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ISS External Microorganisms: Collecting Planetary Protection Samples During Extravehicular Activity

We have developed, tested, and flown a caddy capable of collecting aseptic samples from external surfaces of the ISS (International Space Station). The sampling caddy is certified for use during US EVA (extra vehicular activity) and was launched to ISS in the summer of 2023. We are scheduled to collect samples from 6 locations outside ISS during an EVA in May of 2024. We will freeze these samples at -80°C on orbit and return them to Earth. We will then extract and sequence any DNA collected during the EVA using next generation sequencing technologies to characterize the community composition and function of each sample. Measuring the type and quantity of microbes present on the exterior of ISS will allow us to address knowledge gap 2B, “Acceptable levels of microbial/organic releases from humans and support systems” described in a 2019 COSPAR report. Collecting data about microbial release from current crewed vehicles will inform requirements for acceptable leak rates for future crewed missions to Mars. The sampling kit consists of eight commercially available, sterile, DNA free, macrofoam swabs ( 23 mm. diameter ) installed in custom aluminum end effectors. Each end effector is housed in and individual aluminum canister. Each canister contains a 0.2 μm Teflon filter to allow the interior volume to accommodate pressure changes without permitting microbial contaminants to enter the sterile interior volume. A handle repurposed from the space shuttle tile repair kit is used to remove the end effector from the sample canister, collect a sample by swabbing a surface and then replace the end effector in its canister. The canisters and end effectors were cleaned and assembled on Earth. Prior to installing the sterile swab the canisters and end effectors were sterilized in an autoclave at 134°C, 215 kPA, for 7 min.. The final assembly occurred in a sterilized class II biosafety cabinet. We will collect six samples from the 1) airlock vestibule, 2) airlock thermal cover, 3) a gap in the micrometeorite shielding near the airlock, 4) a handrail near the airlock, 5) the CDRA (Carbon Dioxide Removal Assembly) vent, and 6) the VES (Vacuum Exhaust System) vent. The remaining two swabs will be reserved as controls. One swab will be exposed during the EVA without touching any surfaces to act as a blank. The final swab will remain sealed until the entire sampling kit is returned to earth. Based on previously published results from the Russian segment, we hypothesize that there will be detectable microbes at some or all of these locations. Ground-based testing of this sampling caddy confirms that the swabs remain sterile as the canisters transition in and out of vacuum. We were able to retrieve, viable bacterial and fungal cells as well as DNA from samples collected from US space suits during vacuum chamber tests lasting as long as seven hours. Based on these results and feedback from the test subjects the sampling caddy was modified to improve ergonomics and meet US EVA safety requirements. Bayonet probes were added to the sides of the sample kit as alternate mounting points. Additional locking features were added to the end effector and the filter stack to prevent inadvertent release during use. The opening mechanism was changed from one where the end effector was rocked laterally to defeat a ball detent to a twist-to-open threaded closure for similar reasons. Demonstrating, this sampling caddy’s effectiveness during a US EVA will allow us to address knowledge gaps identified in COSPAR reports and begin to define planetary protection requirements for life support systems on crewed missions to mars. This kit could also be used to collect contamination control samples during Artemis missions to verify requirements and could be easily modified for robotic sample collection.

Planetary Protection↗
DOE OSTI2019

Microbial Diversity in the Deep Sandstones of a Carbon Sequestration Well

A lack of data on microbes in the deep subsurface hinders our ability to predict how these microbial communities will respond to carbon sequestration. Previous studies predicted how microbial communities may shift due to an influx of carbon dioxide (CO2) by 1) examining waters with naturally-occurring elevated CO2 concentration; and/or 2) via experiments involving exposure of laboratory microbial strains to elevated concentrations of CO2 relative to their native subsurface environment. To identify microbes naturally found in carbon sequestration target reservoirs, water samples were collected from three potential target reservoirs in the Powder River Basin, Wyoming which include the Hulett, Lakota, and Minnelusa sandstones. Water samples were collected at depths of 8,060 ft (Lakota), 8,330 ft (Hulett), 9,380 ft (Minnelusa), 9,463 ft (Minnelusa), and 9,544 ft (Minnelusa) for microbial DNA analysis as well as water chemistry and stable isotope analyses to look for any microbial trends that could be related to water chemistry alone. Identification of microbial communities present in the sampled water was determined via 16S rRNA sequencing; these data were compared to 16S rRNA isolated from drilling mud to distinguish native from any microbes introduced via drilling processes. Enrichment experiments reveal that the collected water samples contain active (e.g., growing) microbes and how the microbial community may adapt upon the introduction of CO2.

Wawrousek, K↗
DOE OSTI2021

Mapping glyceride species in biodiesel by high-temperature gas chromatography combined with chemical ionization mass spectrometry.

Accurate and comprehensive identification of residual glycerides in biodiesel is an important part of the fuel characterization, due to the impact of glycerides on the fuel physicochemical properties. However, analysis of bound glycerol in biodiesel samples faces challenges due to lack of readily available standards of structurally complex glyceride species in non-traditional biodiesel feedstocks, and a risk of misannotation in the presence of impurities in gas chromatographic separations. Here we evaluate methane and isobutane chemical ionization – single quadrupole mass spectrometry combined with high temperature gas chromatography separations for mapping monoacylglycerols, diacylglycerols and triacylglycerols in biodiesel. Unlike the electron impact ionization which produces mostly in-source fragments, isobutane chemical ionization spectra of tetramethylsilyl (TMS) derivatized monoacylglycerols and diacylglycerols are dominated by molecular ions and M-SiO(CH3)3+ ions, which provide important diagnostic information. We demonstrate the utility of isobutane chemical ionization in identifying structurally complex glycerolipid standards as well as species in biodiesel samples from different plant and animal feedstocks.

biodiesel, chemcial ionization mass spectrometry↗
NASA NTRS2006

Spectral Measurements of PMCs from SBUV/2 Instruments

The SBUV/2 (Solar Backscattered Ultraviolet, model 2) instrument is designed to monitor ozone stratospheric profile and total column ozone using measurements of the Earth's backscattered ultraviolet albedo. We have previously demonstrated that the normal radiance measurements from SBUV/2 instruments, which sample 12 discrete wavelengths between 252 and 340 nm during each scan, can be used to identify polar mesospheric clouds (PMCs). Some SBUV/2 instruments also periodically view the earth in continuous scan mode, covering the wavelength range 160-400 nm with 0.15 nm sampling. Analysis of these data show PMC occurrence rates similar to the normal discrete scan results, although the observation technique reduces the number of daily measurements by a factor of six. PMC observed by SBUV/2 instruments show a monotonic variation in the residual spectral albedo over the wavelength range 250 300 nm, with maximum enhancements of 10 15% at 250 nm. This result is consistent with microphysical model predictions from Jensen [1989. A numerical model of polar mesospheric cloud formation and evolution, Ph. D. Thesis, University of Colorado]. We find no evidence for a systematic localized increase in PMC residual albedo for wavelengths near 260 nm, in contrast to the recently reported results from the MSX UVISI instrument [Carbary J.F., et al., 2004. Evidence for bimodal particle distribution from the spectra of polar mesospheric clouds. Geophysics Research. Letters 31, L13108]. This result is observed for three different SBUV/2 instruments in both Northern and Southern Hemisphere data over a 13-year span. Our Mie scattering calculations show that the location and magnitude of the 260 nm hump feature is dependent upon the specific scattering angles appropriate to the MSX measurements. Although it explains the MSX spectrum, the bimodal size distribution proposed by Carbary et al. (2004), cannot explain the lack of scattering angle dependence of the SBUV/2 spectral shapes. The spectral signature of the SBUV/2 continuous scan PMC data is thus inconsistent with the bimodal particle size distribution suggested by Carbary et al. (2004).

DeLand, Matthew T.↗
DOE OSTI2018

The Integration of Plant Sample Analysis, Laboratory Studies, and Thermodynamic Modeling to Predict Slag-Matte Equilibria in Nickel Sulfide Converting

The Kalgoorlie Nickel Smelter (KNS) produces low Fe, low Cu nickel matte in its Peirce–Smith converter operations. To inform process development in the plant, new fundamental data are required on the effect of CaO in slag on the distribution of arsenic between slag and matte. A combination of plant sample analysis, high-temperature laboratory experiments, and thermodynamic modeling was carried out to identify process conditions in the converter and to investigate the effect of slag composition on the chemical behavior of the system. The high-temperature experiments involved re-equilibration of industrial matte-slag-lime samples at 1498 K (1225 °C) and P(SO{sub 2}) = 0.12 atm on a magnetite/quartz substrate, rapid quenching in water, and direct measurement of phase compositions using electron probe X-ray microanalysis (EPMA) and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). A private thermodynamic database for the Ca-Cu-Fe-Mg-Ni-O-S-Si-(As) system was used together with the FactSage software package to assist in the analysis. Thermodynamic predictions combined with plant sample characterization and the present experimental data provide a quantitative basis for the analysis of the effect of CaO fluxing on the slag-matte thermochemistry during nickel sulfide converting, in particular on the spinel liquidus and the distribution of elements between slag and matte as a function of CaO addition.

36 MATERIALS SCIENCE↗
DOE OSTI2022

HIPASS study of southern ultradiffuse galaxies and low surface brightness galaxies

ABSTRACT We present results from an H i counterpart search using the HI Parkes All Sky Survey (HIPASS) for a sample of low surface brightness galaxies (LSBGs) and ultradiffuse galaxies (UDGs) identified from the Dark Energy Survey (DES). We aimed to establish the redshifts of the DES LSBGs to determine the UDG fraction and understand their properties. Out of 409 galaxies investigated, none were unambiguously detected in H i. Our study was significantly hampered by the high spectral rms of HIPASS and thus in this paper we do not make any strong conclusive claims but discuss the main trends and possible scenarios our results reflect. The overwhelming number of non-detections suggest that (a) Either all the LSBGs in the groups, blue or red, have undergone environment aided pre-processing and are H i deficient or the majority of them are distant galaxies, beyond the HIPASS detection threshold. (b) The sample investigated is most likely dominated by galaxies with H i masses typical of dwarf galaxies. Had there been Milky Way (MW) size (Re) galaxies in our sample, with proportionate H i content, they would have been detected, even with the limitations imposed by the HIPASS spectral quality. This leads us to infer that if some of the LSBGs have MW-size optical diameters, their H i content is possibly in the dwarf range. More sensitive observations using the SKA precursors in future may resolve these questions.

Zhou, Yun-Fan↗
DOE OSTI2023

Barium stars as tracers of s -process nucleosynthesis in AGB stars: II. Using machine learning techniques on 169 stars

Barium (Ba) stars are characterised by an abundance of heavy elements made by the slow neutron capture process (s-process). This peculiar observed signature is due to the mass transfer from a stellar companion, bound in a binary stellar system, to the Ba star observed today. The signature is created when the stellar companion is an asymptotic giant branch (AGB) star. We aim to analyse the abundance pattern of 169 Ba stars using machine learning techniques and the AGB final surface abundances predicted by the FRUITY and Monash stellar models. We developed machine learning algorithms that use the abundance pattern of Ba stars as input to classify the initial mass and metallicity of each Ba star’s companion star using stellar model predictions. We used two algorithms. The first exploits neural networks to recognise patterns, and the second is a nearest-neighbour algorithm that focuses on finding the AGB model that predicts the final surface abundances closest to the observed Ba star values. In the second algorithm, we included the error bars and observational uncertainties in order to find the best-fit model. The classification process was based on the abundances of Fe, Rb, Sr, Zr, Ru, Nd, Ce, Sm, and Eu. We selected these elements by systematically removing s-process elements from our AGB model abundance distributions and identifying the elements whose removal had the biggest positive effect on the classification. We excluded Nb, Y, Mo, and La. Our final classification combined the output of both algorithms to identify an initial mass and metallicity range for each Ba star companion. With our analysis tools, we identified the main properties for 166 of the 169 Ba stars in the stellar sample. The classifications based on both stellar sets of AGB final abundances show similar distributions, with an average initial mass of M = 2.23 M ⊙ and 2.34 M ⊙ and an average [Fe/H] = –0.21 and –0.11, respectively. We investigated why the removal of Nb, Y, Mo, and La improves our classification and identified 43 stars for which the exclusion had the biggest effect. We found that these stars have statistically significant and different abundances for these elements compared to the other Ba stars in our sample. We discuss the possible reasons for these differences in the abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Plasma proteomic biomarkers of physical frailty in heart failure: a propensity score matched discovery-based pilot study

Background: Physical frailty is highly prevalent in heart failure (HF), but we lack an understanding of the underlying pathophysiology. Proteomics evaluation of plasma samples may elucidate potential mechanisms and biomarkers of physical frailty in HF. We aimed to identify plasma proteomic biomarkers that are differentially expressed between physically frail and non physically frail adults with HF. Methods: This was a secondary analysis of a subset of data and plasma samples from a study of frailty among patients with New York Heart Association (NYHA) Functional Classification I-IV HF. Physical frailty was measured using the Frailty Phenotype Criteria. Propensity score matching was used to match pairs of physically frail (n = 20) vs. non-physically frail (n = 20) patients on clinical characteristics. Plasma samples were processed using a sensitive liquid chromatography mass spectrometry platform, utilizing a multiplexed tandem mass tag-labeled quantitative proteomics approach. Differentially expressed proteins were quantified individually using paired t tests with associated log fold change of 0.3 and Fisher’s combined p values. Results: The sample (n = 40) was 62.8±16.9 years old, 58% female, and 55% NYHA Class III/IV. Proteomics analysis revealed 7 proteins differentially expressed using full differential criteria: matrix metalloproteinase-14 was downregulated in frailty, and copine-1, low affinity immunoglobulin gamma Fc region receptor III-A and III-B, probable non-functional immunoglobulin kappa variable 2D-24, glutathione S-transferase Mu 1, and argininosuccinate lyase were upregulated in frailty. Conclusions: Proteomic biomarkers related to the immune system, stress response, and detoxification were differentially expressed between physically frail and non-physically frail adults with HF.

Biomarkers↗
NASA NTRS1992

Self-tuning control of attitude and momentum management for the Space Station

This paper presents a hybrid state-space self-tuning design methodology using dual-rate sampling for suboptimal digital adaptive control of attitude and momentum management for the Space Station. This new hybrid adaptive control scheme combines an on-line recursive estimation algorithm for indirectly identifying the parameters of a continuous-time system from the available fast-rate sampled data of the inputs and states and a controller synthesis algorithm for indirectly finding the slow-rate suboptimal digital controller from the designed optimal analog controller. The proposed method enables the development of digitally implementable control algorithms for the robust control of Space Station Freedom with unknown environmental disturbances and slowly time-varying dynamics.

Shieh, L. S.↗
NASA NTRS2016

Abundant Solar Nebula Solids in Comets

Comets have been proposed to consist of unprocessed interstellar materials together with a variable amount of thermally annealed interstellar grains. Recent studies of cometary solids in the laboratory have shown that comets instead consist of a wide range of materials from across the protoplanetary disk, in addition to a minor complement of interstellar materials. These advances were made possible by the return of direct samples of comet 81P/Wild 2 coma dust by the NASA Stardust mission and recent advances in microscale analytical techniques. Isotopic studies of 'cometary' chondritic porous interplanetary dust particles (CP-IDPs) and comet 81P/Wild 2 Stardust samples show that preserved interstellar materials are more abundant in comets than in any class of meteorite. Identified interstellar materials include sub-micron-sized presolar silicates, oxides, and SiC dust grains and some fraction of the organic material that binds the samples together. Presolar grain abundances reach 1 weight percentage in the most stardust-rich CP-IDPs, 50 times greater than in meteorites. Yet, order of magnitude variations in presolar grain abundances among CP-IDPs suggest cometary solids experienced significant variations in the degree of processing in the solar nebula. Comets contain a surprisingly high abundance of nebular solids formed or altered at high temperatures. Comet 81P/Wild 2 samples include 10-40 micron-sized, refractory Ca- Al-rich inclusion (CAI)-, chondrule-, and ameboid olivine aggregate (AOA)-like materials. The O isotopic compositions of these refractory materials are remarkably similar to their meteoritic counterparts, ranging from 5 percent enrichments in (sup 16) O to near-terrestrial values. Comet 81P/Wild 2 and CP-IDPs also contain abundant Mg-Fe crystalline and amorphous silicates whose O isotopic compositions are also consistent with Solar System origins. Unlike meteorites, that are dominated by locally-produced materials, comets appear to be composed of materials that were formed across a wide swath of the early protoplanetary disk.

Messenger, S.↗
DOE OSTI2022

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, “Mappgene”, was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2022

Phase II and III Solid Waste Management Unit Assessment and Confirmatory Sampling Report for Per- and Polyfluorinated Alkyl Substances, Potential Release Location 237, Kennedy Space Center, Florida

Per- and polyfluoroalkyl substances (PFAS) Phase II and III Solid Waste Management Unit (SWMU) Assessment (SA) and Confirmatory Sampling (CS) were conducted at the John F. Kennedy Space Center (KSC), Potential Release Location (PRL) 237, located in Merritt Island, Brevard County, Florida for the National Aeronautics and Space Administration (NASA) under Contract 80KSC019D0010/80KSC019F0289. A Phase I SA and CS Report was previously submitted that identified 33 locations of concern (LOCs) at KSC associated with the storage, use, or release of materials containing PFAS. The objectives of the Phase II and III SA and CS were to: - Complete site and source characterization of identified LOCs; - Identify areas of potential concern (AOPCs) where past or present activities may have resulted in a release of PFAS to the environment; - Qualitatively characterize migration potential of released PFAS to environmental media (primarily soil, groundwater, surface water, and sediment); and - Identify potential receptors for exposure to PFAS-impacted environmental media. Surface water samples were collected from LOCs/AOPCs and locations on the KSC periphery during PFAS CS Phases I, II and III. Including duplicate samples, 143 environmental samples were analyzed for 14 PFAS compounds and 104 environmental samples were analyzed for 18 PFAS compounds. Ten of the analytes on the 14 compound list were detected at least once in surface water at KSC, with a wide range in magnitude of detections. The State of Florida has surface water screening levels (SWSLs) for perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) in surface water, both for human and ecological receptors. The human health screening levels are lower than the ecological ones and are used in this report. PFOA was not detected in surface water at concentrations exceeding the SWSL at any LOC or Area of Potential Concern (AOPC). PFOS was detected in surface water at concentrations exceeding the SWSL at 28 LOCs/AOPCs, plus 42 locations on the KSC periphery. The data suggest a wide distribution of PFAS, particularly PFOS, in surface water but the sources of surface water contamination are not yet adequately understood. Sediment samples were collected during Phases II and III but not Phase I. Including duplicate samples, 104 environmental samples were analyzed for 14 PFAS compounds and 10 environmental samples were analyzed for 18 PFAS compounds. Twelve compounds were detected in sediment at KSC, with a wide range in magnitude of detections. There are currently no screening levels or cleanup target levels (CTLs) for sediment. The need to delineate and further characterize PFAS in sediment will be evaluated for those sites that move forward into Site Assessment. Groundwater samples were collected via DPT from LOCs/AOPCs and locations on the KSC periphery during PFAS CS Phases I, II and III. Including duplicate samples, 812 environmental DPT groundwater samples were analyzed for 14 PFAS compounds and 247 environmental samples were analyzed for 18 PFAS compounds. Twelve of the 14 compounds were detected in groundwater at KSC, with a wide range in magnitude of detections. The State of Florida has provisional groundwater cleanup target levels (GCTLs) for PFOA, PFOS and the additive concentration of PFOA+PFOS. PFOA was detected in groundwater at concentrations exceeding its provisional GCTL at 16 LOCs/AOPCs, with no exceedances on the KSC periphery. PFOS was detected in groundwater at concentrations exceeding its provisional GCTL at 30 LOCs/AOPCs, plus two locations on the KSC periphery. PFOA+PFOS was detected in groundwater at concentrations exceeding the provisional GCTL at 31 LOCs/AOPCs, plus two locations on the KSC periphery. Soil samples were collected during Phases II and III but not Phase I. Including duplicate samples, 292 environmental samples were analyzed for 14 PFAS compounds and 80 environmental samples were analyzed for 18 PFAS compounds. Fourteen compounds were detected in soil at KSC, with a wide range in magnitude of detections. The State of Florida has provisional soil cleanup target levels (SCTLs) for PFOA and PFOS. There were no PFOA results above its provisional SCTL. There was one LOC with a result above the provisional SCTL for residential settings. Recommendations are presented for each LOC and AOPC.

PFAS↗
DOE OSTI2018

Statistical analysis of the chemical attribution signatures of 3-methylfentanyl and its methods of production

Chemical attribution of the origin of an illegal drug is a key component of forensic efforts aimed at combating illicit and clandestine manufacture of drugs and pharmaceuticals. The results of these studies yield detailed information on synthesis byproducts, reagents, and precursors that can be used to identify the method of manufacture. Here in the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic 3-methylfentanyl, N-(3-methyl-1-phenethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Eighteen crude samples from six synthesis methods were generated, the analysis of which was used to identify signatures (i.e. chemical compounds) that were important in the discrimination of synthetic route. These methods were carefully selected to minimize the use of scheduled precursors, complicated laboratory equipment, number of steps, and extreme reaction conditions. Using gas and liquid chromatographies combined with time-of-flight mass spectrometry (GC-QTOF and LC-QTOF) over 160 distinct species were monitored. Lastly, analysis of this combined data set was performed using modern machine learning techniques capable of reducing the size of the data set, prioritizing key chemical attribution signatures, and identifying the method of production for blindly synthesized 3-methylfentanyl materials.

3-methylfentanyl↗
DOE OSTI2018

Artifact-Free Coring Procedures for Removing Samples from Photovoltaic Modules for Microscopic Analysis

An important step in producing more reliable and efficient photovoltaic modules is to establish a relationship between the microscopic properties of modules deployed in the field for many years and efficiency-related parameters. The first step in accomplishing this task is to be able to identify and remove small areas from these modules without causing any damage to these samples. In this work, we will describe two different procedures to core small areas of deployed and stressed solar panels produced with different materials (Si, CIGS, and CdTe), and we will prove that these processes did not damage the cored material. We will also show that the coring procedure changes for different types of photovoltaic modules.

14 SOLAR ENERGY↗
DOE OSTI2022

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample

Accurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detection approach, and demonstrated performance advantages on in silico data. In this study, we use the first comprehensive and well-characterized somatic reference data sets from the SEQC2 consortium to investigate best practices for using a deep learning framework in cancer mutation detection. Using the high-confidence somatic mutations established for a cancer cell line by the consortium, we identify the best strategy for building robust models on multiple data sets derived from samples representing real scenarios, for example, a model trained on a combination of real and spike-in mutations had the highest average performance. The strategy identified in our study achieved high robustness across multiple sequencing technologies for fresh and FFPE DNA input, varying tumor/normal purities, and different coverages, with significant superiority over conventional detection approaches in general, as well as in challenging situations such as low coverage, low variant allele frequency, DNA damage, and difficult genomic regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Coevolution of phyllosilicate, carbon, sulfide, and apatite in Ryugu's parent body

Abstract We analyzed an asteroid Ryugu sample returned to Earth by JAXA's Hayabusa2 mission using nanoIR, SEM, and TEM microscopy. We identified multiple distinct carbon reservoirs within the phyllosilicate matrix and demonstrate infrared spectral affinities for some of the carbon to insoluble organic matter (IOM). TEM studies of Ryugu samples have allowed us to better understand the interrelationship between the crystallographic orientations of phyllosilicates and the secondary minerals such as carbonate, sulfide, and apatite. Transport of elements provides a unifying theme for understanding these interrelationships.

Geochemistry & Geophysics↗
DOE OSTI2017

Mira Variable Stars from LAMOST DR4 Data: Emission Features, Temperature Types, and Candidate Selection

Based on an extensive spectral study of a photometrically confirmed sample of Mira variables, we find a relationship between the relative Balmer emission-line strengths and spectral temperatures of O-rich Mira stars. The F{sub Hδ}/F{sub Hγ} flux ratio increases from less than unity to five as stars cool down from M0 to M10, which is likely driven by increasing TiO absorption above the deepest shock-emitting regions. We also discuss the relationship between the equivalent widths of the Balmer emission lines and the photometric luminosity phase of our Mira sample stars. Using our 291 Mira spectra as templates for reference, 191 Mira candidates are newly identified from the LAMOST DR4 catalog. We summarize the criteria adopted to select Mira candidates based on emission-line indices and molecular absorption bands. This enlarged spectral sample of Mira variables has the potential to contribute significantly to our knowledge of the optical properties of Mira stars and will facilitate further studies of these late-type, long-period variables.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗