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DOE OSTI2025

CABO-16S—a Combined Archaea, Bacteria, Organelle 16S rRNA database framework for amplicon analysis of prokaryotes and eukaryotes in environmental samples

Abstract Identification of both prokaryotic and eukaryotic microorganisms in environmental samples is currently challenged by the need for additional sequencing to obtain separate 16S and 18S ribosomal RNA (rRNA) amplicons or the constraints imposed by “universal” primers. Organellar 16S rRNA sequences are amplified and sequenced along with prokaryote 16S rRNA and provide an alternative method to identify eukaryotic microorganisms. CABO-16S combines bacterial and archaeal sequences from the SILVA database with 16S rRNA sequences of plastids and other organelles from the PR2 database to enable identification of all 16S rRNA sequences. Comparison of CABO-16S with SILVA 138.2 results in equivalent taxonomic classification of mock communities and increased classification of diverse environmental samples. In particular, identification of phototrophic eukaryotes in shallow seagrass environments, marine waters, and lake waters was increased. The CABO-16S framework allows users to add custom sequences for further classification of underrepresented clades and can be easily updated with future releases of reference databases. Addition of sequences obtained from Sanger sequencing of methane seep sediments and curated sequences of the polyphyletic SEEP-SRB1 clade resulted in differentiation of syntrophic and non-syntrophic SEEP-SRB1 in hydrothermal vent sediments. CABO-16S highlights the benefit of combining and amending existing training sets when studying microorganisms in diverse environments.

Eitel, Eryn M. (ORCID:0009000723919297)↗

DOE OSTI2025

Open database for GPD analyses

This article summarizes the main ideas behind creating an open database proposed for use in the exploration of generalized parton distributions (GPDs). This lightweight database is well suited for GPD phenomenology and is designed to store both experimental and lattice-QCD data. It can also aid in benchmarking GPD-related developments, such as GPD models. The database utilizes a new data format based on the YAML serialization language, enabling the storage of essential information for modern analyses, such as replica values. It includes interfaces for both Python and C++, allowing straightforward integration with analysis codes.

Burkert, V. D. [Thomas Jefferson National Accelera↗

DOE OSTI2026

Downloadable Dynamometer Database (D3): Public Test Data on Advanced-Technology Vehicles

Access to high-quality, independent vehicle test data is critical to advancing energy-efficient transportation research. The Downloadable Dynamometer Database (D3) is a public repository of dynamometer test data on advanced-technology vehicles, generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory and hosted by the Transportation and Power Systems Division. The database has been made available to support researchers, students, and professionals engaged in energy-efficient vehicle research, development, and education. A wide range of vehicle categories has been tested (i.e., alternative fuel vehicles, conventional gasoline and diesel vehicles, all-electric vehicles, hybrid electric vehicles, and plug-in hybrid electric vehicles), as well as various drive cycles and test conditions documented in the accompanying D3 user presentation. Stakeholders can select a vehicle type, identify a vehicle of interest, and download the associated test data for use in their own analyses. Data downloaded from D3 must be accompanied by the required attribution: "This data is from the Downloadable Dynamometer Database and was generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory." These data are critical to vehicle modeling, validation, technology assessment, and educational use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Basin-Scale Structural Features Database

The Basin-Scale Structural Features database provides spatial datasets of faults, fractures, folds, and earthquakes compiled from public, authoritative sources (e.g., U.S. Geological Survey and State Geological Surveys) and aggregated into derivative forms to support subsurface assessments. Recognizing that characterizing basin-scale structural features requires interpreting data that are often ambiguous or lack key information, the source data were evaluated using a knowledge-data framework and geospatial fuzzy logic method (Justman et al., 2020) to represent both measured (observed) and predicted (inferred or potential) structural features as derivative datasets. This workflow employs conceptual models for known structural features and predicted structural features, incorporating geospatial data to estimate potential, even with limited data. The aim is to aid and support an understanding of basin-scale features and identify potential gaps in data and knowledge. As of 4/30/2025, the database includes resources for nine sedimentary basins: Appalachian, Denver, U.S. Gulf Coast, Illinois, Michigan, Permian, Sacramento, San Joquin and Williston. The database is organized by basin and then data category: 1) Faults, fractures, folds, 2) Earthquakes, 3) Topographic, 4) Structural contours and isopachs, 5) Geophysical, and 6) Structural feature density assessment maps.

basin scale↗

DOE OSTI2025

Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database

The Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database v1.0 is the output of a data availability assessment workflow that was developed by NETL to create a tool for spatial data availability assessment. This results database is the output of the first version of the workflow performed on the data with the CS TVA Database v2.0.

carbon storage↗

DOE OSTI2024

Fuels Irradiation and Physics Database (FIPD) Development and Data Qualification FY24 Updates

The DOE-NE Advanced Reactor Technologies program has supported efforts to recover and preserve metallic fuel data generated throughout the past fast reactor R&D programs. Those efforts are currently focused on establishing databases for information from the experiments conducted during the Integral Fast Reactor program including data generated at EBR-II, FFTF, and TREAT reactors, as well as out of pile transient testing data. These databases are essential for future-licensing activities of metallic fuel based advanced fast reactors. This report describes the Metallic Fuels Irradiation & Physics Database (FIPD) development, content updates, data qualification status, and user support in FY24. Future plans are also provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Spatial Seal Database for Prospective Storage Resources in the USA

The goal of the Spatial Seal Database for Prospective Storage Resources in the USA is to provide relevant information and spatial extents of caprock and seal rocks. A lack of aggregated information is readily available that focuses on the caprock and seal units within sedimentary basins. The EPA class VI permit requires an assessment of the confining zone as part of submitting a permit. The data catalog of seal unit names and relevant properties with the seal spatial extent database aims to help provided important data for carbon storage based assessments. The data catalog and database are designed to show what seal data is available in a sedimentary basin and guide stakeholders to the original data source for those datasets.

Pantaleone, Scott↗

DOE OSTI2024

The Integration and Mapping of an Open-Source National Well Resource to Inform Geologic Carbon Storage Site Selection and Risk Prevention: The CO2-Locate Database

Geologic carbon storage (GCS) offers a way to capture and permanently store CO₂ from fossil fuel operations in underground geologic structures, aiding in the transition to a carbon-neutral energy economy. However, CO₂ injection sites can experience gas leakage through existing wells that penetrate storage reservoirs, making knowledge of well locations and characteristics crucial for permitting, infrastructure reusability, and risk assessment in GCS. Currently, public wellbore data from state, federal, and tribal entities are inconsistent and fragmented, with gaps and redundancies. To address this, the National Energy Technology Laboratory (NETL) developed CO2-Locate, an open-source, geospatial database and online application. CO2-Locate integrates over 50 data sources from federal, state, and tribal entities, creating a standardized national well database. Funded by the Bipartisan Infrastructure Law, the database is publicly available through the Energy Data eXchange (EDX) and viewable via the CO2-Locate web mapping application. This tool allows users to query, filter, and visualize well data to support GCS planning, permitting, and risk assessments. This presentation covers the methods used to create CO2-Locate, including data acquisition, processing, attribute mapping, and integration, much of which is automated for future updates. The web mapping application and its role in GCS site selection will also be discussed.

Tetteh, Daniel A.↗

DOE OSTI2025

Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments

Presentation slides on "Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments" for CCUS 2025 Annual Meeting. The Basin-Scale Structural Features database contains a series of basin-scale spatial datasets representing structural features, including faults, fractures, folds, and earthquakes. Designed to support carbon storage feasibility and resources assessments for Carbon Capture and Storage (CCS) projects, the database leverages publicly available data resources from authoritative sources (e.g. US Geological Survey, State Geologic Surveys), and aims to help users better understand basin-scale structural features, as well as potential data gaps in areas with sparse information.

basin scale↗

DOE OSTI2026

National Hydropower Fish Passage Database User's Guide and Methodology

Fish passage facilities are used to mitigate the impacts of hydropower dams on migratory fish in rivers, but information on the location, types, and characteristics of this infrastructure is incomplete at a national scale. Researchers at Oak Ridge National Laboratory partnered with federal agency and industry stakeholders to create the first national-scale database of fish passage infrastructure at U.S. hydropower developments. This database contains information of great value to a broad range of stakeholders; it includes fish passage facility engineering characteristics, targeted fish species, operational schedules, and costs. This data resource addresses a large gap in knowledge of the deployment of fish passage technology and is freely available to members of the hydropower community, including federal and state regulators and resource agencies, non-governmental organizations, industry, and other user groups to support project planning and regulatory (re)licensing activities. This database supports the U.S. Department of Energy Water Power Technologies Office objective to develop decision support tools and data resources that improve environmental performance and ensure hydropower’s long-term value to the American public.

13 HYDRO ENERGY↗

DOE OSTI2026

National Wind Plant Database

This database provides detailed information on wind power plants across the US. The database contains records from EIA 860, including plant names, turbine counts, installed capacity, etc. Individual turbine-level data is derived from the U.S. Wind Turbine Database, which provides geographic coordinates and technical specifications for individual wind turbines.

17 WIND ENERGY↗

DOE OSTI2026

US Wind Power Plants Static Database

17 WIND ENERGY↗

DOE OSTI2025

ORNL National Hydropower Fish Passage Database

Fish passage facilities are used to mitigate impacts of hydropower dams to migratory fish in rivers, but information on the location, types, and characteristics of this infrastructure is incomplete at a national scale. Researchers at Oak Ridge National Laboratory (ORNL) partnered with fish passage engineers and hydropower experts from the US Fish and Wildlife Service (USFWS), the National Oceanic Atmospheric Administration’s National Marine Fisheries Service (NOAA NMFS), and the Low Impact Hydropower Institute (LIHI) to create the first national scale database of fish passage infrastructure at US hydropower developments. This database consists of the ORNL_Fish_Passage_Dataset.zip file with 13 individual .csv files that contain information on fish passage facility engineering characteristics, targeted fish species, operational schedule, and costs. which is of great value to a diverse range of stakeholders. This information was collected between December 2023 and July 2025 from project partners, other hydropower stakeholders, online datasets available for download, and a stakeholder questionnaire Information. This data resource addresses a large gap in knowledge of the deployment of fish passage technology and is freely available to members of the hydropower community, including federal and state regulators and resource agencies, non-governmental organizations (NGOs), industry, and other user groups to support project planning and regulatory (re)licensing activities. This database supports the US Department of Energy Water Power Technologies Office objective to develop decision support tools and data resources that improve environmental performance and ensure hydropower’s long-term value to the American public.

Matson, Paul [Oak Ridge National Laboratory (ORNL)↗

DOE OSTI2025

The CAI Database: 26 Al– 26 Mg Isotope Systematics

We present a publicly available calcium–aluminum-rich inclusion (CAI) database that focuses on the initial 26 Al/ 27 Al 0 ratio in CAIs, designed in a way that researchers in cosmochemistry and astrophysics may find useful. To date, the database contains 497 CAIs from 75 peer-reviewed papers. The CAIs are from all chondrite groups and cover different CAI types, textures, and sizes. The database includes the paper; the host meteorite; the CAI name and type; the 26 Al/ 27 Al 0 , δ 26 Mg$^*_0$, and δ 25 Mg values and their uncertainties; the number of regression points; the maximum 27 Al/ 24 Mg; the mean-squared weighted deviation; the CAI size; and CAI descriptions. We grouped the CAIs in different ways to discuss 26 Al/ 27 Al 0 ratio distributions with implications for the CAI formation timeline. Overall, we agree with previous authors that CAIs have a bimodal 26 Al distribution: CAIs with robust isochrons (n = 151) have a median 26 Al/ 27 Al 0 = 4.8 × 10 −5 (with a 1σ standard error of 0.1), while those with isotopic anomalies (n = 87) have a median 26 Al/ 27 Al 0 = 0.3 × 10 −5 (with a 1σ standard error of 0.2). However, the large standard deviation of both groups (1.3 and 2.3, respectively) indicates that the 26 Al/ 27 Al 0 values scatter significantly within each population. CAI types and groups can have distinct 26 Al/ 27 Al 0 and δ 26 Mg$^*_0$, but the unmelted inclusions (n = 33) have the highest median 26 Al/ 27 Al 0 = 5.1 × 10 −5 and a low median δ 26 Mg$^*_0$ = −0.05‰. We find slightly different 26 Al/ 27 Al 0 distributions between CAI chondrite types, but no differences between petrographic types or sizes. These observations can help us to understand CAI formation in the context of astrophysical models.

Astronomy and AstroPhysics↗

DOE OSTI2025

JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms, last access: 11 November 2025), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical simulation (DNS) and some LES datasets of canonical turbulent flows, JHTDB-wind stores the 4D space–time history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 10×6 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. These data comprise 1 h (hour) of flow field data (velocity, pressure, potential temperature deviation, subgrid-scale (SGS) eddy viscosity, and turbine forces, approximately 15 TB (terabytes) and wind turbine data – including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB) – stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the giverny Python package, allowing remote users to query the database in Python or MATLAB (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et al. (2025).

17 WIND ENERGY↗

DOE OSTI2024

Baseline Characterization Database Verification Report ? NBG-17 Billet V104

The purpose of this report is to present data collected in the Baseline Graphite Characterization Program, which is directly tasked with supporting the Idaho National Laboratory’s (INL’s) research and development efforts on the Advanced Reactor Technologies (ART) Program. This program populates a comprehensive database that reflects the baseline properties of nuclear-grade graphite regarding individual grade, billet, and position within individual billets. The physical- and mechanical-property information being collected will be transferred to the Nuclear Data Management and Analysis System (NDMAS), and that database will help populate the handbook of property data available to member nations of the Generation-IV International Forum. Transfer of these data from the applicable technical lead to the dissemination databases available to other end users requires a full review of the test procedures and data-collection efforts through an analysis of the multiple summary spreadsheets and values being collected. This report represents the analysis for NBG-17 Billet V104 and facilitates release of associated data to the NDMAS custodians. Millions of raw data points have been collected during testing and quantification analyses for these billets. The summary scalar property values and supplementary traceability data are collected into comprehensive spreadsheets. Data sets are composed of single billets of graphite for any given grade, organized by mechanical test-specimen type, and further subdivided into individual spreadsheet tabs according to the specific test or evaluation being performed. A direct analysis of properties was not conducted, and this report does not provide information on the validity or performance characteristics of the graphite itself. Rather, this report is intended as a verification of the completeness of actual data collected in accordance with PLN-3467, “Baseline Graphite Characterization Plan: Electromechanical Testing,” [1] and PLN-3348 “Graphite Mechanical Testing” [2] and their representation of the measurement and test results with sole regard to the graphite billets under evaluation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

SG50 Data-format Specifications Document for the Automatically Readable, Comprehensive, and Curated Experimental Reaction Database MEDUSAL

The aim of this document is to lay out a first draft of the specifications for the MEDUSAL database (Machine-readable Experimental Data User App & Library) that is being described by OECD/NEA/WPEC SG-50. The EXFOR database (Otuka et al., 2014) has a format that is based on code-value pairs, and a significant portion of the information in the EXFOR entry is contained in free text sections. Several high-level requirements for the MEDUSAL database, as laid out in the Use Cases and Requirements Working Paper (citation), relate to the definition of the specifications

Nuclear Criticality Safety Program (NCSP)↗