide is the best candidate molecule for the formation of cell membranes/vesicle structures in Titan's hydrocarbon-rich lakes and seas. Although the existence of vinyl cyanide (C2H3CN) on Titan was previously inferred using Cassini mass spectrometry, a definitive detection has been lacking until now. We report the first spectroscopic detection of vinyl cyanide in Titan's atmosphere, obtained using archival data from the Atacama Large Millimeter/submillimeter Array (ALMA), collected from February to May 2014. We detect the three strongest rotational lines of C2H3CN in the frequency range of 230 to 232 GHz, each with greater than 4 sigma confidence. Radiative transfer modeling suggests that most of the C2H3CN emission originates at altitudes of approx. greater than 200 km, in agreement with recent photochemical models. The vertical column densities implied by our best-fitting models lie in the range of 3.7 x 10(exp 13) to 1.4 x 10(exp 14) cm(exp −2). The corresponding production rate of vinyl cyanide and its saturation mole fraction imply the availability of sufficient dissolved material to form approx. 10(exp 7) cell membranes/cu cm in Titan's sea Ligeia Mare.

Palmer, Maureen Y.↗

A report on the use of thermal scanner data in an operational program for monitoring apparent rooftop temperatures

CENGAS, a division of Central Telephone and Utilities Corporation in cooperation with the Remote Sensing Institute, South Dakota State University, is using airborne thermal scanner data to monitor relative rooftop temperatures. Four Nebraska communities and one South Dakota community were surveyed by the Remote Sensing Institute for CENGAS. Thermal scanner data were converted to a film format and the resultant imagery has been successfully employed by CENGAS. The program places emphasis on heat losses resulting from inadequate home insulation, offers CENGAS customers the opportunity to observe a thermogram of their rooftop, and assists homeowners in evaluating insulation needs.

Bjorklund, J.↗

Developing a complete AI-accelerated workflow for superconductor discovery

The quest to identify new superconducting materials with enhanced properties is hindered by the prohibitive cost of computing electron-phonon spectral functions, severely limiting the materials space that can be explored. Here, we introduce a Bootstrapped Ensemble of Equivariant Graph Neural Networks (BEE-NET), a machine-learning model trained to predict the Eliashberg spectral function and superconducting critical temperature with a mean-absolute-error of 0.87 K relative to DFT-based Allen-Dynes calculations. Intriguingly, BEE-NET achieves a true-negative-rate of 99.4%, enabling highly efficient screening for the rare property of superconductivity. Integrated into a multi-stage, AI-accelerated discovery pipeline that incorporates elemental-substitution strategies and machine-learned interatomic potentials, our workflow reduced over 1.3 million candidate structures to 741 dynamically and thermodynamically stable compounds with DFT-confirmed T c > 5 K. We report the successful synthesis and experimental confirmation of superconductivity in two of these previously unreported compounds. This study establishes a data-driven framework that integrates machine learning, quantum calculations, and experiments to systematically accelerate superconductor discovery.

Gibson, Jason B. [Quantum Formatics, Cambridge, MA↗

SBIR Phase I Final Report, TACO: Distributed and Heterogeneous Sparse Compiler

Tensor algebra is a powerful tool for computing, but writing optimized codes that operate on sparse tensors can be very complex. This project enables a Tensor Algebra Compiler (TACO) that simplifies this task from man-years to man-days and extends TACO to support complex and large distributed systems. This report details the hypotheses, approaches used, and findings in this project.

97 MATHEMATICS AND COMPUTING↗

Computed Tomography Scanning and Geophysical Measurements of the Patterson #5-25 Well in Western Kansas

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) site in Morgantown, West Virginia, were used to characterize core from the Patterson Field site. This core came from a vertical well (Patterson #5-25 well) that was obtained as part of the U.S. Department of Energy (DOE) sponsored Integrated Midcontinental Stacked Carbon Storage Hub. The primary impetus of this work is a collaboration between NETL and the Kansas Geological Survey to characterize core from the Patterson Field site. The 625 ft of whole core from the Atoka Formation to Precambrian Basement was characterized at NETL. As part of this effort, bulk scans of core were obtained. This report, and the associated scans, provide detailed datasets not typically made publicly available for carbon capture utilization and storage analysis. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/patterson-5-25-well. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. None of the equipment used was suitable for direct visualization of the shale pore space, although fractures and discontinuities were detectable with the methods tested. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with x-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL are useful in identifying zones of interest for more detailed analysis as well as fractured zones. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provided both a macro and micro description of the core that is relevant for many subsurface energy related examinations that have traditionally been performed at NETL.

58 GEOSCIENCES↗

PLTTER user's guide

The PLTTER graphics system, which is part of CDDMS is discussed. CDDMS is a comprehensive system for data basing and subsequent plotting of data acquired during wind tunnel tests or from computational flow analyses. The PLTTER is a system which creates report-quality plots of data which is stored on a CDDMS data base. The Requests file system allows plot-controlling information to be arranged in the way which is most appropriate for any application. The PLTTER system features many capabilities which are especially useful when plotting wind tunnel data. The PLTTER offers a variety of page formats, different grid options and parametric curve fitting algorithms, and a powerful legend capability to identify relevant information about individual curves. One or more plots on a page can be suppressed if desired so that an established page format can be maintained. Final plot output may be standard Versatec plots, QMS Laser printer plots, or microfiche.

Barlow, A.↗

Emission-line galaxies in the third list of the Case Low-Dispersion Northern Sky Survey

Observations of 47 galaxies in the third Case list are reported. Thirty-five of the galaxies in the sample were selected for the presence of emission lines on the objective prism plates. At the higher spectral dispersion of the data, significant line emission was found in 46 of the 47 galaxies. Twenty-six galaxies are found to be undergoing significant bursts of star formation. Ten additional galaxies may be starburst galaxies with low-excitation spectra. Two galaxies are probably type Seyfert 2. The most distant object, CG 200, at a redshift of 0.144, has a strong broad H-alpha emission line, and is probably a Seyfert 1. Seventeen of the galaxies have been detected by IRAS. Eight of the IRAS galaxies have H-II-region-type spectra and eight have low-ionization starburst spectra. The galaxies represent a mixture of types, ranging from intrinsically faint dwarf galaxies with Mb equalling -16 mag, to powerful galaxies with MB equalling -23 mag. Galaxies CG 234 and CG 235 are interacting, as are galaxies CG 269 and CG 270.

Weistrop, Donna↗