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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Post-fire time series of sensor and geochemistry sample data from surface water, groundwater, precipitation, soil, and vegetation across Oak Creek watershed, Washington

This dataset supports a broader study examining wildfire impacts on hydrologic connectivity across 5 sites within the Oak Creek watershed and the resulting biogeochemical impacts. Stream sites were selected using the Advanced Terrestrial Simulator (ATS) hydrologic model to identify locations with varying groundwater contributions and hydrologic responses across different burn severity scenarios. The Retreat Fire burned from July 23 to August 2 in 2024, affecting the five study sites at varying burn severities. Each site is equipped with YSI EXO2 sondes logging sub-hourly throughout the year, and grab samples are collected approximately every six weeks. YSI sondes are used to measure temporally resolved proxies for groundwater inputs (specific conductivity) and organic matter (fluorescent dissolved organic matter; fDOM) along with basic water quality and depth. Grab samples of surface water, groundwater, and precipitation are analyzed for water stable isotopes and conductivity to understand endmembers for hydrologic mixing Grab samples of surface water, groundwater, soil water, and litter/vegetation/soil leachates are analyzed for organic matter composition measured by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) to understand organic matter dynamics. Game camera photos are provided in a separate data package available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018598. Future versions of this dataset will include time series data from YSI EXO2 sondes (fDOM, dissolved oxygen, temperature, depth, specific conductance, turbidity, pH), BaroTROLL sensors (air temperature and barometric pressure), rain gauges (precipitation), and data from the soil and vegetation samples. Because this study is ongoing, this data package will be updated regularly to include newly collected data and the additional data types. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data; (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) a data checks report; (5) file-level metadata; (6) data dictionary; (7) field metadata; (8) readme; (9) international generic sample number (IGSN) mapping file; and (10) field protocols. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) stable water isotopes and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Biogeochemistry↗
DOE OSTI2024

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to enable and understanding of their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transfected with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produce. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of novel DB positions and enzymatic specificity.

mass spectrometry, deep learning, Lipidomics, doub↗
NASA NTRS2011

Stabile Chlorine Isotope Study of Martian Shergottites and Nakhlites; Whole Rock and Acid Leachates and Residues

We have established a precise analytical technique for stable chlorine isotope measurements of tiny planetary materials by TIMS (Thermal Ionization Mass Spectrometry) [1], for which the results are basically consistent with the IRMS tech-nique (gas source mass spectrometry) [2,3,4]. We present here results for Martian shergottites and nakhlites; whole rocks, HNO3-leachates and residues, and discuss the chlorine isotope evolution of planetary Mars.

Nakamura, N.↗
DOE OSTI2021

Loss and Isotopic Fractionation of Alkali Elements during Diffusion-Limited Evaporation from Molten Silicate: Theory and Experiments

Moderately volatile elements (MVEs) are variably depleted in planetary bodies, reflecting the imprints of nebular and planetary processes. Among MVEs, Na, K, and Rb are excellent tracers for unraveling the history of MVE depletion in planetary bodies because they have similar geochemical behaviors but can be chemically fractionated by evaporation and condensation processes. Furthermore, K and Rb are amenable to high-precision isotopic analyses, which can help constrain the conditions of evaporation and condensation. To quantitatively understand why Na, K, and Rb are depleted in planetary bodies, we have carried out vacuum evaporation experiments from basaltic melt at 1200 and 1400 °C to study their evaporation kinetics and isotopic fractionations. We chose this composition because it is relevant to evaporation from small differentiated planetesimals. The Rb isotopic compositions of the evaporation residues were measured by multicollector inductively coupled plasma mass spectrometry (MC-ICPMS), and the K isotopic compositions were measured along profiles across the residues by secondary ion mass spectrometry (SIMS). In the 1400 °C run products, we found that the concentrations of both K and Rb in the run products decreased from core to rim, which was accompanied by a heavy K isotope enrichment near the surface. This indicates that, in this run, evaporation was limited by diffusion. To use those data quantitatively, we derive analytical equations that describe the evaporation rate and isotopic fractionation associated with diffusion-limited evaporation from a sphere, slab, and cylinder in transient and quasi-steady state regimes. This model is used to tease out the roles that diffusive transport in the melt and evaporation at the melt/gas interface play in setting the elemental depletion and isotopic composition of the residue. Under our experimental conditions, volatility decreases in the order of Na, Rb, and K. Using our experimental results in a thermodynamic model, we have estimated the product γΓ of activity coefficients × evaporation coefficients of Na, Rb, and K. The measured isotopic compositions of the residues are well explained using Rayleigh distillations, whereby the relative volatilities of K and Rb isotopes are given by the square root of their masses. We use our results and previously published data to predict how K and Rb could have been lost as a function of temperature, melt composition, oxygen fugacity, and saturation degree relevant to Vesta’s building blocks. We find that the K and Rb depletions, K/Rb elemental fractionation, and δ 41 K and δ 87 Rb isotopic fractionations of Vesta (as sampled by howardite-eucrite-diogenite (HED) meteorites) are best explained by evaporation of submillimeter size objects for 0.1-10 years at moderate temperatures (~1050 °C) in a medium ~98.8% saturated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification

Tandem mass spectrometry (MS/MS)-based phosphoproteomics is a powerful technology for global phosphorylation analysis. However, applying four computational pipelines to a typical mass spectrometry (MS)-based phosphoproteomic dataset from a human cancer study, we observed a large discrepancy among the reported phosphopeptide identification and phosphosite localization results, underscoring a critical need for benchmarking. While efforts have been made to compare performance of computational pipelines using data from synthetic phosphopeptides, evaluations involving real application data have been largely limited to comparing the numbers of phosphopeptide identifications due to the lack of appropriate evaluation metrics. We investigated three deep learning-derived features as potential evaluation metrics: phosphosite probability, Delta RT and spectral similarity. Predicted phosphosite probability is computed by MusiteDeep, which provides high accuracy as previously reported; Delta RT is defined as the absolute retention time (RT) difference between RTs observed and predicted by AutoRT; and spectral similarity is defined as the Pearson’s correlation coefficient between spectra observed and predicted by pDeep2. Using a synthetic peptide dataset, we found that both Delta RT and spectral similarity provided excellent discrimination between correct and incorrect peptide-spectrum matches (PSMs) both when incorrect PSMs involved wrong peptide sequences and even when incorrect PSMs were caused by only incorrect phosphosite localization. Based on these results, we used all the three deep learning-derived features as evaluation metrics to compare different computational pipelines on diverse set of phosphoproteomic datasets and showed their utility in benchmarking performance of the pipelines. The benchmark metrics demonstrated in this study will enable users to select computational pipelines and parameters for routine analysis of phosphoproteomics data and will offer guidance for developers to improve computational methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. In conclusion, we determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

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

Update on Radiochemical Assessment of High Burnup Commercially Irradiated Fuel

This work documents an effort to collect burnup measurements on a high burnup rod, designated 6XV, and first cycle accident tolerant fuel (ATF) rod, designated 47I, to enable benchmarking of fuel performance codes and neutronics codes. In addition to measurements, Virtual Environment for Reactor Applications (VERA) full-core-depletion analysis was also performed for the rods that were experimentally analyzed to provide an opportunity for code validation. This effort focuses on collecting data from rods irradiated at Byron Generating Station and shipped to the Oak Ridge National Laboratory (ORNL) hot-cells. This data will also anchor non-destructive examination evaluations of burnup of the various fuel rods undergoing postirradiation examination (PIE) at ORNL. Previous PIE of these fuel rods provides some guidance on the burnup trend across the fuel. Axial gamma spectroscopy scans provide a measure of relative changes in burnup across a fuel pin. Mass spectrometry based burnup measurements performed for this work at specific axial locations in the fuel are fully quantitative. By combining the mass spectrometry data with the gamma scans it is possible to more quantitatively evaluate axial variations in burnup across the entire fuel pin [1]. The combined set of burnup evaluations will be made available to other organizations that have an interest in high burnup radiochemistry data for validation of neutronic simulations and source term evaluation such as the Nuclear Regulatory Commission (NRC).

Harp, Jason [Oak Ridge National Laboratory (ORNL),↗
NASA NTRS2009

Investigation of Isovaline Enantiomeric Excesses and Other C5 Amino Acids in Carbonaceous Meteorites

The origin of biological homochirality is one of the most perplexing puzzles to understanding the emergence of life on Earth. While many models have been proposed, the only reported non-biologically generated. compounds that show a significant enantiomeric excess are a few amino acids in the CM2 Murchison and Murray meteorites (e.g. Pizzarello and Cronin 2000; Pizzarello et al, 2008). Of these isovaline (alpha-ethyl-alanine) is of particular interest since it is typically abundant in CM2 meteorites, is exceedingly rare in biology, and due to its chemical structure is likely to maintain its primordial D/L ratio. Instead of the gas chromatography-mass spectrometry (GC-MS) technique employed by Pizzarello et al., we have used liquid chromatography-fluorescence detection/time of flight-mass spectrometry (LC-FD/ToF-MS) to study the enantiomeric ratio of isovaline in the CM2 meteorites Murchison and LEW90500 and the CR2 QUE99177. We have placed particular emphasis on understanding the suite of C5 amino acids in these meteorites. In doing so, we have determined that D and L 3-aminopentanoic acid co-elutes with Lisovaline and L-valine under common chromatographic conditions (Glavin and Dworkin 2006) for omicron-phthaldialdehyde/N-acetyl-L-cysteine (OPA/NAC). We have devised a method to separate these compounds and we will report the actual D/ L ratios of isovaline in these meteorites and how they compare to the GC-MS measurements of Pizzarello and co-workers.

Dworkin, Jason P.↗
NASA NTRS2016

Indigenous Carbonaceous Matter in the Nakhla Mars Meteorite

Detailed microanalysis of the Martian meteorite Nakhla has shown there are morphologically distinct carbonaceous features spatially associated with low-T aqueous alteration phases including salts and id-dingsite. A comprehensive suite of analytical instrumentation including optical microscopy, field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) spectroscopy, focused ion beam (FIB) microscopy, transmission electron microscopy (TEM), two-step laser mass spectrometry (mu-L(sup 2)MS), laser mu-Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), and nanoscale secondary ion mass spectrometry (NanoSIMS) are being used to characterize the carbonaceous matter and host mineralogy. The search for carbonaceous matter on Mars has proved challenging. Viking Landers failed to unambiguously detect simple organics at either of the two landing sites although the Martian surface is estimated to have acquired at least 10(exp15) kg of C as a consequence of meteoritic accretion over the last several Ga. The dearth of organics at the Martian surface has been attributed to various oxidative processes including UV photolysis and peroxide activity. Consequently, investigations of Martian organics need to be focused on the sub-surface regolith where such surface processes are either severely attenuated or absent. Fortuitously since Martian meteorites are derived from buried regolith materials they provide a unique opportunity to study Martian organic geochemistry.

Clemett, S. J.↗
NASA NTRS2019

Millimeter/Submillimeter Spectroscopic Detection of Desorbed Ices: A New Technique in Laboratory Astrochemistry

A new laboratory technique has been developed that utilizes gas-phase, direct-absorption millimeter and submillimeter spectroscopy to detect and identify desorbed species from interstellar and cometary ice analogs. Rotational spectroscopy is a powerful structure-specific technique for detecting isomers and other species possessing the same mass that are indistinguishable with mass spectrometry. Furthermore, the resultant laboratory spectra are directly comparable to observational data from far-infrared and millimeter telescopes. Here we present the proof-of-concept measurements of the detection of thermally desorbed H2O, D2O, and CH3OH originating in a solid film created at low temperature (~12 K). The surface binding energy of H2O is reported and compared to results from traditional techniques, including mass spectrometry and quartz-crystal microbalance measurements of mass loss. Lastly, we demonstrate that this technique is capable of deriving thermodynamic values including the sublimation enthalpy and entropy of H2O.

Katarina M. Yocum↗
DOE OSTI2024

Foundations of Molecular 'Isotomics'

The naturally occurring rare isotopes are versions of common elements, such as hydrogen, carbon and oxygen, that contain a larger than usual number of neutrons in their atomic nuclei and therefore are higher in mass than the common atoms of that element. Isotopes exist for most elements and are found in most natural and synthetic materials, but are uneven in their distribution because chemical and physical processes are isotope-selective (e.g., a chemical reaction may proceed more rapidly for one isotope than for another). For this reason, abundances of isotopes in a material of interest can provide a record, or ‘signature’ of various features of that material’s origin and history. These signatures have been used in the geo, life, chemical and physical sciences in a wide variety of ways over close to 8 decades. However, many such applications struggle to reach unique interpretations of isotopic data because multiple factors combine to control a given sample’s overall isotopic content. That is, the factors controlling isotopic content are too numerous and complex to fully constrain from a simple measurement of a material’s isotope abundances. However, the distribution of isotopes within materials, at molecular scales potentially provides a vastly larger number and diversity of constraints on the chemical and physical processes that comprise a material’s history. The rare isotopes may be concentrated into one atomic position in a molecule relative to another, some proportion of molecules in a sample may contain two or more rare isotopes, and those multiply-isotope-substituted forms of molecules may also have uneven distributions of those isotopes across individual atomic sites. For these reasons, even small, seemingly simple molecules, such as sugars, amino acids or drug compounds, actually exist in a vast number of isotopically unique forms (often millions or more), and each one of those forms is in some sense an independent ‘vote’ on that sample’s history. This project has focused on opening this rich archive of information by enabling the creation of routinely and widely applicable ways of measuring and interpreting isotopic structures of molecules. This work has included the development of core technologies and analytical methods, advancing fundamental understanding of the physical and chemical properties of isotopic versions of molecules, and conducting proof of concept studies of illustrative geochemical, cosmochemical and forensic problems in order to show how these technologies, methods and principles come together to solve problems in new ways. A key to the success of this project was the adaptation of ‘Fourier transform mass spectrometry’ (FTMS) to the task of precisely measuring proportions of the rare, naturally occurring isotopic forms of molecules. FTMS is a highly specialized form of mass spectrometry that traps ions within magnetic or electrostatic cavities and, effectively, ‘listens’ (through registering of subtle electrical signals) to the harmonic signals they make while rapidly orbiting within those cavities. These signals have periods that are a function of their mass and strength (or ‘loudness’) that is proportional to their abundances. Thus, these signals constrain relative amounts of molecules that differ in their mass due to various isotopic substitutions. This technology has been essential to the identification of organic molecules in the life, chemical and environmental sciences for over 4 decades, but generally has lacked the control, stability and precision to meaningfully measure rare isotope forms of molecules. This project’s most fundamental contribution has been to modify FTMS, both in terms of hardware and methods, to enable such measurements. The raw data of molecular isotopic structure is tremendously voluminous and complex, so another important activity of this project has been developing the theoretical and data-science tools needed to interpret the data generated by this new form of isotopic measurement. A particularly challenging part of this task has been predicting molecular isotopic structure, as only through the comparison of measurements with predictions can we make progress on hypothesis driven research questions. We have attacked this this prediction task through a combination of first-principles chemical-physics models of the effects of isotope substitution on molecule properties and data-science models that permit us to generalize that chemical physics to cases that have not yet been studied by detailed chemical physics theory. The proof of concept applications we have pursued over the course of this study include biological reactions of amino acids and other biomolecules, non-biological synthesis of organic molecules in extra-terrestrial settings such as meteorites, petroleum geoscience questions concerning the origin and evolution of natural gas, oil and kerogen compounds, and forensic questions such as the sourcing of chemical weapons. The successes of these applications have laid the groundwork for the next phase of this field’s development, which will include larger scale and more ambitious studies of molecular isotopic structure as a means of diagnosing human diseases, such as cancer, and reconstructing detailed interpretations of the origin and evolution of organic molecules in modern and geological environments.

Cesar, Jaime↗
DOE OSTI2020

Matrix-Assisted Ionization of Molecular Uranium Species

Matrix-assisted ionization (MAI) demonstrates high sensitivity for a variety of organic compounds; however, few studies have reported the application of MAI for the detection and characterization of inorganic analytes. Trace-level uranium analysis is important in the realms of nuclear forensics, nuclear safeguards, and environmental monitoring. Traditional mass spectrometry methods employed in these fields require combinations of extensive laboratory chemistry sample preparation and destructive ionization methods. There has been recent interest in exploring ambient mass spectrometry methods that enable timely sample analysis and higher sensitivity than what is attainable by field-portable radiation detectors. Rapid characterization of uranium at nanogram levels is demonstrated in this study using MAI techniques. Mass spectra were collected on an atmospheric pressure mass spectrometer for solutions of uranyl nitrate, uranyl chloride, uranyl acetate, and uranyl oxalate utilizing 3-nibrobenzonitrile as the ionization matrix. The uranyl complexes investigated were detectable, and the chemical speciation was preserved. Sample analysis was accomplished in a matter of seconds, and limits of detection of 5 ng of uranyl nitrate, 10 ng of uranyl oxalate, 100 ng of uranyl chloride, and 200 ng of uranyl acetate were achieved. The observed gas-phase speciation was similar to negative-ion electrospray ionization of uranyl compounds with notable differences. Six matrix-derived ions were detected in all negative-ion mass spectra, and some of these ions formed adducts with the uranyl analyte. Subsequent analysis of the matrix suggests that these molecules are not matrix contaminants and are instead created during the ionization process.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1982

The Mars reference atmosphere

A nominal atmospheric model of Mars is presented, with detailed consideration being given to the various sources of variability in the Martian atmosphere. A basic model for the midlatitude summer is outlined for the northern and southern hemispheres. Attention is given to meteorological variability due to winds, diurnal and seasonal pressure variations, temperature changes, and the effects of dust opacity, particularly on temperature stratification. Viking lander IR thermal mapper data are examined in terms of diurnal and latitudinal temperature variations, and cloud and haze formation and locations are discussed. Mass spectrometry of the atmosphere is used to describe the molecular abundances, and water vapor measurements are reviewed. Finally, radio occultation, UV airglow, and mass spectrometry of the Martian upper atmosphere are investigated, along with the temperature structure of the upper atmosphere.

Kliore, A.↗
DOE OSTI2024

Minimum Detectable Intakes and Doses for Uranium Bioassays—Comparison between Alpha Spectrometry and ICP-MS

Naturally occurring uranium complicates monitoring for occupational exposures. There are several retroactive methods that can be used to monitor for occupational exposures, with benefits and drawbacks to each. Analysis of uranium in urine by mass spectrometry and alpha spectrometry is compared, and methods of determining an occupational exposure are presented. Furthermore, the minimum detectable concentrations from each analysis and a method for intake determination based on the analytical results are compared for various solubility types and mixtures. Mass spectrometry with radiochemical separation was found to be the most sensitive analysis for detecting occupational exposures to anthropogenic mixtures based on minimum detectable doses calculated from the proposed method for intake determination.

bioassay↗
NASA NTRS1974

Organic synthesis in a simulated Jovian atmosphere. III - Synthesis of aminonitriles

The products from spark and semicorona discharges through mixtures simulating the Jovian atmosphere were analyzed by gas chromatography combined with mass spectrometry. When the reaction was performed at -80 C, 3-ethylaminopropionitrile and a number of higher homologs were formed. On the other hand, at +20 C, higher molecular-weight material appeared which yielded aminonitrile-derived fragments on mass spectrometry. Although the spectra were not identical, there were notable similarities between these and the mass spectra of some compounds present in the Murray and Orgeuil meteorites. Aminonitriles may occur as minor constituents of the Jovian atmosphere and perhaps by cyclization may produce pyrimidines.

Molton, P. M.↗
DOE OSTI2021

Conversion of the LLNL/CAMS 1 MV biomedical AMS system to a semi-automated natural abundance 14C spectrometer: system optimization and performance evaluation

The Lawrence Livermore National Laboratory – Center for Accelerator Mass Spectrometry compact 1 MV biomedical accelerator mass spectrometer was repurposed and optimized for the semi-automated radiocarbon measurement of natural abundance environmental samples. Here we present results from 15 months of routine system operation and evaluate the system performance based on 30 sample wheels measured with consistent operating conditions over 7 months from August 2019 to March 2020. Additionally, the average measurement precision was 2.7 ± 0.7‰. System accuracy was assessed with measurements of 14 C-free materials, standard materials with 14 C-content spanning 0.5 to 1.5 F 14 C, and by comparison to split samples measured with the 10 MV AMS system. Overall, this system can routinely measure samples as small as 300 µgC and less than 33000 years without the need for size-specific correction protocols.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Detailed Characterization of Vitrinite-Rich Subbituminous and Bituminous Coals for Utilization in Carbon Fiber Precursor Production

Chemical structures of candidate coals (one subbituminous coal from the Powder River Basin and three bituminous Eastern US coals) were examined for potential low-cost carbon fiber precursor production. Here, the structural evaluation examined the carbon skeleton ( 13 C nuclear magnetic resonance (NMR) and high-resolution transmission electron microscopy (HRTEM)), the heteroatom functionality (X-ray photoelectron spectroscopy (XPS) Fourier transform infrared spectroscopy (FTIR) and NMR), the structural ordering and distribution of PAH sizes (HRTEM), and an estimation of the molecular weight distribution (laser desorption ionization mass spectrometry, LDIMS). The molecular compositional distributions were also evaluated for a mixed solvent extract (atmospheric pressure photoionization, 21 T Fourier transform ion cyclotron resonance mass spectrometry, FT-ICR MS). Significant structural differences existed between the subbituminous and bituminous coals, as expected with coalification (with the bituminous coals having a higher carbon content, lower oxygen content, higher aromaticity values, larger cluster sizes, and so forth). While the bituminous coals were similar in structure (close in rank with Blue Gem being hvAb and the rest being hvBb), structural differences were still evident. Specifically, structural similarities were evident for the average properties of Herrin and Springfield coals: same rank, similar moisture, and volatile matter yields, along with similar aromaticity and carbon and hydrogen content. However, significant structural differences were observed at the molecular level by 21 T FT-ICR MS, which showed that the Springfield coal was structurally more complex. Specifically, 21740, 16931, 30190, and 12982 unique elemental compositions were identified for the Monarch, Herrin, Springfield, and Blue Gem coals, further illustrating the complexity of the coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Secondary Organic Aerosol from OH Oxidation of Acyclic Terpenes Is More Viscous and Less Volatile than That of Their Cyclic Analogs

Biogenic volatile organic compounds (BVOCs), a dominant source of secondary organic aerosol (SOA) globally, exhibit emission rates and composition that are plant species-specific and vary with environmental stressors. A common outcome of plant stress is increased emissions of acyclic terpenes. The paucity of information about acyclic terpene SOA chemistry contributes to uncertainties in predictions of SOA global loadings and impacts on Earth’s radiative budget, particularly in a changing climate where acyclic terpene emissions could become more prominent. This study compared properties of SOA derived from OH oxidation of acyclic and cyclic monoterpenes (ß-ocimene, a-pinene) and sesquiterpenes (ß-farnesene, ß-caryophyllene). Single particle mass spectrometry was used for assessing shape, density, and evaporation kinetics of size-selected SOA particles, and nanospray desorption electrospray ionization high-resolution mass spectrometry (nano-DESI-HRMS) was used to measure molecular composition of SOA. Acyclic terpene SOA exhibited higher viscosity and lower volatility compared to cyclic terpene SOA, and had a greater volume fraction remaining (VFR) after ~24 hours of evaporation - approximately 1.3-1.6 times higher VFR than that of cyclic terpene SOA. Additionally, HRMS analysis revealed greater chemical diversity and higher fractions of extremely low volatility compounds (56-62% ELVOC/LVOC) in acyclic terpene SOA compared to cyclic counterparts (25-37% ELVOC/LVOC). Our findings highlight the potential importance of accounting for acyclic terpene aerosol chemistry under conditions of plant stress to improve predictions of SOA loadings and impacts.

SOA physical properties↗