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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗
DOE OSTI2023

Surface Water Disinfection Byproducts and Organic Matter Characterization Data Associated with: “Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream”

This dataset is associated with the publication “Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream” published in Water Research X (Leonard et al. 2022; https://doi.org/10.1016/j.wroa.2022.100144). The associated study analyzed temporal trends from the Town of Crested Butte water treatment facility and synoptic sampling at Coal Creek in Crested Butte, Colorado, US. This work demonstrates how drinking water quality archives combined with synoptic sampling and targeted analyses can be used to identify and understand export control points for dissolved organic matter. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) metadata and international geo-sample number (IGSN) mapping file; (4) dissolved organic carbon (DOC), ultraviolet absorbance at 254 nanometers (UV254), total nitrogen (TN), and specific ultraviolet absorbance (SUVA) data; (5) disinfection bioproduct formation potential (DBP-FP) data; (6) readme; (7) methods codes; (8) water collection protocol; (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory); and (10) folder of excitation emissions matrix (EEM) spectra. The FTICR folder contains a file of DOC (measured as non-purgeable organic carbon; NPOC) used for FTICR sample preparation. The FTICR folder also contains three subfolders: one subfolder containing the raw .xml data files, one containing the processed data, and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .dat, .R, .ref, or .xml

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

sampling timing↗
DOE OSTI2021

MolDiscovery: learning mass spectrometry fragmentation of small molecules

Identification of small molecules is a critical task in various areas of life science. Recent advances in mass spectrometry have enabled the collection of tandem mass spectra of small molecules from hundreds of thousands of environments. To identify which molecules are present in a sample, one can search mass spectra collected from the sample against millions of molecular structures in small molecule databases. The existing approaches are based on chemistry domain knowledge, and they fail to explain many of the peaks in mass spectra of small molecules. Here, we present molDiscovery, a mass spectral database search method that improves both efficiency and accuracy of small molecule identification by learning a probabilistic model to match small molecules with their mass spectra. A search of over 8 million spectra from the Global Natural Product Social molecular networking infrastructure shows that molDiscovery correctly identify six times more unique small molecules than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

Development and testing of a portable wind sensitive directional air sampler

A portable wind-sensitive directional air sampler has been developed as part of an air pollution source identification system. The system is designed to identify sources of air pollution based on the directional collection of field air samples and their analysis for TSP and trace element characteristics. Sources can be identified by analyzing the data on the basis of pattern recognition concepts. Functional testing of a prototype sampler is described; all items exhibited performance and life sufficient to carry out field performance test operations. Life testing of the wind direction sensor and the directional porting valves, which are critical to reliable operation, was emphasized with successful results.

Deyo, J.↗
NASA NTRS2006

Miniature Gas Chromatograph (GC): Penning Ionization Electron Spectroscopy (PIES) Instrument for the Trace Analyses of Extraterrestrial Environments

In situ exploration of the solar system to identify its early chemistry as preserved in icy bodies and to look for compelling evidence of astrobiology will require new technology for chemical analysis. Chemical measurements in space flight environments highlight the need for a high level of positive identification of chemical compounds, since re-measurement by alternative techniques for confirmation will not be feasible. It also may not be possible to anticipate all chemical species that are observed, and important species may be present only at trace levels where they can be masked by complex chemical backgrounds. Up to now, the only techniques providing independent sample identification of GC separated components across a wide range of chemical species have been Mass Spectrometry (MS) and Ion Mobility Spectrometry (IMS). We describe here the development of a versatile and robust miniature GC detector based on Penning Ionization Electron Spectroscopy (PIES), for use with miniature GC systems being developed for planetary missions. PIES identifies the sample molecule through spectra related to its ionization potential. The combination of miniature GC technology with the primary identification capabilities of PIES provides an analytical approach ideal for planetary analyses.

Kojiro, Daniel R.↗
DOE OSTI2024

SCA Tools - SCRM Value Add or Lossy Noise Machines

Software supply chain risk management (SCRM) depends upon accurate information regarding the software components that comprise any given software system. The collection of components included in a software package can be organized within a software bill of materials, or SBOM. SBOMs are ideally generated when the software components are put together, such as at compile time, but for many reasons that has not and is not always possible. For example, legacy or proprietary software packages often do not have SBOMs available to downstream consumers of that software. It’s not just end users that are affected, manufacturers themselves also must deal with this problem. To answer these questions, the market has seen the rise of several commercial software composition analysis (SCA) tools. These tools aim to peer into completed software systems, automatically identifying hidden software dependencies and looking up known vulnerabilities associated with those dependencies to enable end-users to enhance their cyber supply chain risk management processes. These tools are potentially a huge boon to end users of legacy and proprietary software – and a potential bane, depending on how accurate they are. This research asks that question – how accurate are currently available binary SCA tools – and provides answers to several other questions: What does it mean to be “accurate”? What limitations do the tools have in identifying common edge cases that take place in modern software development? Can they help you avoid a devastating supply chain attack, or is it all just noise? After researching SCA tools on the market, we identified three vendors that fit our use case and would provide analysis on compiled binaries. Using these tools, we submitted firmware for critical infrastructure devices for analysis and SBOM generation. The SBOM outputs were then cross referenced with SBOMs generated through manual analysis for comparison. In addition to the firmware samples, we also submitted edge case samples based off a popular open-source library that were specifically crafted to evaluate each tools’ ability to accurately identify components. These samples were customized to be consistent with modifications we have seen in modern software development as well as a couple that are representative of supply chain attacks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DESI z ≳ 5 Quasar Survey. I. A First Sample of 400 New Quasars at z ~ 4.7–6.6

We report the first results of a high-redshift (z ≳ 5) quasar survey using the Dark Energy Spectroscopic Instrument (DESI). As a DESI secondary target program, this survey is designed to carry out a systematic search and investigation of quasars at 4.8 < z < 6.8. The target selection is based on the DESI Legacy Imaging Surveys (the Legacy Surveys) DR9 photometry, combined with the Pan-STARRS1 data and J-band photometry from public surveys. A first quasar sample has been constructed from the DESI Survey Validation 3 (SV3) and first-year observations until 2022 May. This sample includes more than 400 new quasars at redshift 4.7 ≤ z < 6.6, down to 21.5 magnitude (AB) in the z band, discovered from 35% of the entire target sample. Remarkably, there are 220 new quasars identified at z ≥ 5, more than one-third of existing quasars previously published at this redshift. The observations so far result in an average success rate of 23% at z > 4.7. The current spectral data set has already allowed analysis of interesting individual objects (e.g., quasars with damped Lyα absorbers and broad absorption line features), and statistical analysis will follow the survey's completion. A set of science projects will be carried out leveraging this program, including quasar luminosity function, quasar clustering, intergalactic medium, quasar spectral properties, intervening absorbers, and properties of early supermassive black holes. Additionally, a sample of 38 new quasars at z ~ 3.8–5.7 discovered from a pilot survey in the DESI SV1 is also published in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗
NASA NTRS2008

Tracing the Mass-Dependent Star Formation History of Late-Type Galaxies using X-ray Emission: Results from the CHANDRA Deep Fields

We report on the X-ray evolution over the last approx.9 Gyr of cosmic history (i.e., since z = 1.4) of late-type galaxy populations in the Chandra Deep Field-North and Extended Chandra Deep Field-South (CDF-N and E-CDF-S. respectively; jointly CDFs) survey fields. Our late-type galaxy sample consists of 2568 galaxies. which were identified using rest-frame optical colors and HST morphologies. We utilized X-ray stacking analyses to investigate the X-ray emission from these galaxies, emphasizing the contributions from normal galaxies that are not dominated by active galactic nuclei (AGNs). Over this redshift range, we find significant increases (factors of approx. 5-10) in the X-ray-to-optical mean luminosity ratio (L(sub x)/L(sub B)) and the X-ray-to-stellar-mass mean ratio (L(sub x)/M(sub *)) for galaxy populations selected by L(sub B) and M(sub *), respectively. When analyzing galaxy samples selected via SFR, we find that the mean X-ray-to-SFR ratio (L(sub x)/SFR) is consistent with being constant over the entire redshift range for galaxies with SFR = 1-100 Solar Mass/yr, thus demonstrating that X-ray emission can be used as a robust indicator of star-formation activity out to z approx. 1.4. We find that the star-formation activity (as traced by X-ray luminosity) per unit stellar mass in a given redshift bin increases with decreasing stellar mass over the redshift range z = 0.2-1, which is consistent with previous studies of how star-formation activity depends on stellar mass. Finally, we extend our X-ray analyses to Lyman break galaxies at z approx. 3 and estimate that L(sub x)/L(sub B) at z approx. 3 is similar to its value at z = 1.4.

Lehmer, B.D↗
DOE OSTI2023

Accelerating Nature: Induced Atomic Order in Equiatomic FeNi

Abstract The production of locally atomically ordered FeNi (known by its meteoric mineral name, tetrataenite) is confirmed in bulk samples by simultaneous conversion X‐ray and backscattered γ‐ray 57 Fe Mössbauer spectroscopy. Up to 22 volume percent of the tetragonal tetrataenite phase is quantified in samples thermally treated under simultaneous magnetic‐ and stress‐field conditions for a period of 6 weeks, with the remainder identified as the cubic FeNi alloy. In contrast, all precursor samples consist only of the cubic FeNi alloy. Data from the processed alloys are validated using Mössbauer parameters derived from natural meteoritic tetrataenite. The meteoritic tetrataenite exhibits a substantially higher degree of atomic order than do the processed samples, consistent with their low uniaxial magnetocrystalline anisotropy energy of ≈1 kJ·m −3 . These results suggest that targeted refinements to the processing conditions of FeNi will foster greater atomic order and increased magnetocrystalline anisotropy, leading to an enhanced magnetic energy product. These outcomes also suggest that deductions concerning paleomagnetic conditions of the solar system, as derived from meteoritic data, may warrant re‐examination and re‐evaluation. Additionally, this work strengthens the argument that tetrataenite may indeed become a member of the advanced permanent magnet portfolio, helping to meet rapidly escalating green energy imperatives.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Host-specific and tissue-dependent orchestration of microbiome community structure in traditional rice paddy ecosystems

Abstract Background and aim Rice and duckweed are two monocotyledonous plants that naturally coexist in paddy fields. While the presence of duckweed in paddy fields significantly improves rice productivity, the interplay between soil microbes and the two plant hosts in this agroecosystem remains unexplored. Methods We compared the bacterial community structure between duckweed, rice and soil from multiple rice paddies. We also isolated bacteria from these communities and characterized their modes of bacterial colonization and plant growth-promotion using model plants. Results Our data indicate that host-specific and tissue-dependent factors reproducibly orchestrate the bacterial community structure associated with their plant hosts. This is corroborated by results from culture-dependent approaches in which the dominant genus Pantoea isolated from rice aerial tissues can strongly attach and colonize gnotobiotic duckweed in spite of the low representation of this bacterial genus in the natural duckweed microbiome. Our study identified a core of 254 bacterial taxa that are consistently found in all rice and duckweed tissue samples from rice paddy fields. Furthermore, characterizing auxin-producing bacteria isolates from both plant species identified potential plant growth-promoting bacteria that may improve growth for both duckweed and rice in paddy fields. Conclusions Results from this work provide evidence for the importance of the host tissue and species context in determining plant colonization by microbes in the paddy field system. The resources generated in this study could facilitate the agronomic deployment of microbes for more sustainable rice production.

Agriculture↗
DOE OSTI2023

Multi-Scale Characterization of Porosity and Cracks in Silicon Carbide Cladding after Transient Reactor Test Facility Irradiation

Silicon carbide (SiC) ceramic matrix composite (CMC) cladding is currently being pursued as one of the leading candidates for accident-tolerant fuel (ATF) cladding for light water reactor applications. The morphology of fabrication defects, including the size and shape of voids, is one of the key challenges that impacts cladding performance and guarantees reactor safety. Therefore, quantification of defects’ size, location, distribution, and leak paths is critical to determining SiC CMC in-core performance. This research aims to provide quantitative insight into the defect’s distribution under multi-scale characterization at different length scales before and after different Transient Reactor Test Facility (TREAT) irradiation tests. A non-destructive multi-scale evaluation of irradiated SiC will help to assess critical microstructural defects from production and/or experimental testing to better understand and predict overall cladding performance. X-ray computed tomography (XCT), a non-destructive, data-rich characterization technique, is combined with lower length scale electronic microscopic characterization, which provides microscale morphology and structural characterization. This paper discusses a fully automatic workflow to detect and analyze SiC-SiC defects using image processing techniques on 3D X-ray images. Following the XCT data analysis, advanced characterizations from focused ion beam (FIB) and transmission electron microscopy (TEM) were conducted to verify the findings from the XCT data, especially quantitative results from local nano-scale TEM 3D tomography data, which were utilized to complement the 3D XCT results. In this work, three SiC samples (two irradiated and one unirradiated) provided by General Atomics are investigated. The irradiated samples were irradiated in a way that was expected to induce cracking, and indeed, the automated workflow developed in this work was able to successfully identify and characterize the defects formation in the irradiated samples while detecting no observed cracking in the unirradiated sample. These results demonstrate the value of automated XCT tools to better understand the damage and damage propagation in SiC-SiC structures for nuclear applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Calibration and Uncertainty Estimation Using the Ensemble Kalman Filter with a Large Subsurface Flow and Transport Model - 20321

At routinely monitored groundwater contamination sites, periodically measured environmental conditions such as groundwater levels and contaminant concentrations are used to inform and confirm a conceptual site model (CSM) and guide the development and calibration of a numerical groundwater flow and transport model. The calibration of groundwater flow and transport models after each measurement (sampling) event can illuminate deficiencies in a CSM, identify areas where additional monitoring is warranted, and predict the behavior of the system to guide decision making. However, manual and automated (e.g. PEST) model calibration tools can be time-consuming and computationally expensive to implement after each sampling event. Perhaps as a result, such calibration tools generally utilize all available monitoring data simultaneously rather than sequentially assimilating monitoring data one sampling event at a time as the results from sampling become available. A more real-time data assimilation approach may reduce parameter uncertainty, quantify the value of additional monitoring data, and produce a usable model more quickly and with less effort. To mitigate the potential time-consuming aspects of manual and widely applied automated calibration techniques, a data assimilation algorithm called the ensemble Kalman filter (EnKF) was evaluated as a relatively efficient method of model calibration and uncertainty assessment via the sequential integration of monitoring data into a model. The EnKF was able to successfully and efficiently assimilate monitoring and modeling data to calibrate a complex flow and transport model at a real-world site with significant subsurface heterogeneity, uncertainty, and 12 years of monitoring data (over 4,000 individual measurements of groundwater levels and over 2,500 measurements of contaminant concentrations). Starting with an uncalibrated model data from annual sampling events were sequentially assimilated, and the resultant predication errors and estimated parameter uncertainties were tracked. After all monitoring data were assimilated, both flow and transport residuals at the end of the EnKF process were comparable to those produced via a concurrent PEST calibration effort but required fewer model simulations. Both uncertainty and prediction errors decreased over time. In a real-time application, the adequacy of the model could be assessed after each sampling event. The benefits of such a real-time approach to utilizing monitoring data include reduced costs (in the form of model updates or site characterization efforts), early flagging of possible errors in the CSM, and a reduced risk of overfitting and corresponding increased confidence in model predictions. This tool may be particularly useful compared to other calibration techniques (e.g. manual, PEST) when model runtimes are long, calibration parameters are many, or parameter uncertainty is large. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomics measures the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of significant changes in subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot precisely infer the abundance changes of intact proteins, which are presented as proteoforms. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantification directly on thin tissue sections. The spatial TDP platform consisted of a nanoPOTS (nanodroplet Processing in One pot for Trace Samples)-based sample preparation system and an LCM (laser capture microdissection)-based cell isolation system. We improved the nanoPOTS sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ~200 cultured cells as model samples, the improved approach increased proteoform identifications from 493 to 700; newly identified proteoforms primarily corresponded to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed LCM-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 426 proteoforms by combining identifications from TopPIC and TDPortal with the quantitation from ProMex. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential PTM-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Prediction of ECS and SSC Models for Flux-Limited Samples of Gamma-Ray Blazars

The external Compton scattering (ECS) and synchrotron self-Compton (SSC) models make distinct predictions for the amount of Doppler boosting of high-energy gamma-rays emitted by Nazar. We examine how these differences affect the predicted properties of active galactic nucleus (AGN) samples selected on the basis of Murray emission. We create simulated flux-limited samples based on the ECS and SSC models, and compare their properties to those of identified EGRET blazars. We find that for small gamma-ray-selected samples, the two models make very similar predictions, and cannot be reliably distinguished. This is primarily due to the fact that not only the Doppler factor, but also the cosmological distance and intrinsic luminosity play a role in determining whether an AGN is included in a flux-limited gamma-ray sample.

Lister, Matthew L.↗
NASA NTRS1986

Analysis of a thioether lubricant by infrared Fourier microemission spectrophotometry

An infrared Fourier microemission spectrophotometer is used to obtain spectra (wavenumber range, 630 to 1230 0.1 cm) from microgram quantities of thioether lubricant samples deposited on aluminum foil. Infrared bands in the spectra are reproducible and could be identified as originating from aromatic species (1,3-disubstituted benzenes). Spectra from all samples (neat and formulated, used and unused) are very similar. Additives (an acid and a phosphinate) present in low concentration (0.10 percent) in the formulated fluid are not detected. This instrument appears to be a viable tool in helping to identify lubricant components separated by liquid chromatography.

Jones, W. R., Jr.↗
NASA NTRS1993

Containerless processing of undercooled melts

The investigation focused on the control of microstructural evolution in Mn-Al, Fe-Ni, Ni-V, and Au-Pb-Sb alloys through the high undercooling levels provided by containerless processing, and provided fundamental new information on the control of nucleation. Solidification analysis was conducted by means of thermal analysis, x-ray diffraction, and metallographic characterization on samples processed in a laboratory scale drop tube system. The Mn-Al alloy system offers a useful model system with the capability of phase separation on an individual particle basis, thus permitting a more complete understanding of the operative kinetics and the key containerless processing variables. This system provided the opportunity of analyzing the nucleation rate as a function of processing conditions and allowed for the quantitative assessment of the relevant processing parameters. These factors are essential in the development of a containerless processing model which has a predictive capability. Similarly, Ni-V is a model system that was used to study duplex partitionless solidification, which is a structure possible only in high under cooling solidification processes. Nucleation kinetics for the competing bcc and fcc phases were studied to determine how this structure can develop and the conditions under which it may occur. The Fe-Ni alloy system was studied to identify microstructural transitions with controlled variations in sample size and composition during containerless solidification. This work was forwarded to develop a microstructure map which delineates regimes of structural evolution and provides a unified analysis of experimental observations. The Au-Pb-Sb system was investigated to characterize the thermodynamic properties of the undercooled liquid phase and to characterize the glass transition under a variety of processing conditions. By analyzing key containerless processing parameters in a ground based drop tube study, a carefully designed flight experiment may be planned to utilize the extended duration microgravity conditions of orbiting spacecraft.

Perepezko, J. H.↗