SEARCH · Search NASA

Results for “sample analyses”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Comparison of the sensitivity of 236 U measurements in environmental samples by MC-ICP-MS and ATONA based high precision U TIMS measurements

The ATONA project is focused upon exploring the improvements in uranium isotope ratio measurements by thermal ionization mass spectrometry (TIMS) provided by a new, capacitor-based, amplifier technology. These “ATONA” Faraday amplifiers (Isotopx Ltd, UK) promise accurate, low-noise measurements of very small signals (< 1 femto-amp) in a traditional Faraday cup, which was only previously possible using an ion counter. This report outlines a series of experiments that were performed to assess the performance of the system in samples that test our rapid analysis procedures, and then compare the results against other mass spectrometry techniques currently available for environmental analyses. The following major goals were achieved: (1) illustrated the importance of 236 U measurements for the screening and analysis of environmental samples; (2) improved sensitivity for 236 U, and then identified 236 U in the 4350B standard at ultra-trace levels (3) Provided comparison of the 236 U sensitivity to multi-collector inductively coupled mass spectrometry techniques (4) Illustrated high TRL for the ATONA based measurement technique. This completes the reporting requirements for task 4 in the project LCP and highlights the utility of the system to make highly sensitive 236 U measurements in programmatically relevant sample matrices and at relevant uranium concentrations.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗

DOE OSTI2024

The mass profiles of dwarf galaxies from Dark Energy Survey lensing

We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterize their stellar mass and redshift distributions with a spectroscopic calibration sample. By combining the ${\sim} 5000\,\mathrm{deg}^2$ multiband photometry from the Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs Survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z\lt 0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log _{10}(M_*/\text{M}_\odot)=\left[8.52\substack{+0.57 -0.76},\, 9.02\substack{+0.50 -0.64},\, 9.49\substack{+0.50 -0.58}\right]$ . We measure the stacked excess surface mass density profiles, $\Delta \Sigma (R)$, of these galaxies using galaxy–galaxy lensing with a signal-to-noise ratio of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log _{10}(M_{\rm halo}/\text{M}_\odot)$ = [$10.67\substack{+0.2 -0.4}$, $11.01\substack{+0.14 -0.27}$, $11.40\substack{+0.08 -0.15}$]. The cold dark matter profiles are consistent with NFW (Navarro, Frenk, and White) profiles over scales ${\lesssim} 0.15 \, {h}^{-1}$ Mpc. We find that ${\sim} 20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data.

dark matter↗

DOE OSTI2024

Neural network based emulation of galaxy power spectrum covariances: A reanalysis of BOSS DR12 data

We train neural networks to quickly generate redshift-space galaxy power spectrum covariances from a given parameter set (cosmology and galaxy bias). This covariance emulator utilizes a combination of traditional fully connected network layers and transformer architecture to accurately predict covariance matrices for the high redshift, north galactic cap sample of the BOSS DR12 galaxy catalog. We run simulated likelihood analyses with emulated and brute-force computed covariances, and we quantify the network’s performance via two different metrics: (1) difference in Χ 2 and (2) likelihood contours for simulated BOSS DR 12 analyses. We find that the emulator returns excellent results over a large parameter range. We then use our emulator to perform a reanalysis of the BOSS HighZ NGC galaxy power spectrum, and find that varying covariance with cosmology along with the model vector produces Ω m = $0.27⁢6$$^{+0.013}_{–0.015}$, H 0 = 70.2 ± 1.9 km/s/Mpc, and σ 8 = $0.67⁢4$$^{+0.058}_{–0.077}$. These constraints represent an average 0.46⁢σ shift in best-fit values and a 5% increase in constraining power compared to fixing the covariance matrix (Ω m = 0.293 ± 0.017, H 0 = 70.3 ± 2.0 km/s/Mpc, σ 8 = $0.70⁢2$$^{+0.063}_{–0.075}$). As a result, this work demonstrates that emulators for more complex cosmological quantities than second-order statistics can be trained over a wide parameter range at sufficiently high accuracy to be implemented in realistic likelihood analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Single-crystal X-ray diffraction on the structure of (Al,Fe)-bearing bridgmanite in the lower mantle

Abstract Here we have performed single-crystal X-ray diffraction (SCXRD) experiments on two high-quality crystal platelets of (Al,Fe)-bearing bridgmanite (Mg0.88Fe0.0653+Fe0.0352+Al0.03)(Al0.11Si0.90)O3 (Fe10-Al14-Bgm) up to 64.6(6) GPa at room temperature in a Boehler-Almax type diamond-anvil cell. Refinements on the collected SCXRD patterns reveal reliable structural information of single-crystal Fe10-Al14-Bgm, including unit-cell parameters, atomic coordinates, and anisotropic displacement parameters. Together with Mössbauer and electron microprobe analyses, our best single-crystal refinement model indicates that the sample contains ~6.5 mol% Fe3+, 3.5 mol% Fe2+, and 3 mol% Al3+ in the large pseudo-dodecahedral site (A site), and ~11 mol% Al3+ in the small octahedral site (B site). This may indicate that Al3+ in bridgmanite preferentially occupies the B site. Our results show that the compression of Fe10-Al14-Bgm with pressure causes monotonical decreases in the volumes of AO12 pseudo-dodecahedron and BO6 octahedron (VA and VB, respectively) as well as the associated A-O and B-O bond lengths. The interatomic angles of B-O1-B and B-O2-B decrease from 145.2–145.8° at 4.2(1) GPa to 143.3–143.5° at 64.6(6) GPa. Quantitative calculations of octahedral tilting angles (Ф) show that Ф increases smoothly with pressure. We found a linear relationship between the polyhedral volume ratio and the Ф in the bridgmanite with different compositions: VA/VB = –0.049Φ + 5.549. Our results indicate an increased distortion of the Fe10-Al14-Bgm structure with pressure, which might be related to the distortion of A-site Fe2+. The local environmental changes of A-site Fe2+ in bridgmanite could explain previous results on the hyperfine parameters, abnormal lattice thermal conductivity, mean force constant of iron bonds and other physical properties, which in turn provide insights into our understanding on the geophysics and geochemistry of the planet.

Geochemistry & Geophysics↗

DOE OSTI2025

Synthesis and characterization of uranium trichloride in alkali-metal chloride media

Given a growing interest in uranium salts for pyrochemical processing of used fuel and uranium-fueled molten salt reactors, the synthesis of uranium trichloride in alkali-metal chloride media was investigated in a series of four experiments. Specifically, uranium metal powder and uranium hydride powder were prepared and separately blended with ammonium chloride and lithium chloride – potassium chloride eutectic in two runs, while the same powders were separately blended with ammonium chloride and sodium chloride in two additional runs. Each of the lithium chloride – potassium chloride containing blends was slowly heated to 923 K, while those containing sodium chloride were heated to 1123 K. During each heat up, the ammonium chloride sublimed into gaseous ammonia and hydrogen chloride, leading to the chlorination of uranium metal or uranium hydride and the formation of molten salt solutions of the respective chlorides. Experimental conditions were incorporated in the runs to promote formation of uranium trichloride over uranium tetrachloride in the respective media. Molten samples of each run product were taken and characterized via chemical analyses, diffractometry, and microscopy. The final products from each run were dark dense ingots of the respective salt systems with uranium concentrations ranging from 44 to 51 wt%. Chemical analyses and diffractometry identified the predominant presence of uranium trichloride in these systems; however, a possible minor presence of uranium tetrachloride could not be conclusively dismissed.

D Herrmann, Steven↗

DOE OSTI2026

Full calibration of the tomographic redshift distribution from the HSC PDR3 Shape Catalog with DESI

The calibration of tomographic redshift distributionsis essential for cosmological analysis of weak lensing data.In this work, we calibrate all four tomographic bins of the Hyper Suprime Camera (HSC) weak lensing catalog with the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 and 2 using the clustering redshifts technique. We include z > 1.2 redshift sources such as emission line galaxies (ELG) and quasars (QSO) sources in our calibration, which were not available in the previous HSC calibration (Rau et al. (2022), Mon. Not. Roy. Astron. Soc. 524 (2023) 5109), allowing a complete calibration of all the redshift bins. We find the first tomographic bin exhibits a small shift towards low redshifts. The second bin is in good agreement with the photometric calibration, while third and fourth bin exhibit a shift towards higher redshifts. However, these shifts are considerably smaller than the shifts obtained in the HSC Year 3 cosmic shear analyses. We evaluate the impact of galaxy bias and magnification effects from all the samples on the measurements, finding them to be small, and we propose corrections to reduce them further. Specifically, we relax the assumption of linear bias and only assume no redshift evolution of the cross-correlation coefficient, allowing us to leverage smaller clustering scales. We model the redshift distributions with splines and compare our results to previous analyses as well as to other parameterizations found in literature. For the two high-redshift tomographic bins, we find the shifts to higher redshifts with respect to the measurements performed in Rau+2022 to be Δz$_{3}$ =-0.039$^{+0.020}$$_{-0.021}$ and Δz$_{4}$ = -0.048$^{+0.012}$$_{-0.012}$.

Choppin de Janvry, J. [LBL, Berkeley; UC, Berkeley↗

DOE OSTI2024

Characterization Results for the October 2024 Tank Farm 3H Evaporator Overhead Sample

On an annual basis, Savannah River Mission Completion (SRMC) provides 2H and 3H evaporator overhead samples to Savannah River National Lab (SRNL) to be analyzed per Section 5.2 of the Effluent Treatment Project (ETP) Waste Compliance Plan (WCP) and the Waste Acceptance Criteria (WAC). This report presents characterization results for the October 2024 3H evaporator overhead sample. The sample was clear and colorless with no visible solids. The results provide measurements for cesium-137 (137Cs), strontium-90 (90Sr), and iodine-129 (129I) with the radionuclide concentration limits specified by the WAC. These analyses were performed in duplicate, and a summary of the analytical results for this 3H evaporator overhead sample includes the following: The measured cesium-137 activity in the 3H evaporator overhead sample averaged 6.72E+01 dpm/mL, (3.90E+00 %RSD), which is below the ETP WAC limit of 1.30E+03 dpm/mL. The strontium-90 activity in the 3H evaporator overhead sample averaged <2.72E+00 dpm/mL, which is below the ETP WAC limit of 1.76E+02 dpm/mL. The iodine-129 activity in the 3H evaporator overhead sample averaged <1.63E-01 dpm/mL, which is below the ETP WAC limit of 1.00E+00 dpm/mL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

APPL Hyperspectral_Imaging_Dataset_for_Heritability_Analysis_in_Populus_trichocarpa

This dataset contains hyperspectral imaging data collected at the Advanced Plant Phenotyping Laboratory (APPL) at Oak Ridge National Laboratory. Natural variants of Populus trichocarpa were imaged using a high-throughput hyperspectral phenotyping pipeline to quantify spectral reflectance traits for downstream quantitative genetics analyses. The dataset includes hyperspectral image files and derived reflectance data products suitable for extracting spectral features across the measured wavelength range (e.g., VNIR and/or SWIR, depending on instrument configuration), along with associated sample metadata (e.g., genotype identifiers, experimental design factors, and imaging run identifiers). These data were generated to support analyses of broad-sense heritability of hyperspectral traits and their relationships with biochemical phenotypes (including lignin traits from Py-MBMS).

APPL↗

DOE OSTI2025

Preliminary Insights Into the Feasibility of Determining the Purification Date of Enriched Uranium by Direct Measurement of the 230 Th/ 234 U Ratio Using an All-Faraday Detector Configuration on the Neoma MC-ICP-MS

Rationale: Mass spectrometric measurement of the 230 Th/ 234 U ratio to calculate the purification age of enriched uranium is typically conducted via a combination of ion counters and faraday detectors, thus requiring an inter-detector calibration scheme. Here, our aim is to understand whether the pursuit of a simplified measurement scheme involving only faraday detectors is feasible. Methods: We investigate the possibility of determining U-Th model ages for two enriched uranium standards (NBL U630 and U850) by direct measurement of the 230 Th/ 234 U ratio (without chromatographic separation or isotope dilution) on a ThermoFisher Scientific Neoma MC-ICP-MS utilizing both solution and laser ablation (LA)-based sampling techniques and an all-faraday detector configuration. Results: For the solution mode analyses conducted on aliquots containing sub μg/mL total U, we produce composite average 230 Th/ 234 U model dates of May 19, 1988 (± 351 days), and March 26, 1961 (± 2.5 years) using the directly measured 230 Th/ 234 U ratios for the NBL U630 and U850 uranium standards, which have certified purification dates of June 6, 1988 (± 190 days), and December 31, 1957 (± 36.5 days), respectively. The ages produced by LA-based sampling of dried residues of the same standards deposited onto cotton TexWipes are less accurate and of poorer precision (June 23, 2004 ± 8.7 years for U630 and December 21, 1965 ± 7.9 years for U850) but still yield meaningful information in regards to the purification date. Conclusions: We believe that further refinement of the all faraday detector measurement approach to include development of a more robust Th/U relative sensitivity factor determination, signal cutoff selection, and data processing protocols will allow for this approach to be confidently applied to enriched uranium materials with unknown purification histories. Potential advantages of the method include the reduced sample handling and infrastructure requirements as well as the ability to simultaneously generate a broad picture of the uranium isotopic composition in tandem with the U-Th age determination.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Peatland Plant Community Changes in Annual Production and Composition Through 8 Years of Warming Manipulations Under Ambient and Elevated CO 2 Atmospheres

The Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment has operated five whole-ecosystem warming manipulations (+0, +2.25, +4.5, +6.75, and +9°C) with paired ambient and elevated CO 2 atmospheres (eCO 2 , +500 ppm) for 8 full calendar years (since August 2015). We tracked shrub-layer vegetation responses to the treatments using annual destructive plot sampling. Tree (Picea and Larix) responses were assessed annually using nondestructive dimensional analyses and allometric conversions. Shrub community changes were assessed for key ericaceous shrubs (Rhododendron, Chamaedaphne, and Kalmia), two Vaccinium species (V. angustifolium, V. oxycoccos), graminoid species (mostly Eriophorum), and one common forb (Maianthemum trifolium), plus minor understory species. We tracked annual aboveground net primary production (ANPP) for vascular plant species in gC m -2 y -1 and overall stand contribution in dry mass. We observed a linear increase in shrub-layer aboveground biomass accumulation with warming over time due primarily to an increase in ericaceous shrub abundance. Cumulative biomass increases across the shrub community showed overall positive responses to eCO 2 after 8 years. Community composition also changed with warming, with increases in woody shrub density, and the reduction or loss of forbs. The tree community showed minimal initial responses to warming early in the treatments, but since 2020, has shown significant increases in ANPP and individual tree growth with warming. The main driver of change in the vascular plant community was temperature, with less pronounced effects of eCO 2 evident. These results indicate an overall increase in ANPP with warming from both the tree and shrub layers of peatland vegetation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

pop-cosmos : redshifts and physical properties of KiDS-1000 galaxies

ABSTRACT Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak-lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy distribution (SED) fitting for 4 million KiDS (Kilo-Degree Survey)-1000 galaxies. Calibrated on deep COSMOS2020 photometric data, pop-cosmos specifies a physically motivated prior over the galaxy population up to $z \simeq 6$ in stellar population synthesis (SPS) parameter space. Using the Speculator SPS emulator with GPU (graphics processing unit)-accelerated Markov Chain Monte Carlo sampling, we perform full posterior inference at 8.2 GPU seconds per galaxy, obtaining joint constraints on galaxy redshifts and physical properties. We validate photometric redshifts against $\sim \!185\,\!000$ KiDS galaxies cross-matched to Dark Energy Spectroscopic Instrument Data Release 1 spectroscopic samples, achieving low bias ($2\times 10^{-3}$), scatter ($\sigma _{\mathrm{MAD}}=0.03$), and outlier fraction (3.2 per cent) for the Bright Galaxy Survey, with comparable performance (bias $3\times 10^{-2}$, $\sigma _{\mathrm{MAD}}=0.05$, 1.0 per cent outliers) for luminous red galaxies (LRGs). Within the LRG sample, we identify massive, dusty, star-forming contaminants at $z \simeq 0.4$ satisfying standard colour selections for quenched populations. We infer trends in stellar mass, star formation, metallicity, and dust across five tomographic redshift bins consistent with established scaling relations. Using specific star formation rate constraints, we identify $\sim$7 per cent of KiDS-1000 galaxies as quenched, versus 37 per cent implied by conservative colour cuts. This enables the construction of weak-lensing samples defined by physical properties while mitigating intrinsic alignment systematics and preserving statistical power. Our analysis validates pop-cosmos out of sample, establishing it as a scalable approach for galaxy evolution and cosmological analyses with photometric surveys.

Halder, Anik [Institute of Astronomy and Kavli Ins↗

DOE OSTI2025

Image registration for accurate electrode deformation analysis in operando microscopy of battery materials

Operando imaging techniques have become increasingly valuable in both battery research and manufacturing. However, the reliability of these methods can be compromised by instabilities in the imaging setup and operando cells, particularly when utilizing high-resolution imaging systems. The acquired imaging data often include features arising from both undesirable system vibrations and drift, as well as the scientifically relevant deformations occurring in the battery sample during cell operation. For meaningful analysis, it is crucial to distinguish and separately evaluate these two factors. To address these challenges, we employ a suite of advanced image-processing techniques. These include fast Fourier transform analysis in the frequency domain, power spectrum-based assessments for image quality, as well as rigid and non-rigid image-registration methods. These techniques allow us to identify and exclude blurred images, correct for displacements caused by motor vibrations and sample holder drift and, thus, prevent unwanted image artifacts from affecting subsequent analyses and interpretations. Additionally, we apply optical flow analysis to track the dynamic deformation of battery electrode materials during electrochemical cycling. This enables us to observe and quantify the evolving mechanical responses of the electrodes, offering deeper insights into battery degradation. Together, these methods ensure more accurate image analysis and enhance our understanding of the chemomechanical interplay in battery performance and longevity.

Sun, Tianxiao↗

DOE OSTI2024

Sludge Batch 11 Assembly: Tank 35

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 35 characterization analyses in support of Sludge Batch 11 (SB11) assembly. Two Tank 35 samples were delivered to SRNL and composited into a single sample in April 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Characterizing the Uncertainty of Measurement of Traceable Isotope Ratios with Bayesian Statistical Techniques

Analytical techniques such as multicollector—inductively coupled plasma—mass spectrometry (MC-ICP-MS) are routinely employed at SRNL, other National Laboratories, and in academia to determine the precise isotopic composition of diverse natural and anthropogenic samples (e.g., rocks and nuclear materials). Quantifying and reporting uncertainty in such analyses, while regularly performed, have a rigorous statistical foundation. The Guide to the Expression of Uncertainty in Measurement 4 (GUM) outlines conventional techniques used to assess such uncertainty. As the accessibility and speed of statistical computing increase, there is a need to modernize conventional techniques. For example, Supplement 1 to the 3rd to the GUM suggests the use of approximation methods as an updated approach to the GUM.

McLarty, Ellis C.↗

DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (June to October 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken at three time points from June 12, 2019 to October 23,2019 at a location (PTT1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples were collected from 60 to 180 cm below surface every 30cm for microbial analyses through metagenomic sequencing. 15 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 780 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”

This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). 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. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.

Dissolved organic matter↗

DOE OSTI2026

WHONDRS River Corridor Surface Water Metabolites and Geochemistry from Global Sites

This dataset supports a broader study examining the character of organic matter that may be delivered to subsurface sediments via hydrologic exchange. To implement the global survey, free stream sampling kits were provided to interested volunteers throughout the world. Samples were collected with minimal constraints in terms of location, but following strict protocols, and shipped for metabolomic analysis via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic matter concentration) were conducted, standardized photos of each field system were taken, and extensive metadata were captured. Sampling began in 2018 and is ongoing as of 2025. This dataset is comprised of one folders of field photos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; and (7) a subfolder with sample data. The sample data subfolder contains (1) surface water dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) methods codes; (3) surface water FTICR methods; and (4) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains three subfolders, one containing the.xml files, one containing the 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, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, or .png. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

Biogeochemistry↗