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At least 235 records · Page 13

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NASA NTRS2016

First Detection of Non-Chlorinated Organic Molecules Indigenous to a Martian Sample

The Sample Analysis at Mars (SAM) instrument onboard Curiosity can perform pyrolysis of martian solid samples, and analyze the volatiles by direct mass spectrometry in evolved gas analysis (EGA) mode, or separate the components in the GCMS mode (coupling the gas chromatograph and the mass spectrometer instruments). In addition, SAM has a wet chemistry laboratory designed for the extraction and identification of complex and refractory organic molecules in the solid samples. The chemical derivatization agent used, N-methyl-N-tert-butyldimethylsilyl- trifluoroacetamide (MTBSTFA), was sealed inside seven Inconel metal cups present in SAM. Although none of these foil-capped derivatization cups have been punctured on Mars for a full wet chemistry experiment, an MTBSTFA leak was detected and the resultant MTBSTFA vapor inside the instrument has been used for a multi-sol MTBSTFA derivatization (MD) procedure instead of direct exposure to MTBSTFA liquid by dropping a solid sample directly into a punctured wet chemistry cup. Pyr-EGA, Pyr-GCMS and Der-GCMS experiments each led to the detection and identification of a variety of organic molecules in diverse formations of Gale Crater.

Freissinet, C.↗

DOE OSTI2023

Chemical Signatures of Seasonally Unique Anthropogenic Influences on Organic Aerosol Composition in the Central Amazon

Urbanization and fires perturb the quantities and composition of fine organic aerosol in the central Amazon, with ramifications for radiative forcing and public health. These disturbances include not only direct emissions of particulates and secondary organic aerosol (SOA) precursors, but also changes in the pathways through which biogenic precursors form SOA. The composition of ambient organic aerosol is complex and incompletely characterized, encompassing millions of potential structures relatively few of which have been synthesized and characterized. Through analysis of submicron aerosol samples from the Green Ocean Amazon (GoAmazon2014/5) field campaign by two-dimensional gas chromatography coupled with machine learning, ~1300 unique compounds were traced and characterized over two seasons. Fires and urban emissions produced chemically and interseasonally distinct impacts on product signatures, with only ~50% of compounds observed in both seasons. Seasonally unique populations point to the importance of aqueous processing in Amazonian aerosol ageing, but further mechanistic insights are impeded by limited product identity knowledge. Further, less than 10% of compounds were identifiable at an isomer-specific level. Overall, the findings (i) provide compositional characterization of anthropogenic influence on submicron organic aerosol in the Amazon, (ii) identify key season-to-season differences in chemical signatures, and (iii) highlight high-priority knowledge gaps in current speciated knowledge.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Unimodal Imaging of Monovalent Metal-Chelator Complexes and Lipids by MALDI Imaging Mass Spectrometry

Careful regulation of monovalent metal ions (M + ) is necessary to maintain a functional cellular system. Of these ions, appropriate sodium (Na + ) and potassium (K + ) concentrations are particularly integral for electrochemical signaling, as well as the secondary transport of nutrients and waste. Dysregulation of M + homeostasis can disrupt these mechanisms, potentially influencing the metabolism of downstream biomolecules such as lipids. Thus, the relationship between M + abundances and related biomolecular distributions must be elucidated to better understand the physiology of healthy and disordered tissues. Traditional techniques for imaging biological metal distributions include SIMS, LA-ICP-MS, and XRF; however, these capabilities are limited to elemental analysis or the analysis of molecular fragments and must be paired with other modalities to visualize distributions of more complex biomolecules within the same or similar samples. Conversely, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool often used for mapping such biomolecular distributions, but current methods are unable to detect metals within tissue. This study illustrates a novel methodology that adds metal detection to the MALDI IMS repertoire through which the simultaneous detection of M + metals and lipids is achievable. Using a robotic sprayer for homogeneous application, on-tissue deposition of the chelator deferiprone (DEF) enables subsequent detection of the ionizable metal-chelator complex by MALDI without hindering lipid detection. Our work provides proof-of-concept data for the simultaneous detection of K + , Na + , and intact lipids using MALDI IMS.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

Space station integrated wall design and penetration damage control

The analysis code BUMPER executes a numerical solution to the problem of calculating the probability of no penetration (PNP) of a spacecraft subject to man-made orbital debris or meteoroid impact. The codes were developed on a DEC VAX 11/780 computer that uses the Virtual Memory System (VMS) operating system, which is written in FORTRAN 77 with no VAX extensions. To help illustrate the steps involved, a single sample analysis is performed. The example used is the space station reference configuration. The finite element model (FEM) of this configuration is relatively complex but demonstrates many BUMPER features. The computer tools and guidelines are described for constructing a FEM for the space station under consideration. The methods used to analyze the sensitivity of PNP to variations in design, are described. Ways are suggested for developing contour plots of the sensitivity study data. Additional BUMPER analysis examples are provided, including FEMs, command inputs, and data outputs. The mathematical theory used as the basis for the code is described, and illustrates the data flow within the analysis.

Coronado, A. R.↗

NASA NTRS1997

The Origin, Composition and History of Comets from Spectroscopic Studies

A wealth of information essential to understanding the composition and physical structure of cometary ice and hence gain deep insight into the comet's origin and history, can be gleaned by carrying out a full range of spectroscopic studies on the returned sample. These studies ought to be among the first performed as they are generally non-destructive and will provide a broad data bank which will be crucial in planning subsequent analysis. Examples of the spectroscopic techniques along with relative sensitivities and transitions probed, are discussed. Different kind of "spectroscopy" is summarized, with emphasis placed on the kind of information each provides. Infrared spectroscopy should be the premier method of analysis as the mid-IR absorption spectrum of a substance contains more global information about the identity and structure of that material than any other property. In fact, the greatest strides in our understanding of the composition of interstellar ices (thought by many to be the primordial material from which comets have formed) have been taken during the past ten years or so because this was when high quality infrared spectra of the interstellar medium (ISM) first became available. The interpretation of the infrared spectra of mixtures, such as expected in comets, is often (not always) ambiguous. Consequently, a full range of other non-destructive, complementary spectroscopic measurements are required to fully characterize the material, to probe for substances for which the IR is not well suited and to lay the groundwork for future analysis. Given the likelihood that the icy component (including some of the organic and mineral phases) of the returned sample will be exceedingly complex, these techniques must be intensely developed over the next decade and then made ready to apply flawlessly to what will certainly be one of the most precious, and most challenging, samples ever analyzed.

Allamandola, L. J.↗

NASA NTRSDate not supplied

Organic Carbon Concentrations in 3-Billion-Year-Old Lacustrine Mudstones of Mars

Understanding the inventory of carbon on Mars is relevant to the question of whether Mars was ever habitable. While the Mars atmosphere represents a large reservoir of carbon, in situ pyrolysis performed on Mars and meteorite analyses indicate that another significant reservoir of carbon is the rocks themselves. Complex organic carbon was discovered in 3.5 Ga mudstones sampled at Cumberland (CB) in the Yellowknife Bay Formation in Gale Crater by the Sample Analysis at Mars (SAM) instrument suite on the Mars Science Laboratory (MSL) using a thermal decomposition technique called evolved gas analysis (EGA). Other simple organics have also been detected in these same CB materials. Low temperature co-evolution of CO and CO2 (~200°C – 500°C) has been detected in many samples from Gale Crater where SAM EGA has been performed, and potential sources include combustion of terrestrial organics from SAM, as well as combustion and/or decarboxylation of either indigenous martian or exogenous organic carbon.

J. C. Stern↗

NASA NTRS2004

Novel Biomedical Device Utilizing Light-Emitting Nanostructures Developed

Sketches and chemical diagrams of state-of-the-art device and novel proposed device are presented. Current device uses a diode laser that emits into a fluorescent fluid only one wavelength and a photodetector diode that detects only one wavelength. Only one type of bacteria can be detected. The proposed device uses a quantum dot array that emits into a fluorescent fluid multiple wavelengths and an NIR 512 spectrometer that scans 0.8- to 1.7-mm wavelengths. Hundreds of different bacteria and viruses can be detected. A novel biomedical device is being developed at the NASA Glenn Research Center in cooperation with the University of Michigan. This device uses nano-structured quantum dots that emit light in the near-infrared (IR) region. The nanostructured quantum dots are used as a source and excite fluorochrome polymers coupled with antibodies that seek out and attach to specific bacteria and viruses. The fluorochrome polymers/antibodies fluoresce at specific wavelengths in the near-IR spectrum, but these wavelengths are offset from the excitation wavelength and can be detected with a tunable spectrometer. The device will be used to detect the presence of viruses and bacteria in simple fluids and eventually in more complex fluids, such as blood. Current state-of-the-art devices are limited to single bacteria or virus detection and a considerable amount of time and effort is required to prepare samples for analysis. Most importantly, the devices are quite large and cumbersome, which prohibits them from being used on the International Space Station and the space shuttles. This novel device uses nanostructured quantum dots which, through molecular beam epitaxy and highly selective annealing processes, can be developed into an illumination source that could potentially generate hundreds of specific wavelengths. As a result, this device will be able to excite hundreds of antibody/fluorochrome polymer combinations, which in turn could be used to detect hundreds of bacteria and viruses in fluids. A novel sample preparation technique that exploits micromembrane filtration and centrifugation methods has been developed for this device. The technique greatly reduces the time required to prepare the sample and the amount of sample needed to perform an accurate and comprehensive analysis. Last, and probably most important, because of the nano-light-emitting source and the novel sample preparation technique, the overall size of the device could be reduced dramatically. This device will serve as a nanoscale lab-on-a-chip for in situ microorganism detection and will enable tests to be performed on a time scale of minutes rather than days. Thus, it is ideally suited for monitoring the environmental conditions onboard the International Space Station and the space shuttles, thereby enhancing the safety of the astronauts. In addition, the device has important commercial applications, such as detecting the presence of bacteria and viruses in water at food- and beverage-processing centers, water treatment plants, and restaurants. Also, this technology has the potential to be used to detect bacteria and viruses in more complex fluids, such as blood--which in all likelihood would revolutionize blood analysis as it is performed today. This project was made possible through the Director's Discretionary Fund and is ongoing. In addition, this project provides funding to Dr. Rachel Goldman of the University of Michigan for the research and development of nanostructured quantum dots.

Scardelletti, Maximilian C.↗

DOE OSTI2019

Analysis of surface and seismic sources in dense array data with match field processing and Markov chain Monte Carlo sampling

Not provided.

Geochemistry & Geophysics↗

NASA NTRS2007

A Method to Perform Direct Oxygen Analysis on Lunar Simulants and Other Complex Oxide Materials

An essential requirement for making space travel and long term missions more efficient and affordable to NASA includes finding innovative ways to supply oxygen for life support and propulsion. In this experiment, carrier gas hot extraction was investigated as a possible method for measuring the oxygen from samples of lunar soil simulants before and after oxygen extraction. The determination of oxygen using the R0600 Oxygen Determinator is usually limited to oxides with low oxygen concentrations, but after the manipulation of certain furnace operating parameters such as analysis time and ramp rate, the R0600 was used to determine the oxygen content of high concentration oxides such as Fe 2O3 , Al2O3 , and SiO2.

Santiago-Maldonado, Edgardo↗

DOE OSTI2018

A method for processing the Confidential Carload Waybill Sample for railroad freight analysis

Freight transportation research is often constrained by the availability of appropriate data. Within the context of freight rail research, use of traditional freight datasets present some critical challenges. Aggregating freight data to geographic areas diminishes the ability to perform nuanced analysis. More challenging, the complexity of railroad operations limits the usability of publicly available freight flow data which do not account for which rail company is economically and legally responsible for the movement of the goods or for the contractual arrangements between infrastructure owners and carriers. Finally, detailed data are usually privately owned and not readily-accessible for analysis outside the individual rail companies. As part of their regulatory authority, the Surface Transportation Board has developed the Confidential Carload Waybill Sample, a stratified sample representing 1% to 3% of all rail traffic in the United States for a particular year. While the sample is rich with data, it is limited in spatial information as well as in its implementation in geospatial analysis. This paper introduces a methodology for geospatially enabling the Confidential Carload Waybill Sample which can then be used to generate rail routes based on a topological representation of the U.S. railroad network. As a result, this methodology is applied using two case studies, a freight diversion analysis and transporting hazardous materials.

42 ENGINEERING↗

NASA NTRS1992

A Combined XRD/XRF Instrument for Lunar Resource Assessment

Robotic surface missions to the Moon should be capable of measuring mineral as well as chemical abundances in regolith samples. Although much is already known about the lunar regolith, our data are far from comprehensive. Most of the regolith samples returned to Earth for analysis had lost the upper surface, or it was intermixed with deeper regolith. This upper surface is the part of the regolith most recently exposed to the solar wind; as such it will be important to resource assessment. In addition, it may be far easier to mine and process the uppermost few centimeters of regolith over a broad area than to engage in deep excavation of a smaller area. The most direct means of analyzing the regolith surface will be by studies in situ. In addition, the analysis of the impact-origin regolith surfaces, the Fe-rich glasses of mare pyroclastic deposits, are of resource interest, but are inadequately known; none of the extensive surface-exposed pyroclastic deposits of the Moon have been systematically sampled, although we know something about such deposits from the Apollo 17 site. Because of the potential importance of pyroclastic deposits, methods to quantify glass as well as mineral abundances will be important to resource evaluation. Combined x ray diffraction (XRD) and x ray fluorescence (XRF) analysis will address many resource characterization problems on the Moon. XRF methods are valuable for obtaining full major-element abundances with high precision. Such data, collected in parallel with quantitative mineralogy, permit unambiguous determination of both mineral and chemical abundances where concentrations are high enough to be of resource grade. Collection of both XRD and XRF data from a single sample provides simultaneous chemical and mineralogic information. These data can be used to correlate quantitative chemistry and mineralogy as a set of simultaneous linear equations, the solution of which can lead to full characterization of the sample. The use of Rietveld methods for XRD data analysis can provide a powerful tool for quantitative mineralogy and for obtaining crystallographic data on complex minerals.

Vaniman, D. T.↗

NASA NTRSDate not supplied

Uncertainty Modeling for Mars Ascent Vehicle’s Aerodatabase Development

The design of the Mars Ascent Vehicle - Mars Sample Return (MAV-MSR) trajectories requires an accurate assessment of flight performance. Typically, these trajectories are developed by flight mechanics analysis to meet complex mission requirements and then flight performance assessed through Monte Carlo simulations. Consequently, it is crucial to develop an aerodynamic aerodatabase as an input model for flight mechanics analysis to provide static and dynamic force and moment coefficients under specific flight conditions. The force and moment coefficients in the MAV aerodatabase are determined using the FUN3D computational fluid dynamics solver. Firstly, an overview of the aerodatabase is presented to demonstrate its applicability to trajectory-defined simulations. This effort is followed by an initial attempt to quantify uncertainties in the force and moment coefficients necessary for updating the current aerodatabase. The uncertainty model identifies uncertainty adders and multipliers for coefficient-based forces and moments through a direct comparison between FUN3D and wind tunnel test data from NASA Marshall Space Center's 14x14 inch Trisonic Wind Tunnel. These uncertainties aim to encompass various changes in Mach number, angle of attack, and aerodynamic roll angle.

Uncertainty analysis↗

NASA NTRSDate not supplied

Uncertainty Modeling for Mars Ascent Vehicle’s Aerodynamic Database Development

Uncertainty analysis↗

NASA NTRS1999

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗

NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗

DOE OSTI2020

Nucleation of soot: experimental assessment of the role of polycyclic aromatic hydrocarbon (PAH) dimers

The irreversible dimerization of polycyclic aromatic hydrocarbons (PAHs) – typically pyrene (C 16 H 10 ) dimerization – is widely used in combustion chemistry models to describe the soot particle inception step. This study concerns itself with the detection and identification of dimers of flame-synthesized PAH radicals and closed-shell molecules and an experimental assessment of the role of these PAH dimers for the nucleation of soot. To this end, flame-generated species were extracted from an inverse co-flow flame of ethylene at atmospheric pressure and immediately diluted with excess nitrogen before the mixture was analyzed using flame-sampling tandem mass spectrometry with collision-induced fragmentation. Signal at m/z = 404.157 (C 32 H 20 ) and m/z = 452.157 (C 36 H 20 ) were detected and identified as dimers of closed-shell C 16 H 10 and C 18 H 10 monomers, respectively. A complex between a C 13 H 9 radical and a C 24 H 12 closed-shell PAH was observed at m/z = 465.164 (C 37 H 21 ). However, a rigorous analysis of the flame-sampled mass spectra as a function of the dilution ratio, defined as the ratio of the flow rates of the diluent nitrogen to the sampled gases, indicates that the observed dimers are not flame-born, but are produced in the sampling line. In agreement with theoretical considerations, this paper provides experimental evidence that pyrene dimers cannot be a key intermediate in particle inception at elevated flame temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1986

Airport-Noise Levels and Annoyance Model (ALAMO) user's guide

A guide for the use of the Airport-Noise Level and Annoyance MOdel (ALAMO) at the Langley Research Center computer complex is provided. This document is divided into 5 primary sections, the introduction, the purpose of the model, and an in-depth description of the following subsystems: baseline, noise reduction simulation and track analysis. For each subsystem, the user is provided with a description of architecture, an explanation of subsystem use, sample results, and a case runner's check list. It is assumed that the user is familiar with the operations at the Langley Research Center (LaRC) computer complex, the Network Operating System (NOS 1.4) and CYBER Control Language. Incorporated within the ALAMO model is a census database system called SITE II.

Deloach, R.↗

NASA NTRSDate not supplied

Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗