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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design and Construction of a High-Resolution Hodoscope for the GlueX Experiment with High-Statistics Analysis of the p0, ¿, and ¿1 Photoproduction Cross Sections from the RadPhi Experiment

Differential cross sections for forward-angle photoproduction of p0, ¿, and ¿ 1 pseudoscalar mesons were measured using data from the RadPhi experiment conducted in Hall B at Jef ferson Lab. RadPhi utilized a tagged bremsstrahlung photon beam incident on a stationary 9Be target, with a detector system configured to trigger on a recoil proton in coincidence with multiple neutral showers in the calorimeter. Events were reconstructed and subjected to kinematic constraints, with background suppressed via sideband subtraction guided by Monte Carlo modeling of background contributions. Cross sections were extracted over the photon energy range 4.4– 5.4 GeV and binned in invariant momentum transfer t, providing measurements from one of the first high-statistics experiments of forward ¿ and ¿1 pro duction from a nuclear target at these energies. Acceptance corrections were applied using a detailed GEANT-based simulation of the detector geometry and response. The resulting cross sections are consistent with 2020 CLAS results, when scaled by the number of protons in beryllium, and show broad agreement with other data and theoretical models. In parallel, a high-resolution photon tagger detector, the Tagger Microscope (TAGM), was designed, constructed, and commissioned for the GlueX experiment in Hall D at Jefferson Lab. The TAGM was developed to provide high-rate tagging capability in the coherent bremsstrahlung peak by detecting post-bremsstrahlung electrons across a one GeV range along the focal plane of the tagging spectrometer. The detector consists of a 5ˆ102 array of 2ˆ2 mm2 square BCF-20 plastic scintillating fibers thermally fused to BCF-98 light guide fibers optically coupled to silicon photomultipliers. These fibers are mounted in a precision machined framework enabling fine positional adjustments to maintain precise alignment with post-bremsstrahlung electron trajectories, while ensuring mechanical rigidity, thermal stability, optical isolation, minimal inactive area, and radiation shielding for electronics. The construction effort involved extensive testing of fiber quality, light transmission, thermal fusing, radiation hardness, and defect analysis using SEM and EDX techniques. Following its installation and commissioning, the TAGM became a critical component of the GlueX beamline, enabling high-rate tagging essential for studies of hybrid mesons and gluonic ex citations.

McIntyre, James [Univ. of Connecticut, Storrs, CT ↗
DOE OSTI2022

New Industry Partnerships: Solar Energy Technologies Office Support for Early Projects in the Energy Systems Integration Facility: An Agreement Closeout Summary Report

The U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Solar Energy Technologies Office (SETO)-funded New Industry Partnerships (NIPs) agreement established multiple new cooperative research projects with industry partners. Each project demonstrated the use of the National Renewable Energy Laboratory's Energy Systems Integration Facility (ESIF) as a national asset for research and development, testing, and validation of new technologies to support high penetrations of solar energy on the electric grid. The agreement was launched in 2013 and represented the SETO portion of the DOE EERE-wide Integrated Network Testbed for Energy Grid Research and Technology Experimentation (INTEGRATE) program. The focus of INTEGRATE was on multi-energy system testing and on testing the interactions of energy systems with information technology, communications, and telecommunications (ICT) systems. The NIPs agreement was a bit different from traditional research projects because it was specifically structured to enable partnerships for ESIF testing and as such required at least a 1:1 funds-in cost share from industry partners. In the end, the project engaged six different industry partnerships and resulted in testing a large number of innovative technologies. These included tiny inverters; power-to-gas technologies; and advanced simulation, analysis, and power-hardware-in-the-loop testing techniques. The agreement also provided significant impact for both research and industrial communities. This summary report provides a brief, high-level overview of these projects and their highlights along with lists of citations and other impacts. Readers are referred to the corresponding project reports for more in-depth information.

14 SOLAR ENERGY↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2024

CyanoCyc cyanobacterial web portal

CyanoCyc is a web portal that integrates an exceptionally rich database collection of information about cyanobacterial genomes with an extensive suite of bioinformatics tools. It was developed to address the needs of the cyanobacterial research and biotechnology communities. The 277 annotated cyanobacterial genomes currently in CyanoCyc are supplemented with computational inferences including predicted metabolic pathways, operons, protein complexes, and orthologs; and with data imported from external databases, such as protein features and Gene Ontology (GO) terms imported from UniProt. Five of the genome databases have undergone manual curation with input from more than a dozen cyanobacteria experts to correct errors and integrate information from more than 1,765 published articles. CyanoCyc has bioinformatics tools that encompass genome, metabolic pathway and regulatory informatics; omics data analysis; and comparative analyses, including visualizations of multiple genomes aligned at orthologous genes, and comparisons of metabolic networks for multiple organisms. CyanoCyc is a high-quality, reliable knowledgebase that accelerates scientists’ work by enabling users to quickly find accurate information using its powerful set of search tools, to understand gene function through expert mini-reviews with citations, to acquire information quickly using its interactive visualization tools, and to inform better decision-making for fundamental and applied research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Microbial Biomass in Soils Receiving Varying Levels of Organic Inputs - A Data Compilation

This dataset contains soil microbial biomass data compiled from published laboratory studies and field manipulations of organic inputs to soils. Each study included at least three levels of a given type of organic input applied to a given type of soil. Studies were selected from the literature that had experimentally manipulated organic input rates to soils using unburned, non-synthetic material (e.g. plant litters, manures, and composts). Fifty-five (55) studies, conducted from 1997 to October 2019, were chosen and compiled into a dataset with 358 observations from 96 combinations of a given organic material applied to a given soil in agricultural systems, laboratory incubations, forests, or grasslands. • Studies were selected when biomass measurements used the chloroform fumigation-extraction procedure followed by carbon analysis, or, in two instances, studies estimated microbial biomass using phospholipid fatty acid analysis. • Studies that used fewer than three input rates or characterized microbial biomass via substrate induced respiration were excluded. • The temporal and spatial aspects of the laboratory and field studies were not essential to the analyses (Craig et al., 2021) and were not included with the measurement data. These data were used to assess the relationship between organic input amounts and microbial biomass. Complete reference citations are provided if additional information is needed. The compiled data are provided in two .csv files: (1) soil treatments and microbial biomass data and (2) literature citations. The “Study” field is the cross reference between files. Also provided is the R code for reproducing the results in the related publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

$\bar{\nu}_\mu$ charged-current $\pi^0$ data release

Data release for the NOvA muon antineutrino charged-current (CC) pi^0 cross section presented in arXiv:2511.05807. The signal for this analysis is defined as muon antineutrino CC interactions in the fiducial volume of the NOvA near detector (a 2.7 m × 2.7 m × 9.0 m region) that produce at least one pi^0 in the final state emerging from the nucleus, within the phase space of muon momentum [0.5, 2.5) GeV/c and muon angle [0, 60) degree, as described in arXiv:2511.05807. The released zip file contains two files: NOvA_NumubarCCPi0_DataRelease.root README.txt The ROOT file includes the cross-section results as well as the statistical and systematic covariance matrices for each variable used in this analysis. The README provides a detailed description of the contents of the data release. Official Flux: The flux used in this analysis is available from the NOvA Public Docs: https://publicdocs.fnal.gov/cgi-bin/ShowDocument?docid=8. File structure --- The ROOT file contains the following TDirectories: pi0p - pi^0 momentum distributions pi0dir - pi^0 angular distributions muonp - muon momentum distributions muondir - muon angular distributions Q2 - reconstructed Q^2 distributions Wmass - reconstructed W_mass distributions Each directory contains three histograms: xsec (TH1D): Cross section result cov_stat (TH2D): Statistical covariance matrix cov_syst (TH2D): Systematic covariance matrix Usage notes: - xsec gives the measured differential cross section w.r.t. the corresponding variable. - cov_stat and cov_syst provide the full covariance matrices. - The bin definitions and kinematic phase spaces follow those used in arXiv:2511.05807. Citation --- If you use these data, please cite: NOvA Collaboration, arXiv:2511.05807.

Wu, Wanwei [Pittsburgh U.] (ORCID:0000000326327215↗
DOE OSTI2023

United States Land-based Wind Supply Curves 2023

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for land-based wind across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE), levelized cost of transmission (LCOT), and more for each reV site (~60,000 sites). Hourly generation profiles are available for each reV site and can be matched to the available capacity in the supply curve (refer to the Jupyter Notebook). The composite exclusion TIFF is a single file that delineates areas where wind installations are permissible based on various siting assumptions. This data packet contains information for the Reference and Limited siting scenarios. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

2023↗
DOE OSTI2021

Publication and Impact of Preprints Included in the First 100 Editions of the CDC COVID-19 Science Update: Content Analysis

Preprints are publicly available manuscripts posted to various servers that have not been peer reviewed. Although preprints have existed since 1961, they have gained increased popularity during the COVID-19 pandemic due to the need for immediate, relevant information. The aim of this study is to evaluate the publication rate and impact of preprints included in the Centers for Disease Control and Prevention (CDC) COVID-19 Science Update and assess the performance of the COVID-19 Science Update team in selecting impactful preprints. All preprints in the first 100 editions (April 1, 2020, to July 30, 2021) of the Science Update were included in the study. Preprints that were not published were categorized as “unpublished preprints.” Preprints that were subsequently published exist in 2 versions (in a peer-reviewed journal and on the original preprint server), which were analyzed separately and referred to as “peer-reviewed preprint” and “original preprint,” respectively. Time to publish was the time interval between the date on which a preprint was first posted and the date on which it was first available as a peer-reviewed article. Impact was quantified by Altmetric Attention Score and citation count for all available manuscripts on August 6, 2021. Preprints were analyzed by publication status, publication rate, preprint server, and time to publication. Of the 275 preprints included in the CDC COVID-19 Science Update during the study period, most came from three servers: medRxiv (n=201, 73.1%), bioRxiv (n=41, 14.9%), and SSRN (n=25, 9.1%), with 8 (2.9%) coming from other sources. Additionally, 152 (55.3%) were eventually published. The median time to publish was 2.3 (IQR 1.4-3.7). When preprints posted in the last 2.3 months were excluded (to account for the time to publish), the publication rate was 67.8%. Moreover, 76 journals published at least one preprint from the CDC COVID-19 Science Update, and 18 journals published at least three. The median Altmetric Attention Score for unpublished preprints (n=123, 44.7%) was 146 (IQR 22-552) with a median citation count of 2 (IQR 0-8); for original preprints (n=152, 55.2%), these values were 212 (IQR 22-1164) and 14 (IQR 2-40), respectively; for peer-review preprints, these values were 265 (IQR 29-1896) and 19 (IQR 3-101), respectively. Prior studies of COVID-19 preprints found publication rates between 5.4% and 21.1%. Preprints included in the CDC COVID-19 Science Update were published at a higher rate than overall COVID-19 preprints, and those that were ultimately published were published within months and received higher attention scores than unpublished preprints. These findings indicate that the Science Update process for selecting preprints had a high fidelity in terms of their likelihood to be published and their impact. The incorporation of high-quality preprints into the CDC COVID-19 Science Update improves this activity’s capacity to inform meaningful public health decision-making.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

INGENIOUS - Great Basin Regional Dataset Compilation

This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while reducing the exploration and development risks for all geothermal resources. These datasets will be used in INGENIOUS as input features for predicting geothermal favorability throughout the Great Basin study area. Datasets consist of shapefiles, geotiffs, tabular spreadsheets, and metadata that describe: 2-meter temperature probe surveys, quaternary faults and volcanic features, geodetic shear and dilation models, heat flow, magnetotellurics (conductance), magnetics, gravity, paleogeothermal features (such as sinter and tufa deposits), seismicity, spring and well temperatures, spring and well aqueous geochemistry analyses, thermal conductivity, and fault slip and dilation tendency. For additional project information, see the INGENIOUS project site linked in the submission. Terms of use: These datasets are provided "as is", and the contributors assume no responsibility for any errors or omissions. The user assumes the entire risk associated with their use of these data and bears all responsibility in determining whether these data are fit for their intended use. These datasets may be redistributed with attribution (see citation information below). Please refer to the license information on this page for full licensing terms and conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Challenges of open data in aquatic sciences: issues faced by data users and data providers

Free use and redistribution of data (i.e., Open Data) increases the reproducibility, transparency, and pace of aquatic sciences research. However, barriers to both data users and data providers may limit the adoption of Open Data practices. Here, we describe common Open Data challenges faced by data users and data providers within the aquatic sciences community (i.e., oceanography, limnology, hydrology, and others). These challenges were synthesized from literature, authors’ experiences, and a broad survey of 174 data users and data providers across academia, government agencies, industry, and other sectors. Through this work, we identified seven main challenges: 1) metadata shortcomings, 2) variable data quality and reusability, 3) open data inaccessibility, 4) lack of standardization, 5) authorship and acknowledgement issues 6) lack of funding, and 7) unequal barriers around the globe. Our key recommendation is to improve resources to advance Open Data practices. This includes dedicated funds for capacity building, hiring and maintaining of skilled personnel, and robust digital infrastructures for preparation, storage, and long-term maintenance of Open Data. Further, to incentivize data sharing we reinforce the need for standardized best practices to handle data acknowledgement and citations for both data users and data providers. We also highlight and discuss regional disparities in resources and research practices within a global perspective.

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 OSTI2026

Soil microbiome resilience to short-term (30 days, 90 days) and long-term (1000 days) drought

This dataset contains data used for the paper "Drought duration does not impact soil microbiome resilience". The Related References will be updated with a full citation when available. Increasing global droughts exert large but poorly understood effects on the microbial communities and ecology of soil. Microbial communities generally show resilience and return to pre-drought conditions when short-term droughted soils are rewet; soils exposed to long-term drought, however, often show a lag upon rewetting, after which microbial communities may or may not return to their pre-stressed conditions. Though short-term droughts have been widely studied, long-term drought manipulation experiments remain rare, especially those that compare microbial response to short-term and long-term drought in tandem. We conducted a 1000-day drought simulation in controlled laboratory conditions with soil cores collected from a tidal freshwater ecosystem in Washington state, USA, and subsequently exposed them to rewetting for two weeks. We also included short-term (30-day and 90-day) drought and rewet treatments to directly compare microbial community and organic matter responses across drought durations. We found distinct microbial taxa belonging to Firmicutes and Actinobacteria enriched after the 1000-day drought, but not after the short-term droughts. While we hypothesized that the microbial community would recover from a short-term drought after rewetting to resemble pre-drought conditions, our results revealed community dissimilarities between rewet and pre-drought conditions across all drought durations. These findings suggest unique microbial life history strategies within certain microbial phyla that make them successful colonizers during an extended drought period, and the influence of environmental and physiological context on microbial responses to rewetting. The 16SrRNA gene amplicon dataset contains processed DNA sequences in the form of an ASV table with raw unrarefied read counts and representative sequences in .fasta format as described in the ESS-DIVE amplicon sequence reporting format (https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format/instructions). The Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) dataset consists of processed files containing presence absence data of molecular formulae and molecular characterization of FTICR resolved peaks. The Nuclear Magnetic Resonance (NMR) dataset contains files relevant to NMR spectra and peaks. A sample key file and a sample metadata file is included for the FTICR/NMR and 16S dataset respectively.

1000-day drought↗