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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Search for light neutral particles decaying promptly into collimated pairs of electrons or muons in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for a dark photon, a new light neutral particle, which decays promptly into collimated pairs of electrons or muons is presented. The search targets dark photons resulting from the exotic decay of the Standard Model Higgs boson, assuming its production via the dominant gluon-gluon fusion mode. The analysis is based on 140 fb -1 of data collected with the ATLAS detector at the Large Hadron Collider from proton-proton collisions at a center-of-mass energy of 13 TeV. Events with collimated pairs of electrons or muons are analysed and background contributions are estimated using data-driven techniques. No significant excess in the data above the Standard Model background is observed. Upper limits are set at 95% confidence level on the branching ratio of the Higgs boson decay into dark photons between 0.001% and 5%, depending on the assumed dark photon mass and signal model.

Aad, G. [Aix-Marseille Université] (ORCID:00000002↗
DOE OSTI2022

Evaluation of simulations of near-surface variables using the regional climate model CCLM for the MOSAiC winter period

The ship-based experiment MOSAiC 2019/2020 was carried out during a full year in the Arctic and yielded an excellent data set to test the parameterizations of ocean/sea-ice/atmosphere interaction processes in regional climate models (RCMs). In the present paper, near-surface data during MOSAiC are used for the verification of the RCM COnsortium for Small-scale MOdel–Climate Limited area Mode (COSMO-CLM or CCLM). CCLM is used in a forecast mode (nested in ERA5) for the whole Arctic with 15 km resolution and is run with different configurations of sea ice data. These include the standard sea ice concentration taken from passive microwave data with around 6 km resolution, sea ice concentration from Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data and MODIS sea ice lead fraction data for the winter period. CCLM simulations show a good agreement with the measurements. Relatively large negative biases for temperature occur for November and December, which are likely associated with a too large ice thickness used by CCLM. The consideration of sea ice leads in the sub-grid parameterization in CCLM yields improved results for the near-surface temperature. ERA5 data show a large warm bias of about 2.5°C and an underestimation of the temperature variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics

Data package for Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the below citations for the data packages and associated manuscript. Please cite as: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics. [Data Set] PNNL DataHub. doi: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. MSV000097435: GLBRC soil yearlong incubation 13C-SIP-Lipidomics [Data Set] MassIVE. doi:10.25345/C57659T3K Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon. In Prep This data package consists of compound-specific 13C SIP-lipidomics data from a yearlong tracer incubation experiment designed to investigate microbial lipid persistence in switchgrass bioenergy crop soils. In order to explore how lipid structure may modulate the persistence of C in soil lipids, we leveraged soils from two sites (Michigan - sandy texture, Wisconsin - silty texture) operated by the U.S. Department of Energy-funded Great Lakes Bioenergy Research Center (GLBRC). These sites had comparable climates, identical management practices, but contrasting soil textures, allowing us to assess the variability of lipid accrual or degradation in soils as well as provide insight regarding the degree to which edaphic properties may regulate the retention of soil lipids. Untargeted lipidomics analyses were performed to identify 13C-labeled lipids in the soil microbiome after long-term incubation. Soils were supplemented with 100 micrograms glucose per gram dry soil (99 atom % 13C or natural abundance for paired control) and incubated; samples were collected two months and one year after glucose addition. Lipid extracts (MPLEx) were analyzed by LC-MS/MS and identified using LIQUID. Calculation of isotopic enrichment of lipids was performed by targeted approach using TarMet to quantify lipid isotopologues and IsoCorrectoR to correct for natural abundance isotopes. Contents: Data package contents reported here are the first version and contain downstream analysis files for the raw LC-MS mass spectrometry files (.mzXML) deposited at the MassIVE database repository under accession MSV000097435 (80 experimental runs; 5.85 GB) | MassIVE DOI: 10.25345/C57659T3K. Support files include the additional data download 'Read Me' file containing data descriptor information. Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. Data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location. Available Data Downloads (0.3 GB): "GLBRC soil yearlong incubation 13C-SIP-Lipidomics_readme.txt" - 'Read Me' data package content file (txt) "GLBRC_DataPackage_analysis files" - Data processing files (Rmd) and saved intermediate data processing outputs (rds, csv, xlsx) "GLBRC_13C_lipidomics_dataset.xlsx" - processed data in tabular format (xlsx) Linked Software: LIQUID LC-MS Analysis Software | 10.5281/zenodo.6459462 Lipid Mini-On Software Tools | 10.5281/zenodo.1492803 pmartR Omics Statistical Software | 10.5281/zenodo.6108667 xcms (v4.3.3) TarMet (v1.1.1) IsoCorrectoR (1.24.0) Funding Acknowledgments: This research was supported by an Early Career Research Program award funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (OBER) Genomic Science program under FWP 68292, FWP 07880 and EMSL Exploratory Research Project 51095. A portion of this work was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by OBER and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RLO1830.

Rempfert, Kaitlin R [Pacific Northwest National La↗
DOE OSTI2021

WA-Omic_LA.1.0 - Quantitative Lipidomics, Metabolomics, and Sequencing (16S/ITS) Publication Data DOI Package

Corresponding Data Publication: "Rapid remodeling of the soil lipidome in response to a drying-rewetting event." This study reveals specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. Drought induced nutrient limitation was reflected in the lipidome and polar metabalome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long chain polyunsaturated fatty acids, in dry soil suggests that lipids play an important role in fungal drought tolerance. Increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions. Data package contents reported here are the first version and contain pre- and post-processed data acquisition and subsequent downstream analysis files using various data source instrument method techniques and Mass Spectroscopy (MS) EMSL capabilities. This publication data package DOI is a comprehensive high-throughput multi-omics data lifecycle collection containing processed data method metadata. Support files include additional data download “Read Me” file containing data descriptor information and data source application ontologies (see data dictionary). Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. For increased data availability and interoperability, GC-MS/LC-MS mass spectrometry datasets (Thermo .raw ) were deposited at the MassIVE database repository under the related data accession MSV000086931 and can be accessed by using the API. Statistical data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location.

Amplicon sequencing 16S ITS LC-MS/MS lipidomics mu↗
DOE OSTI2021

WA-Omic_LA.1.0 - Quantitative Lipidomics, Metabolomics, and Sequencing (16S/ITS) Publication Data DOI Package

Corresponding Data Publication: "Rapid remodeling of the soil lipidome in response to a drying-rewetting event." This study reveals specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. Drought induced nutrient limitation was reflected in the lipidome and polar metabalome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long chain polyunsaturated fatty acids, in dry soil suggests that lipids play an important role in fungal drought tolerance. Increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions. Data package contents reported here are the first version and contain pre- and post-processed data acquisition and subsequent downstream analysis files using various data source instrument method techniques and Mass Spectroscopy (MS) EMSL capabilities. This publication data package DOI is a comprehensive high-throughput multi-omics data lifecycle collection containing processed data method metadata. Support files include additional data download “Read Me” file containing data descriptor information and data source application ontologies (see data dictionary). Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. For increased data availability and interoperability, GC-MS/LC-MS mass spectrometry datasets (Thermo .raw ) were deposited at the MassIVE database repository under the related data accession MSV000086931 and can be accessed by using the API. Statistical data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location.

Amplicon sequencing 16S ITS LC-MS/MS lipidomics mu↗
DOE OSTI2021

WA-Omic_LA.1.0 - Quantitative Lipidomics, Metabolomics, and Sequencing (16S/ITS) Publication Data DOI Package

Corresponding Data Publication: "Rapid remodeling of the soil lipidome in response to a drying-rewetting event." This study reveals specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. Drought induced nutrient limitation was reflected in the lipidome and polar metabalome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long chain polyunsaturated fatty acids, in dry soil suggests that lipids play an important role in fungal drought tolerance. Increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions. Data package contents reported here are the first version and contain pre- and post-processed data acquisition and subsequent downstream analysis files using various data source instrument method techniques and Mass Spectroscopy (MS) EMSL capabilities. This publication data package DOI is a comprehensive high-throughput multi-omics data lifecycle collection containing processed data method metadata. Support files include additional data download “Read Me” file containing data descriptor information and data source application ontologies (see data dictionary). Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. For increased data availability and interoperability, GC-MS/LC-MS mass spectrometry datasets (Thermo .raw ) were deposited at the MassIVE database repository under the related data accession MSV000086931 and can be accessed by using the API. Statistical data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location.

Amplicon sequencing 16S ITS LC-MS/MS lipidomics mu↗
DOE OSTI2021

Making a Water Data System Responsive to Information Needs of Decision Makers

Evidence-based environmental management requires data that are sufficient, accessible, useful and used. A mismatch between data, data systems, and data needs for decision making can result in inefficient and inequitable capital investments, resource allocations, environmental protection, hazard mitigation, and quality of life. In this paper, we examine the relationship between data and decision making in environmental management, with a focus on water management. We focus on the concept of decision-driven data systems —data systems that incorporate an assessment of decision-makers' data needs into their design. The aim of the research was to examine the process of translating data into effective decision making by engaging stakeholders in the development of a water data system. Using California's legislative mandate for state agencies to integrate existing water and other environmental data as a case study, we developed and applied a participatory approach to inform data-system design and identify unmet data needs. Using workshops and focused stakeholder meetings, we developed 20 diverse use cases to assess data sources, availability, characteristics, gaps, and other attributes of data used for representative decisions. Federal and state agencies made up about 90% of the data sources, and could readily adapt to a federated data system, our recommended model for the state. The remaining 10% of more-specialized data, central to important decisions across multiple use cases, would require additional investment or incentives to achieve data consistency, interoperability, and compatibility with a federated system. Based on this assessment, we propose a typology of different types of data limitations and gaps described by stakeholders. We also propose technical, governance, and stakeholder engagement evaluation criteria to guide planning and building environmental data systems. Data-system governance involving both producers and users of data was seen as essential to achieving workable standards, stable funding, convenient data availability, resilience to institutional change, and long-term buy-in by stakeholders. Our work provides a replicable lesson for using decision-maker and stakeholder engagement to shape the design of an environmental data system, and inform a technical design that addresses both user and producer needs.

Cantor, Alida↗
DOE OSTI2021

Outlier classification using autoencoders: application for fluctuation driven flows in fusion plasmas

Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a novel diagnostic that uniquely allow us to sample the plasma parameters on a time scale shorter than the characteristic time scale of their fluctuations. Sudden large-amplitude fluctuations in the plasma degrade the precision and accuracy of the plasma parameters reported by MLPs for cases in which the probe bias range is of insufficient amplitude. While some data samples can readily be classified as valid and invalid, we find that such a classification may be ambiguous for up to 40% of data sampled for the plasma parameters and bias voltages considered in this study. In this contribution, we employ an autoencoder (AE) to learn a low-dimensional representation of valid data samples. By definition, the coordinates in this space are the features that mostly characterize valid data. Ambiguous data samples are classified in this space using standard classifiers for vectorial data. In this way, we avoid defining complicated threshold rules to identify outliers, which require strong assumptions and introduce biases in the analysis. By removing the outliers that are identified in the latent low-dimensional space of the AE, we find that the average conductive and convective radial heat fluxes are between approximately 5% and 15% lower as when removing outliers identified by threshold values. For contributions to the radial heat flux due to triple correlations, the difference is up to 40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Global gridded crop harvested area, production, yield, and monthly physical area data circa 2015

Abstract Here we provide an update to global gridded annual and monthly crop datasets. This new dataset uses the crop categories established by the Global Agro-Ecological Zones (GAEZ) Version 3 model, which is based on the Food and Agricultural Organization of the United Nations (FAO) crop production data. We used publicly available data from the FAOSTAT database as well as GAEZ Version 4 global gridded dataset to generate circa 2015 annual crop harvested area, production, and yields by crop production system (irrigated and rainfed) for 26 crops and crop categories globally at 5-minute resolution. We additionally used available data on crop rotations, cropping intensity, and planting and harvest dates to generate monthly gridded cropland data for physical areas for the 26 crops by production system. These data are in standard georeferenced gridded format, and can be used by any global hydrology, land surface, or other earth system model that requires gridded annual or monthly crop data inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

5-meter Sonic Anemometer Winds Nantucket (Standardized)

This dataset contains three-dimensional wind measurements (u, v, w) at 5 meters, as well as virtual temperature. These measurements are taken from the meteorological tower at Nantucket, with the instrument facing toward the southwest. The data have been standardized into NetCDF format.

17 WIND ENERGY↗
DOE OSTI2023

Standardized naming of microbiome samples in Genomes OnLine Database

The power of next-generation sequencing has resulted in an explosive growth in the number of projects aiming to understand the metagenomic diversity of complex microbial environments. The interdisciplinary nature of this microbiome research community, along with the absence of reporting standards for microbiome data and samples, poses a significant challenge for follow-up studies. Commonly used names of metagenomes and metatranscriptomes in public databases currently lack the essential information necessary to accurately describe and classify the underlying samples, which makes a comparative analysis difficult to conduct and often results in misclassified sequences in data repositories. The Genomes OnLine Database (GOLD) (https:// gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute has been at the forefront of addressing this challenge by developing a standardized nomenclature system for naming microbiome samples. GOLD, currently in its twenty-fifth anniversary, continues to enrich the research community with hundreds of thousands of metagenomes and metatranscriptomes with well-curated and easy-to-understand names. Through this manuscript, we describe the overall naming process that can be easily adopted by researchers worldwide. Additionally, we propose the use of this naming system as a best practice for the scientific community to facilitate better interoperability and reusability of microbiome data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

On the Ambiguity of Using Isc for Analyzing Suns-Voc Data on Modules

In standard silicon solar modules, cells are strung in series with bypass diodes incorporated to reduce the effects of shading. When all of the strings are partially shaded the measured short circuit current is affected and the Isc of the module will be equal to that of the lowest current cell in the least shadowed string. In bifacial modules the ability to assess losses due to shading is especially important. This paper advocates an alternative approach to converting the raw suns-voc data to pseudo IV data in modules where shading may be affecting the suns-voc curve results.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity

Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants.

Lamour, Julien [Université of Toulouse (France); U↗
DOE OSTI2021

Observation of e + e - → ηψ(2S) at center-of-mass energies from 4.236 to 4.600 GeV

Using a total of 5 25 fb -1 of e + e - collision data with center-of-mass energies from 4.236 to 4.600 GeV, we report the first observation of the processe + e - → ηψ(2S) with a statistical significance of 4.9 standard deviations. The data sets were collected by the BESIII detector operating at the BEPCII storage ring. We measure the yield of events integrated over center-of-mass energies and also present the energy dependence of the measured cross section.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

59 BASIC BIOLOGICAL SCIENCES↗