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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Growth of GaP1 − x − yAsyNx on Si substrates by chemical beam epitaxy

Chemical beam epitaxy has been used to grow layers of GaP1 − xNx, GaP1 − yAsy, and nearly lattice-matched layers GaP1 − x − yAsyNx on Si substrates. To address the issue of antiphase domain generation associated with the growth of polar semiconductors on Si, misoriented Si(001) substrates have been used combined with a carefully designed GaP buffer layer growth. The reflection high-energy electron diffraction pattern exhibits a (2 × 4) surface reconstruction after GaP buffer layer and GaP(As,N) graded layer growth, indicating the good surface quality and planarity of the grown layers. Sample composition was obtained by simultaneous acquisition of Rutherford backscattering spectrometry and nuclear reaction analysis, indicating a linear dependence of N and As mole fractions on the flux of their respective precursor. GaP1 − x − yAsyNx layers grown on Si substrates have a lattice mismatch not larger than ±0.005 for N contents in the range 0.02 < x < 0.05. High-resolution X-ray diffraction reciprocal space maps demonstrate a good crystalline quality. Intense photoluminescence spectra have been measured in all GaP1 − xNx and GaP1 − x − yAsyNx layers, as it is expected for direct bandgap materials. Two wide overlapped emission peaks are observed in all the spectra, most likely related to near bandgap recombination. The position of the higher energy peak for GaP1 − xNx and GaP1 − x − yAsyNx layers has been compared to bandgap energy calculations using the band anticrossing model, showing good agreement.

Ben Saddik, K.↗
DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗
NASA NTRS1983

Organic molecules as chemical fossils - The molecular fossil record

The study of biochemical clues to the early earth and the origin of life is discussed. The methods used in such investigation are described, including the extraction, fractionation, and analysis of geolipids and the analysis of kerogen. The occurrence of molecular fossils in the geological record is examined, discussing proposed precursor-product relationships and the molecular assessment of deep sea sediments, ancient sediments, and crude petroleums. Alterations in the molecular record due to diagenesis and catagenesis are considered, and the use of microbial lipids as molecular fossils is discussed. The results of searches for molecular fossils in Precambrian sediments are assessed.

Eglinton, G.↗
NASA NTRS2005

Synthesis, Characterization and Decomposition Studies of Tris(N,N-dibenzyldithiocarbamato) Indium(III): Chemical Spray Deposition of Polycrystalline CuInS2 on Copper Films

Tris(bis(phenylmethyl)carbamodithioato-S,S ), commonly referred to as tris(N,Ndibenzyldithiocarbamato) indium(III), In(S2CNBz2)3, was synthesized and characterized by single crystal X-ray crystallography. The compound crystallizes in the triclinic space group P1 bar with two molecules per unit cell. The material was further characterized using a novel analytical system employing the combined powers of thermogravimetric analysis, gas chromatography/mass spectrometry and Fourier-Transform infrared spectroscopy to investigate its potential use as a precursor for the chemical vapor deposition (CVD) of thin film materials for photovoltaic applications. Upon heating, the material thermally decomposes to release CS2 and benzyl moieties in to the gas phase, resulting in bulk In2S3. Preliminary spray CVD experiments indicate that In(S2CNBz2)3 decomposed on a Cu substrate reacts to produce stoichiometric CuInS2 films.

Hehemann, David G.↗
DOE OSTI2021

COUPLED GRIFFIN AND PRONGHORN SIMULATION OF THE MOLTEN SALT FAST REACTOR (MSFR) FOR THE VIRTUAL TEST BED

The Virtual Test Bed (VTB) repository hosts a wide range of challenge problems to showcase modeling and simulation capabilities to support advanced reactor demonstration. An overview of a coupled multiphysics model for Molten Salt Reactors (MSR) is presented here. The analysis leverages MOOSE-based tools (notably Griffin and Pronghorn) for neutronic and thermal hydraulic simulation. Neutron precursor drifting capability is showcased, along with some initial turbulence models. Both steady-state and transient coupled multiphysics results for an MSR concept are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Exploring the fragmentation efficiency of proteins analyzed by MALDI-TOF-TOF tandem mass spectrometry using computational and statistical analyses

Matrix-assisted laser desorption/ionization time-of-flight-time-of-flight (MALDI-TOF-TOF) tandem mass spectrometry (MS/MS) is a rapid technique for identifying intact proteins from unfractionated mixtures by top-down proteomic analysis. MS/MS allows isolation of specific intact protein ions prior to fragmentation, allowing fragment ion attribution to a specific precursor ion. However, the fragmentation efficiency of mature, intact protein ions by MS/MS post-source decay (PSD) varies widely, and the biochemical and structural factors of the protein that contribute to it are poorly understood. With the advent of protein structure prediction algorithms such as Alphafold2, we have wider access to protein structures for which no crystal structure exists. In this work, we use a statistical approach to explore the properties of bacterial proteins that can affect their gas phase dissociation via PSD. We extract various protein properties from Alphafold2 predictions and analyze their effect on fragmentation efficiency. Our results show that the fragmentation efficiency from cleavage of the polypeptide backbone on the C-terminal side of glutamic acid (E) and asparagine (N) residues were nearly equal. In addition, we found that the rearrangement and cleavage on the C-terminal side of aspartic acid (D) residues that result from the aspartic acid effect (AAE) were higher than for E- and N-residues. From residue interaction network analysis, we identified several local centrality measures and discussed their implications regarding the AAE. We also confirmed the selective cleavage of the backbone at D-proline bonds in proteins and further extend it to N-proline bonds. Finally, we note an enhancement of the AAE mechanism when the residue on the C-terminal side of D-, E- and N-residues is glycine. To the best of our knowledge, this is the first report of this phenomenon. Our study demonstrates the value of using statistical analyses of protein sequences and their predicted structures to better understand the fragmentation of the intact protein ions in the gas phase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Transcriptomic Analysis Reveals Novel Regulators of the Scots Pine Stilbene Pathway

Stilbenes accumulate in Scots pine heartwood where they have important roles in protecting wood from decaying fungi. They are also part of active defense responses, and their production is induced by different (a)biotic stressors. The specific transcriptional regulators as well as the enzyme responsible for activating the stilbene precursor cinnamate in the pathway are still unknown. UV-C radiation was the first discovered artificial stress activator of the pathway. Here, we describe a large-scale transcriptomic analysis of pine needles in response to UV-C and treatment with translational inhibitors, both activating the transcription of stilbene pathway genes. We used the data to identify putative candidates for the missing CoA ligase and for pathway regulators. We further showed that the pathway is transcriptionally activated by phosphatase inhibitor, ethylene and jasmonate treatments, as in grapevine, and that the stilbene synthase promoter retains its inducibility in some of the tested conditions in Arabidopsis, a species that normally does not synthesize stilbenes. Shared features between gymnosperm and angiosperm regulation and partially retained inducibility in Arabidopsis suggest that pathway regulation occurs not only via ancient stress-response pathway(s) but also via species-specific regulators. Understanding which genes control the biosynthesis of stilbenes in Scots pine aids breeding of more resistant trees.

4-Coumarate-CoA ligase↗
DOE OSTI2023

Toward a tunable fabrication of multifunctional iron-aluminum spinels via solution combustion synthesis: The effects of fuel, heating mode, and Fe:Al precursor ratio

The solid solutions of iron and aluminum spinels (hercynite, maghemite, magnetite, and γ-alumina) are promising materials for emerging technologies such as solar thermochemical fuel production and clean dehydrogenation of fossil fuels. Solution combustion synthesis (SCS) is an attractive technique for the fabrication of these materials as it has been used for synthesis of many nanoscale oxides. However, the design space of SCS is large with many synthesis parameters affecting the properties of the combustion products. To optimize the SCS of these materials, it is important to determine which parameters yield the best properties. In the present work, FeAlO x nanocomposites were obtained by SCS using iron nitrate and aluminum nitrate as precursors and oxidizers. Two fuels (citric acid and glycine), three Fe:Al molar ratios (1:2, 1:1, and 2:1) in the precursors, and three heating modes (hotplate, muffle furnace, and microwave oven) were compared. The products were characterized by X-ray diffraction analysis, scanning electron microscopy, Brunauer-Emmett-Teller surface area analysis, and laser diffraction particle size analysis. The fuel used had the largest impact on the combustion behavior and hence the material properties. The high combustion temperature of glycine allowed for the formation of an FeAl 2 O 4 /Fe 3 O 4 solid solution, while the lower-temperature combustion of citric acid yielded Al-substituted γ-Fe 2 O 3 with high amorphous content. With citric acid, the specific surface area as high as 200 m 2 /g was achieved. The effect of Fe:Al precursor ratio was clearly seen in variations of the lattice parameter, which demonstrated the ability to tune the phase composition. The heating mode had minor effects on material properties, but some differences were observed. As a result, all products obtained by SCS in a microwave oven had low specific surface areas compared to those obtained with a hotplate and a muffle furnace.

Alumina↗
DOE OSTI2018

Rapidly Assessing the Quality of Targeted Proteomics Experiments through Monitoring Stable-Isotope Labeled Standards

Selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), is a data acquisition technique used in targeted analysis of molecules, including targeted proteomic studies. It exploits the unique capability of triple-quadrupole (QQQ) mass spectrometers to monitor the predefined precursor and fragment ion pairs of specific molecules of interest throughout a liquid chromatography (LC) elution profile. Compared to shotgun proteomics, targeted proteomics using SRM has high selectivity, high sensitivity, and a wide linear dynamic range,(1-3) which makes it especially useful in the accurate and reproducible quantification of low-abundance proteins in highly complex biological samples. SRM has been widely used in the fields of biomarker discovery,(4-7) analysis of protein post-translational modifications(8) and characterization of biological protein networks.(4,9) In the recent years, multiple technical advances have greatly improved the throughput of SRM analyses, allowing for the quantification of hundreds of peptides in a single analysis.(6,7,10) For example, a single 800-plex SRM assay (e.g., 400 unlabeled and heavy-labeled peptide pairs and 2400 transitions with retention time scheduling) using ultrahigh-performance liquid chromatography (UHPLC) has been developed to quantify proteins in plasma.(11) Advanced labeling techniques utilizing in vitro proteome-assisted MRM for protein absolute quantification (iMPAQT) demonstrated the capability of SRM in genome-wide protein quantification of over 18?000 human proteins.(12) Moreover, the scan speed of QQQ instrumentation has been greatly improved in recent releases of commercial instrumentation. The newly developed TSQ Altis (released in 2017) can scan more than 600 transitions per second, which is 6 times more than a traditional QQQ scan speed of 100 transitions per second. The breadth of measurement enabled by these technological improvements to QQQ mass spectrometry has increased the feasibility and popularity of large scale targeted proteomics studies,(13) a major application of which will be in clinical studies in which up to hundreds of protein candidates need to be quantified in hundreds of clinical specimens.(14) Quantitative accuracy is a primary motivating factor for utilizing a targeted proteomics protocol. The precise and reproducible absolute quantification produced by SRM assays is essential to many clinical and laboratory experiments.(15,16) Because the abundance of an endogenous peptide is calculated from the measurement of the spiked-in reference standard, it is essential to assess the data quality of these references.(17) In early applications of targeted proteomics, when instrument speed greatly limited the number of transitions that could be monitored, much of this quality assessment was done manually. However, recent improvements in instrument performance and experimental design have enabled a dramatic increase in the number of target peptides and associated SRM transitions, which makes manual quality assessment an untenable and laborious task. A variety of computational tools assist in SRM experiment design and data analysis. The first task in creating an SRM experiment is the choice of proteins and representative peptides to monitor. Achieving a reliable protein abundance requires appropriately choosing peptides that have a strong signal and are free from interferences in the biological matrix. Numerous computational tools exist to facilitate assay design by identifying peptides and refining SRM transitions.(18-21) To help share these assays and eliminate time spent designing the same transitions at multiple institutions, community portals have begun to host well-designed and vetted assays.(22-24) Analyzing the experimental data requires significant computational effort to align files across replicates and experimental conditions, pick peaks and produce quantitative values, normalize data and perform statistical tests, etc.(25-27)

Gibbons, Bryson C.↗
NASA NTRSDate not supplied

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗
DOE OSTI2021

Equatorial waves triggering extreme rainfall and floods in southwest Sulawesi, Indonesia

On the basis of detailed analysis of a case study and long-term climatology, it is shown that equatorial waves and their interactions serve as precursors for extreme rain and flood events in the central Maritime Continent region of southwest Sulawesi, Indonesia. Meteorological conditions on January 22, 2019, leading to heavy rainfall and devastating flooding in this area were studied. It is shown that a convectively coupled Kelvin wave (CCKW) and a convectively coupled Rossby wave (CCERW) embedded within the larger-scale envelope of the Madden-Julian Oscillation (MJO) enhanced convective phase, contributed to the onset of a mesoscale convective system which developed over the Java Sea. Low-Level convergence from the CCKW forced mesoscale convective organization and orographic ascent of moist air over the slopes of southwest Sulawesi. Climatological analysis shows that 92 % of December-January-February floods and 76% of extreme rain events in this region were immediately preceded by positive low-level westerly wind anomalies. It is estimated that both CCKWs and CCERWs propagating over Sulawesi double the chance of floods and extreme rain event development, which the probability of such hazardous events occurring during their combined activity is eight times greater than on a random day. While the MJO is a key component shaping tropical atmospheric variability, it is shown that its usefulness as a single factor for extreme weather-driven hazard prediction is limited.

Latos, Beata↗
DOE OSTI2024

Laser-Induced Thermal Decomposition of Uranium Coordination Compounds with Non-oxidic Ligands to Produce Nitride and Carbide Materials

The production of ceramics from uranium coordination compounds can be achieved through thermal processing if an excess amount of the desired atoms (i.e., C or N), or reactive gaseous products (e.g., methane or nitrogen oxide) is made available to the reactive uranium metal core via decomposition/fragmentation of the surrounding ligand groups. Here, computational thermodynamic approaches were utilized to identify the temperatures necessary to produce uranium metal from some starting compounds—UI 4 (TMEDA) 2 , UCl 4 (TMEDA) 2 , UCl 3 (pyridine) x , and UI 3 (pyridine) 4 . Experimentally, precursors were irradiated by a laser under various gaseous environments (argon, nitrogen, and methane) creating extreme reaction conditions (i.e., fast heating, high temperature profile >2000 °C, and rapid cooling). Despite the fast dynamics associated with laser irradiation, the central uranium atom reacted with the thermal decomposition products of the ligands yielding uranium ceramics. Residual gas analysis identified vaporized products from the laser irradiation, and the final ceramic products were characterized by powder X-ray diffraction. The composition of the uranium precursor as well as the gaseous environment had a direct impact on the production of the final phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Recyclability of reversible polymer networks over a Dozen reprocessing cycles

Reversible polymer networks capable of reversible reactions along their backbone provide a promising strategy for addressing waste management challenges associated with conventional thermoset products. However, reversible polymer networks cannot be recycled infinitely. Unavoidable side reactions eventually cause significant degradation of mechanical properties or loss of recyclability. This study aims to answer a simple yet critical question on reversible polymer network systems: how many reprocessing cycles can be achieved before profound mechanical degradation or a loss of recyclability? The recyclability of Diels–Alder (DA) network samples was evaluated by repeating consistent reprocessing cycles until they were no longer reprocessable. To enhance their recyclability, the chemical structure of the maleimide precursor was tailored to mitigating side reactions by maleimide homopolymerization. Remarkably, by employing a maleimide precursor with alkyl substitutions on its phenyl group, the DA network system attained 12 reprocessing cycles using injection molding at 160 °C without significant degradation of mechanical properties. However, the 13th reprocessing cycle did not succeed. Rheological analysis revealed the accumulation of non-reversible bonds within the network structure during repeated reprocessing, despite fairly consistent mechanical properties under operating conditions. This study demonstrates that the rational design of the maleimide precursor is an effective means to enhance the reprocessability of DA networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine learning assisted phase and size-controlled synthesis of iron oxide particles

Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

PEDOT:PSS-based Multilayer Bacterial-Composite Films for Bioelectronics

Abstract Microbial electrochemical systems provide an environmentally-friendly means of energy conversion between chemical and electrical forms, with applications in wastewater treatment, bioelectronics, and biosensing. However, a major challenge to further development, miniaturization, and deployment of bioelectronics and biosensors is the limited thickness of biofilms, necessitating large anodes to achieve sufficient signal-to-noise ratios. Here we demonstrate a method for embedding an electroactive bacterium, Shewanella oneidensis MR-1, inside a conductive three-dimensional poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) matrix electropolymerized on a carbon felt substrate, which we call a multilayer conductive bacterial-composite film (MCBF). By mixing the bacteria with the PEDOT:PSS precursor in a flow-through method, we maintain over 90% viability of S. oneidensis during encapsulation. Microscopic analysis of the MCBFs reveal a tightly interleaved structure of bacteria and conductive PEDOT:PSS up to 80 µm thick. Electrochemical experiments indicate S. oneidensis in MCBFs can perform both direct and riboflavin-mediated electron transfer to PEDOT:PSS. When used in bioelectrochemical reactors, the MCBFs produce 20 times more steady-state current than native biofilms grown on unmodified carbon felt. This versatile approach to control the thickness of bacterial composite films and increase their current output has immediate applications in microbial electrochemical systems, including field-deployable environmental sensing and direct integration of microorganisms into miniaturized organic electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Source Characterization of Volatile Organic Compounds at Carlsbad Caverns National Park

Carlsbad Caverns National Park (CAVE), located in southeastern New Mexico, experiences elevated ground-level ozone (O 3 ) exceeding the National Ambient Air Quality Standard (NAAQS) of 70 ppbv. It is situated adjacent to the Permian Basin, one of the largest oil and gas (O&G) producing regions in the US. In 2019, the Carlsbad Caverns Air Quality Study (CarCavAQS) was conducted to examine impacts of different sources on ozone precursors, including nitrogen oxides (NO x ) and volatile organic compounds (VOCs). Here, we use positive matrix factorization (PMF) analysis of speciated VOCs to characterize VOC sources at CAVE during the study. Seven factors were identified. Three factors composed largely of alkanes and aromatics with different lifetimes were attributed to O&G development and production activities. VOCs in these factors were typical of those emitted by O&G operations. Associated residence time analyses (RTA) indicated their contributions increased in the park during periods of transport from the Permian Basin. These O&G factors were the largest contributor to VOC reactivity with hydroxyl radicals (62%). Two PMF factors were rich in photochemically generated secondary VOCs; one factor contained species with shorter atmospheric lifetimes and one with species with longer lifetimes. RTA of the secondary factors suggested impacts of O&G emissions from regions farther upwind, such as Eagle Ford Shale and Barnett Shale formations. The last two factors were attributed to alkenes likely emitted from vehicles or other combustion sources in the Permian Basin and regional background VOCs, respectively.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

NASAs Evolvable Mars Campaign: Mars Moons Robotic Precursor

Human exploration missions to the moons of Mars are being considered within NASA's Evolvable Mars Campaign (EMC) as an intermediate step for eventual human exploration and pioneering of the surface of Mars. A range of mission architectures is being evaluated in which human crews would explore one or both moons for as little as 14 days or for as long as 500 days with a variety of orbital and surface habitation and mobility options being considered. Relatively little is known about the orbital, surface, or subsurface characteristics of either moon. This makes them interesting but challenging destinations for human exploration missions during which crewmembers must be able to effectively conduct scientific exploration without being exposed to undue risks due to radiation, dust, micrometeoroids, or other hazards. A robotic precursor mission to one or both moons will be required to provide data necessary for the design and operation of subsequent human systems and for the identification and prioritization of scientific exploration objectives. This paper identifies and discusses considerations for the design of such a precursor mission based on current human mission architectures. Objectives of a Mars' moon precursor in support of human missions are expected to include: 1) identifying hazards on the surface and the orbital environment at up to 50-km distant retrograde orbits; 2) collecting data on physical characteristics for planning of detailed human proximity and surface operations; 3) performing remote sensing and in situ science investigations to refine and focus future human scientific activities; and 4) prospecting for in situ resource utilization. These precursor objectives can be met through a combination or remote sensing (orbital) and in-situ (surface) measurements. Analysis of spacecraft downlink signals using radio science techniques would measure the moon's mass, mass distribution, and gravity field, which will be necessary to enable trajectory planning. Laser altimetry would precisely measure the moon's shape and improve the accuracy of radio science measurements. A telescopic imaging camera would map the moon at submeter resolution and photograph selected areas of interest at subcentimeter resolution and a visible and near-infrared (0.4-3.0 mm) imaging spectrograph would produce a global map of mineral composition variations at a resolution of tens of meters and maps of selected areas of interest at meter resolution. Additional remote sensing capabilities could include a thermal infrared imager (heat flow, thermal inertia, and grain size distributions), a gamma-ray and neutron detector (atomic composition), a ground-penetrating radar (internal structure), and a magnetometer and Langmuir probe (magnetic properties and plasma field). Once on the surface of Phobos or Deimos, necessary instrumentation would include a penetrometer (regolith compressive strength), a motion-imagery camera (to observe the penetrometer tests before, during, and after contact), a dust-adhesion witness plate and camera (dust levitation), a microimager (dust particle sizes and shapes), and an alpha-proton-X-ray, X-ray fluorescence, Mossbauer, or Raman spectrometer (atomic and mineral composition of surface materials) and an optional temperature probe (regolith thermal properties). A variety of robotic mission design options to enable both orbital and surface measurements are being considered that include fully integrated and modular approaches. In-situ measurements from at least one surface location would be required, with additional measurement locations possible through use of multiple landers, through propulsive relocation of a single lander, or through electromechanical surface translation by a walking or hopping lander vehicle, which could also serve to evaluate such mobility capabilities for subsequent human missions. Preliminary orbital analysis suggests that remote sensing would likely be performed while in a distant retrograde orbit around the target moon. Mission design options to enable characterization of both Mars’ moons in a single mission are also being studied.

Gernhardt, Michael L.↗
DOE OSTI2016

Lead free CH{sub 3}NH{sub 3}SnI{sub 3} perovskite thin-film with p-type semiconducting nature and metal-like conductivity

Lead free CH{sub 3}NH{sub 3}SnI{sub 3} perovskite thin film was prepared by low temperature solution processing and characterized using current sensing atomic force microscopy (CS-AFM). Analysis of electrical, optical, and optoelectrical properties reveals unique p-type semiconducting nature and metal like conductivity of this material. CH{sub 3}NH{sub 3}SnI{sub 3} film also showed a strong absorption in visible and near infrared spectrum with absorption onset of 1.3 eV. X-ray Diffraction analysis and scanning electron microscopy (SEM) confirmed a structure of this compound and uniform film formation. The morphology, film uniformity, light harvesting and electrical properties strongly depend on preparation method and precursor solution. CH{sub 3}NH{sub 3}SnI{sub 3} films prepared based on dimethylformamide (DMF) showed higher crystallinity and light harvesting capability compared to the film based on combination of dimethyl sulfoxide (DMSO) with gamma-butyrolactone (GBL). Local photocurrent mapping analysis showed that CH{sub 3}NH{sub 3}SnI{sub 3} can be used as an active layer and have a potential to fabricate lead free photovoltaic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗