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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Compositional Measurements of Saturn's Upper Atmosphere and Rings From Cassini INMS: An Extended Analysis of Measurements From Cassini's Grand Finale Orbits

The Cassini spacecraft's final orbits sampled Saturn's atmosphere and returned surprisingly complex mass spectra from the Ion and Neutral Mass Spectrometer (INMS). Signal returned from the instrument included native Saturn species, as expected, as well as a significant amount of signal attributed to vaporized ices and higher mass organics believed to be owing into Saturn's atmosphere from the rings. In this paper, we present an in-depth compositional analysis of the mass spectra returned from Cassini's last few orbits. We use a mass spectral deconvolution algorithm designed specifically to handle the complexities involved with unit resolution spaceflight mass spectrometry data to determine the relative abundance of species detected in the observations. We calculate the downward external flux and mass deposition rates of ring volatile species into Saturn's atmosphere and conclude that during these observations ring material was being deposited into Saturn's equatorial region at a rate on the order of 10(exp 4) kg/s.

Saturn↗
NASA NTRS2022

Compositional Measurements of Saturn's Upper Atmosphere and Rings From Cassini INMS: An Extended Analysis of Measurements From Cassini's Grand Finale Orbits

The Cassini spacecraft's final orbits sampled Saturn's atmosphere and returned surprisingly complex mass spectra from the Ion and Neutral Mass Spectrometer (INMS). Signal returned from the instrument included native Saturn species, as expected, as well as a significant amount of signal attributed to vaporized ices and higher mass organics believed to be flowing into Saturn's atmosphere from the rings. In this paper, we present an in-depth compositional analysis of the mass spectra returned from Cassini's last few orbits. We use a mass spectral deconvolution algorithm designed specifically to handle the complexities involved with unit resolution spaceflight mass spectrometry data to determine the relative abundance of species detected in the observations. We calculate the downward external flux and mass deposition rates of ring volatile species into Saturn's atmosphere and conclude that during these observations ring material was being deposited into Saturn's equatorial region at a rate on the order of 10(exp 4) kg/s.

Saturn↗
NASA NTRSDate not supplied

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗
DOE OSTI2025

Data for Kim et al., "Variations in the optical and molecular composition of dissolved organic matter exported from coastal wetlands"

Knowledge about sources and composition of marsh-derived dissolved organic matter (DOM) is critical for understanding the role of marshes in coastal biogeochemical cycling and the fate of marsh-derived DOM in the ocean. To investigate tidal variability in composition of marsh-derived DOM, Kim et al. examined the optical and molecular characteristics of hourly surface water samples at three tidal creeks in the Chesapeake Bay. Groundwater samples along the terrestrial landscape gradient as well as estuarine water from the adjacent estuary at each site were also collected to help resolve sources of surface water DOM. Samples were collected in summer 2024 at three sites – SWH: Sweet Hall Marsh, GCW: Kirkpatrick Marsh, and GWI: Goodwin Islands – which are part of synoptic sites in the Chesapeake Bay region of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales - Field, Measurements, and Experiments) project. Surface water samples were collected hourly over a 48-hour period at each site. Groundwater and estuarine water samples were collected once. This dataset includes- Surface water depth and salinity- Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) concentrations- Optical indices and relative composition of parallel factor analysis (PARAFAC) components- High resolution mass spectrometry data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

AlphaFold and Structural Mass Spectrometry Enable Interrogations on the Intrinsically Disordered Regions in Cyanobacterial Light-harvesting Complex Phycobilisome

Intrinsically disordered proteins/regions (IDPRs) are a very large and functionally important class of proteins that participate in weak multivalent interactions in protein complexes. They are recalcitrant for interrogations using X-ray crystallography and cryo-EM. The IDPRs observed at the interface of the photosynthetic pigment protein complexes (PPCs) remain much less clear, e.g., the major cyanobacterial light-harvesting complex (PBS) contains an unstructured PB-loop insertion in the phycocyanobilin domain (PB domain) of ApcE (the largest polypeptide in PBS). Here, a joint platform is built to probe such structural domains. This platform is characterized by two-round progressive justifications of in silico models by using the structural mass spectrometry data. First, the AlphaFold-generated 3D structure of the PB domain (containing PB-loop) was justified in the context of PBS. Second, docking the AlphaFold-generated ApcG (a ligand) into the first-step justified structure (a receptor). The final ligand-receptor complex was then subjected to a second-round justification, again, by using unequivocal isotopically-encoded cross-links identified in LC-MS/MS. This work reveals a full-length PB-loop structure modelled in the PBS basal cylinder, free from any spatial conflicts against the other subunits in PBS. The structure of PB domain highlights the close associations of the intrinsically disordered PB-loop with its binding partners in PBS, including ApcG, another IDPR. The PB-loop region involved in the binding of photosystem II (PSII) is also discussed in the context of excitation energy transfer regulation. Finally, this work calls attention to the highly disordered, yet interrogatable interface between the light-harvesting antenna complexes and the reaction centers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Dynamic changes in dissolved organic matter composition in a Mountain Lake under ice cover and relationships to changes in nutrient cycling and phytoplankton community composition

We studied Bear Lake, a sub-alpine oligotrophic lake in Rocky Mountain National Park, Colorado U.S.A, during the winter ice cover period of 2018. Our goal was to understand relationships between biogeochemical processes and the chemical quality of the dissolved organic matter, a major pool of organic carbon in all lakes. The lake exhibited a highly stratified environment with limited light availability, a consistent oxycline at 7 meters, and dilute hydrochemistry. Nutrient concentrations were low and depletion of nitrogen, particularly for NH4 to a lesser extent NO3, were related to increasing phytoplankton abundance. The deep chlorophyll maxima that developed above the oxycline was dominated by a potentially mixotrophic dinoflagellate. DOM chemical quality as measured through high-resolution mass spectrometry was related to these shifts in aquatic ecosystem structure. However, CDOM spectroscopy of the whole water was a poor indicator of biogeochemical changes in the DOM pool. The spectrometry data highlighted an evolving and contrasting reservoir of phosphorus, nitrogen, and sulfur-containing organic compounds sensitive to nutrient cycling and redox conditions. We also observed reduced chemodiversity between the surface and bottom water DOM molecular formulas over time. Homogeneity increased in the surface and more unique compounds were produced in the bottom waters, where an overall increase occurred in the favorability of carbon to support microbial respiration. Our results show dynamic chemical changes in the DOM pool reflect dynamic nutrient cycling under ice cover, potentially driven by mixotrophic growth of the dinoflagellate Gymnodinium sp.

Rue, Garrett↗
DOE OSTI2015

Effects of long-term elevated CO 2 treatment on the inner and outer bark chemistry of sweetgum (Liquidambar styraciflua L.) trees

Long-term exposure of sweetgum trees to elevated atmospheric CO 2 concentrations significantly shifted inner bark (phloem) and outer bark (rhytidome) chemical compositions, having implications for both defense and nutrient cycling. Changes in plant tissue chemistry due to increasing atmospheric carbon dioxide (CO 2 ) concentrations have direct implications for tissue resistance to abiotic and biotic stress while living, and soil nutrient cycling when senesced as litter. Although the effects of elevated CO 2 concentrations on tree foliar chemistry are well documented, the effects on tree bark chemistry are largely unknown. The objective of our study was to determine the effects of a long-term elevated CO 2 treatment on the contents of individual elements, extractives, ash, lignin, and polysaccharide sugars of sweetgum (Liquidambar styraciflua L.) bark. Trees were harvested from sweetgum plots equipped with the Free-Air CO 2 Enrichment (FACE) apparatus, receiving either elevated or ambient CO 2 treatments over a 12-year period. Whole bark sections were partitioned into inner bark (phloem) and outer bark (rhytidome) samples before analysis. Moreover, principal component analysis, coupled with either Fourier transform infrared spectroscopy or pyrolysis-gas chromatography-mass spectrometry data, was also used to screen for differences. Elevated CO 2 reduced the N content (0.42 vs. 0.35 %) and increased the C:N ratio (109 vs. 136 %) of the outer bark. For the inner bark, elevated CO 2 increased the Mn content (470 vs. 815 mg kg -1 ), total extractives (13.0 vs. 15.6 %), and residual ash content (8.1 vs. 10.8 %) as compared to ambient CO 2 ; differences were also observed for some hemicellulosic sugars, but not lignin. Shifts in bark chemistry can affect the success of herbivores and pathogens in living trees, and as litter, bark can affect the biogeochemical cycling of nutrients within the forest floor. Our results demonstrate that increasing atmospheric CO 2 concentrations have the potential to impact the chemistry of temperate, deciduous tree bark such as sweetgum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Kinemage of action - Proposed reaction mechanism of glutamate-1-semialdehyde aminomutase at an atomic level

Highlights: {yields} Inhibitors of tetrapyrrole cofactor biosynthesis may be useful antibiotics. {yields} Mechanism of critical enzyme, glutamate-1-semialdehyde aminomutase, is presented. {yields} Unique vitamin B6-dependant enzyme traps intermediate in active site. {yields} Molecular dynamics show that a re-orientation of the substrate is required. -- Abstract: Glutamate-1-semialdehyde aminomutase (GSAM), a key enzyme in tetrapyrrole cofactor biosynthesis, performs a unique transamination on a single substrate. The substrate, glutamate-1-semialdehyde (GSA), undergoes a reaction that exchanges the position of an amine and a carbonyl group to produce 5-aminolevulinic acid (ALA). This transamination reaction is unique in the fact that is does not require an external cofactor to act as a nitrogen donor or acceptor in this transamination reaction. One of the other remarkable features of the catalytic mechanism is the release free in the enzyme active site of the intermediate 4,5-diaminovaleric acid (DAVA). The action of a gating loop prevents the escape of DAVA from the active site. In a MD simulation approach, using snapshots provided by X-ray crystallography and protein crystal absorption spectrometry data, the individual catalytic steps in this unique intramolecular transamination have been elucidated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2010

Fission Product Yields from Fission Spectrum n+{sup 239}Pu for ENDF/B-VII.1

We describe a new cumulated fission product yield (FPY) evaluation for fission spectrum neutrons on plutonium that updates the ENDF/B-VI evaluation by England and Rider, for the forthcoming ENDF/B-VII.1 database release. We focus on FPs that are needed for high accuracy burnup assessments; that is, for inferring the number of fissions in a neutron environment. Los Alamos conducted an experiment in the 1970s in the Bigten fast critical assembly to determine fission product yields as part of the Interlaboratory Reaction Rate (ILRR) collaboration, and this has defined the Laboratory's fission standard to this day. Our evaluation includes use of the LANL-ILRR measurements (not previously available to evaluators) as well as other Laboratory FPY measurements published in the literature, especially the high-accuracy mass spectrometry data from Maeck and others. Because the measurement database for some of the FPs is small - especially for {sup 99}Mo - we use a meta-analysis that incorporates insights from other accurately-measured benchmark FP data, using R-value ratio measurements. The meta-analysis supports the FP measurements from the LANL-ILRR experiment. Differences between our new evaluations and ENDF/B-VI are small for some FPs (less than 1-2%-relative for {sup 95}Zr, {sup 140}Ba, {sup 144}Ce), but are larger for {sup 99}Mo (4%-relative) and {sup 147}Nd (5%-relative, at 1.5 MeV) respectively. We present evidence for an incident neutron energy dependence to the {sup 147}Nd fission product yield that accounts for observed differences in the FPY at a few-hundred keV average energy in fast reactors versus measurements made at higher average neutron energies in Los Alamos' fast critical assemblies. Accounting for such FPY neutron energy dependencies is important if one wants to reach a goal of determining the number of fissions to accuracies of 1-2%. An evaluation of the energy-dependence of fission product yields is given for all A values based on systematical trends in the measured data, with a focus on the energy dependence over the fast neutron energy range from 0.2-2 MeV. Based on these trends, we present an evaluation of the FPY data at 0.5 and 2.0 MeV average incident neutron energies. This new set of ENDF/B-VII data will enable users to linearly interpolate between the pooled FPY data at {approx}0.5 MeV and our new data at 2 MeV to obtain FPYs at other energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Atmospheric Oxidation of Squalene: Molecular Study Using COBRA Modeling and High-Resolution Mass Spectrometry

Squalene is a major component of skin and plant surface lipids, and is known to be present at high concentrations in indoor dust. Its high reactivity toward ozone makes it an important ozone sink and a natural protectant against atmospheric oxidizing agents. While the volatile products of squalene ozonolysis are known, the condensed-phase products have not been characterized. We present an analysis of condensed-phase products resulting from an extensive oxidation of squalene by ozone probed by electrospray ionization (ESI) high-resolution mass spectrometry (HR-MS). A complex distribution of nearly 1,300 peaks assignable to molecular formulas is observed in direct infusion positive ion mode ESI mass spectra. The distribution of peaks in the mass spectra suggests that there are extensive cross-coupling reactions between hydroxy-carbonyl products of squalene ozonolysis. To get additional insights into the mechanism, we apply a Computational Brewing Application (COBRA) to simulate the oxidation of squalene in the presence of ozone, and compare predicted results with those observed by the HR-MS experiments. The system predicts over one billion molecular structures between 0-1450 Da, which correspond to about 27,000 distinct elemental formulas. Over 83% of the squalene oxidation products inferred from the mass spectrometry data are matched by the simulation. Simulation indicates a prevalence of peroxy groups, with hydroxyl and ether groups being the second-most important O-containing functional groups formed during squalene oxidation. These highly oxidized products of squalene ozonolysis may accumulate on indoor dust and surfaces, and contribute to their redox capacity.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2025

Sources and Composition of Organic Aerosols in the Central Arctic during Spring and Summer

Organic aerosols (OA) are a major component of Arctic aerosol mass and influence the region’s radiation budget, yet their sources and physicochemical properties remain largely unknown. We investigate OA sources and climate-relevant characteristics over the central Arctic Ocean in spring and summer, by applying positive matrix factorization to aerosol mass spectrometry data from two ship-based expeditions (2018 and 2020), complemented by total and interstitial aerosol measurements during fog periods. Six distinct OA factors were identified: haze-related OA, Arctic oxygenated OA, two mixed-OA types resembling biomass burning and primary marine OA linked to warm-air intrusions, marine OA, and hydrocarbon-related OA. Seasonal transitions strongly shaped OA composition. Following polar sunrise, highly oxygenated OA, likely formed secondarily from photo-oxidized volatile organic compounds, became dominant. After the polar vortex collapsed in May, episodic spikes in marine OA from the marginal ice zone appeared, alongside a reduced influence from Eurasian anthropogenic sources. These transitions influenced OA oxidation state and related properties including volatility, acidity, and hygroscopicity, highlighting the role of the Arctic spring atmosphere as an active photochemical reactor. Overall, OA was highly oxidized, with particles activated in fog during summer showing even greater oxidation, suggesting that central Arctic OA can be highly cloud active.

Arctic haze↗
DOE OSTI2020

Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line

Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs but attempts to combine different algorithms and optimize them on large datasets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in identification of 540 SAAVs in the mass spectrometry data, the most comprehensive coverage yet reported. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53 and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling

Abstract Metabolite identification in non-targeted mass spectrometry-based metabolomics remains a major challenge due to limited spectral library coverage and difficulties in predicting metabolite fragmentation patterns. Here, we introduce Multiplexed Chemical Metabolomics (MCheM), which employs orthogonal post-column derivatization reactions integrated into a unified mass spectrometry data framework. MCheM generates orthogonal structural information that substantially improves metabolite annotation through in silico spectrum matching and open-modification searches, offering a powerful new toolbox for the structure elucidation of unknown metabolites at scale.

Science & Technology - Other Topics↗
DOE OSTI2026

ENVnet provides a global molecular resource of dissolved organic matter

Dissolved organic matter (DOM) is an important component of Earth's carbon cycle and one of the planet's most chemically diverse pools, yet the molecular structures of its constituents remain largely unresolved. This limitation has hindered our ability to link DOM composition to microbial processes and ecosystem function. Here we present ENVnet, a global molecular repository built from tandem mass spectrometry data collected across 13 terrestrial and aquatic environment types, including 419 newly generated samples that expand publicly available DOM metabolomics data and cover previously underrepresented environments. By computationally deconvolving chimeric mass spectra, a longstanding challenge in environmental metabolomics, we recover high-quality fragmentation data for >22,000 distinct molecular features (defined by a specific precursor mass and fragmentation pattern). Using ENVnet, we uncover conserved and environment-specific molecular patterns in DOM composition and underlying biogeochemical processes. We also use molecular features encoded in ENVnet to train predictive models of DOM persistence, allowing molecular-level assessment of microbial turnover in independent systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Random forest models accurately classify synthetic opioids using high-dimensionality mass spectrometry datasets

Detection of novel threat agents presents several challenges, a principle one being the development of untargeted methods to screen an increasing number of threat chemicals whose exact structures are unknown. With the use of Machine Learning (ML) tools, we can guide the development of analytical methods for broad-spectrum detection of unbounded threat chemical families in complex mixtures. Toward this goal, we used nominal mass and high-resolution mass spectrometry data for hundreds of synthetic opioids and non-opioid compounds. We tested two ML techniques, logistic regression and random forest, to develop models towards a practical, implementable method for opioid detection. We found that of these tested ML methods, random forest models resulted in the highest validation accuracy (95+%) for both nominal mass and high-resolution classification of opioids versus non-opioids, with low false positive and false negative rates. The RF models were then used to successfully predict the classification of 10 compounds—five opioids and five non-opioids not part of the training and validation analysis. This application of ML is a critical step towards the development of field-deployable nominal mass spectrometers with ML-driven analyses for classification of emergent threats.

Chemistry↗
DOE OSTI2015

High temperature annealing effects on deep-level defects in a high purity semi-insulating 4H-SiC substrate

Effects of high-temperature annealing on deep-level defects in a high-purity semi-insulating 4H silicon carbide substrate have been studied by employing current-voltage, capacitance-voltage, junction spectroscopy, and chemical impurity analysis measurements. Secondary ion mass spectrometry data reveal that the substrate contains boron with concentration in the mid 10{sup 15 }cm{sup −3} range, while other impurities including nitrogen, aluminum, titanium, vanadium and chromium are below their detection limits (typically ∼10{sup 14 }cm{sup −3}). Schottky barrier diodes fabricated on substrates annealed at 1400–1700 °C exhibit metal/p-type semiconductor behavior with a current rectification of up to 8 orders of magnitude at bias voltages of ±3 V. With increasing annealing temperature, the series resistance of the Schottky barrier diodes decreases, and the net acceptor concentration in the substrates increases approaching the chemical boron content. Admittance spectroscopy results unveil the presence of shallow boron acceptors and deep-level defects with levels in lower half of the bandgap. After the 1400 °C annealing, the boron acceptor still remains strongly compensated at room temperature by deep donor-like levels located close to mid-gap. However, the latter decrease in concentration with increasing annealing temperature and after 1700 °C, the boron acceptor is essentially uncompensated. Hence, the deep donors are decisive for the semi-insulating properties of the substrates, and their thermal evolution limits the thermal budget for device processing. The origin of the deep donors is not well-established, but substantial evidence supporting an assignment to carbon vacancies is presented.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The solar wind neon abundance observed with ACE/SWICS and ULYSSES/SWICS

Using in situ ion spectrometry data from ACE/SWICS, we determine the solar wind Ne/O elemental abundance ratio and examine its dependence on wind speed and evolution with the solar cycle. We find that Ne/O is inversely correlated with wind speed, is nearly constant in the fast wind, and correlates strongly with solar activity in the slow wind. In fast wind streams with speeds above 600 km s{sup –1}, we find Ne/O = 0.10 ± 0.02, in good agreement with the extensive polar observations by Ulysses/SWICS. In slow wind streams with speeds below 400 km s{sup –1}, Ne/O ranges from a low of 0.12 ± 0.02 at solar maximum to a high of 0.17 ± 0.03 at solar minimum. These measurements place new and significant empirical constraints on the fractionation mechanisms governing solar wind composition and have implications for the coronal and photospheric abundances of neon and oxygen. The results are made possible by a new data analysis method that robustly identifies rare elements in the measured ion spectra. The method is also applied to Ulysses/SWICS data, which confirms the ACE observations and extends our view of solar wind neon into the three-dimensional heliosphere.

79 ASTRONOMY AND ASTROPHYSICS↗