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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SPRUCE: Peat Core Sample Collection Metadata, Marcell Experimental Forest, Minnesota, August 2024

This data set contains metadata associated with peat core samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2024. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored at Oak Ridge National Laboratory and may be available for further analysis. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B00VQ. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR. Note: Only dried and ground material from C Cores are available for new analysis.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗
DOE OSTI2026

SPRUCE Peat Core Sample Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with peat core samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B05LW. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > TERRESTRI↗
DOE OSTI2025

SPRUCE: Shrub-Layer Vegetation Biomass Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with shrub-layer vegetation samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. See below under 7 Sample Access. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B069L. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗
DOE OSTI2026

Knowledge Graph of RB-Tnseq Data from Fitness Browser (KP-DP1)

Motivation: Predicting microbial gene fitness across environmental conditions remains a central challenge for predictive phenomics and autonomous experimentation. Fitness assays generate large volumes of genotype–phenotype measurements difficult to integrate with experimental metadata and biological function in a form that supports mechanistic reasoning. Knowledge graphs offer a semantic framework for unifying modalities and enabling context-aware inference. Results: We build GIMME (Graph Inference for Microbial Metabolism Exploration), a semantically grounded knowledge graph that unifies gene fitness measurements spanning 10 Pseudomonas species with experimental metadata and biological context. Media are decomposed into chemical components and experiments carry structured links to natural-language descriptions. The resulting graph supports two inference modes: (1) symbolic graph traversal to surface candidate gene–environment and gene–chemical associations, and (2) learned inference using heterogeneous graph neural networks that propagate information across neighborhoods. We formulate link regression over (gene, media, experiment) triplets, combining learned gene embeddings with pretrained LLM sourced text embeddings of node descriptions to predict gene fitness. We then augment a baseline MLP with an auxiliary message-passing encoder (GraphSAGE/GAT) that propagates information over gene–protein–function and media–chemical subgraphs, and fuse the two pathways with a gated residual connection. This approach produces strong agreement with held-out fitness measurements (GraphSAGE Pearson r 0.74) while also highlighting inference challenges in extreme-fitness regimes. We aggregate GAT edge-attention weights by relation type and layer to estimate which biological and environmental relations most influence fitness predictions. Conclusion: This work explores using knowledge graphs as “context graphs” for microbial phenotype prediction. They provide a rich substrate which enables explainable retrieval of supporting evidence, and provides a natural bridge to autonomous workflows that prioritize the next experiment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

RhizoGrid Indexed Sorghum Rhizosphere Multi-Omics

PerCon SFA project data dentification of spatially resolved biomarkers of drought in Sorghum bicolor rhizosphere molecular-microbe interactions using a novel root cartography "RhizoGrid" system for sampling plants under drought and control conditions across 10 equally sized root zone environments (4 quadrants each). Each quadrant was sampled and processed for 16S amplicon, metabolomics, and X-ray computed tomography (XCT). Data download includes experimental metadata and results files for 16S rRNA sequence analysis of microbial community assembly (processed data files), liquid chromatography mass spectrometry (LC-MS) metabolomics analysis of microbial community root exudates (processed data files), X-ray computed tomography (XCT) spatial gradient analysis (raw and processed data files) of microbial community composition, and related computational modeling outputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PPI DataHub Project Data Package: S. elongatus PCC 7942 Limited Proteolysis and Thermal Proteome Profiling Structural Proteomics (JM-PB-DP3)

The purpose of this experiment was to investigate structural alterations in proteins involved in central carbon metabolism and photosynthetic electron transfer pathways in Synechococcus elongatus PCC 7942. Sample data was obtained from S. elongatus cell lysates using three complementary mass spectrometry (MS) techniques using limited proteolysis (LiP-MS), thermal proteome profiling (TPP-MS), and redox enrichment (Redox-MS) in evaluating alterations solvent accessibility and structural stability caused by light perturbation at the molecular level. Experimentally processed sample data for LiP and TPP proteomic datasets were derived from the same cell culture stock, prepared simultaneously in parallel, and acquired by mass spectrometry. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files, computed outputs, and supporting metadata materials. Experimental samples processed for LiP-MS label-free quantification (LFQ) or TPP-MS tandem mass tag (TMT) 10-plex were acquired using a Q-Exactive HF-X mass spectrometer and processed/compiled using either MSGF+ (v2024.03.26) or ​​​​PlexedPiper for proteome evaluation. Additional software supporting downstream proteomic analysis include FragPipe (v.4.0), MSFragger (v.22.1), and an adapted Microbial Isolate LiP Analysis Workflow (located at Zenodo). Processed proteomic data downloads include a sample naming key, normalized quantification results files, and processed protein annotated abundance files.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Universal Workflow Language and Software Enable Geometric Learning and FAIR Scientific Protocol Reporting

Written language and conventional data structures for representing scientific procedures suffer from low process detail, often fail to accurately represent protocols, and lack universality. New strategies for the handling of experimental data are needed to provide viable process information for both humans and machines. In this work, we present the universal workflow language (UWL) and interface (UWLi). UWL is a findable, accessible, interoperable, and reusable (FAIR)-compatible, graph-based data architecture that can capture arbitrary scientific procedures through workflow representation, and UWLi is an accompanying software package for building, manipulating, and interpreting UWL entries. The UWL format was found to be highly effective in identifying deficiencies in the reported process details of high-impact, peer-reviewed scientific journals, and in simulated scenarios, the graph format was shown to be more effective than conventional methods in predictively modeling the outcome of diverse scientific protocols. Implementation of UWL could enable more accurate scientific communication and more impactful process datasets.

14 SOLAR ENERGY↗
DOE OSTI2025

Rhodotorula toruloides Nitrogen Limitation PTM Profiling Multi-Omics (TZ-DP1)

The purpose of this experiment was to evaluate the regulatory stress response of Oleaginous yeast species Rhodotorula toruloides NBRC 0880 (JGI strain IFO0880 v4.0) under nitrogen-rich and nitrogen-limited conditions over time. Time course experimental samples (0, 24, 48, and 72 hours after inoculation) were prepared using a semi-automated multi-PTM proteomic approach, using tandem mass tag 18-plex (TMT18), and lipidome remodeling for downstream multi-omics analysis. Processed datasets are openly accessible from PNNL DataHub and contain secondary processed proteomic (redox, phospho, and global TMT) and lipidomic (positive and negative ion mode) results files and experimental design metadata.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Data from a four-day long microcosm experiment addressing the destabilization of artificial mineral-associated organic matter by model root exudates embedded in a soil matrix from the Rocky Mountain Biological Laboratory (Gothic, CO, USA), 2019

This dataset provides data collected during a four-day long laboratory soil microcosm experiment testing the efficacy of root exudate-driven mineral-associated organic matter destabilization. This dataset contains four data files in comma-separate values (*.csv). The files provide the metadata and the experimental results on microbial respiration, MAOM-derived respiration, and sequential mineral-extractions. This data was used to produce the figures in Bölscher et al., 2026. The results of the experiment can be found in the open access article Bölscher et al., 2026 (https://doi.org/10.1016/j.soilbio.2026.110276). Abstract: Mineral-associated organic matter (MAOM) is often considered stable, but root exudates can destabilize MAOM via various pathways. Theory and model system studies suggest that direct MAOM destabilization by strong ligands, like oxalic acid, or reducing agents, like catechol, is more effective than indirect, microbial-mediated MAOM destabilization, stimulated by less reactive compounds like glucose. Here, we demonstrate that the presence of a soil matrix alters the efficacy of exudate-driven MAOM destabilization pathways. Glucose and catechol destabilized significantly greater amounts of MAOM from ferrihydrite and aluminum hydroxide (Al (OH)3) embedded in a soil matrix than oxalic acid. Our findings indicate that indirect, microbial-mediated MAOM destabilization may play a larger role than direct MAOM destabilization in soil environments.

Destabilization↗
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

SPRUCE Air 13C and 14C Isotopes, Marcell Experimental Forest, Minnesota, 2016-2025

This data set reports 13C (carbon) and 14C signatures of air from Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental study plots located in the S1-Bog at the Marcell Experimental Forest in northern Minnesota from 2016-2025 (2016-04-13 to 2025-09-24). Air measurements were collected approximately five times throughout each active growing season beginning in 2016 and included the 10 SPRUCE experimental plots (Plots 4, 6, 8, 10, 11, 13, 16, 17, 19, and 20) two ambient co-located ambient plots (Plots 7 and 21) and a site at the Marcell Experiment Station’s S2-Bog meteorological station (MET) located 1.7 km northeast of the SPRUCE experimental site on the S1-Bog. Air samples were assessed for both 13C- and 14C-CO2 (carbon-carbon dioxide) signatures. 13C and 14C isotopic signatures can be used in end-member analysis and C-cycle models to track the movement of C within the experimental ecosystem, calculate turnover times within plant tissues, and to test mechanisms used in models. This dataset contains one data file in comma separate (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

SPRUCE Methane Transport in Plants at S1 Bog, Marcell Experimental Forest, Minnesota, 2017-2019

This data set contains measurements of methane (CH4) transport by plants (both ground-layer and trees) and diffusion, as well as whole-plot emissions, taken in September 2018 and June 2019 in S1 Bog outside of the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experimental enclosures. Additionally, CH4 and carbon dioxide (CO2) stable isotope data in porewater and atmospheric emissions were taken in July 2017 in the SPRUCE enclosures to explore the relative magnitude of CH4 oxidation. Episodic ebullition rates for S1 Bog are taken from Gill et al. (2017). Methane transport is an important component of many ecosystem models of peatlands. The results were compared to two methane models that have been developed for the SPRUCE project, ELM-SPRUCE (Earth Land Model) and TECO_SPRUCE (Terrestrial ECOsystem model). This dataset contains six data files in comma separate (.csv) format. Additional metadata are provided: six data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

SPRUCE Whole Ecosystem Warming (WEW) Environmental Data and Water Table Summaries, Marcell Experimental Forest, Minnesota, 2015-2024

This data set contains observations of photosynthetically active radiation (PAR), precipitation, soil temperature, soil volumetric water content, air temperature, relative humidity, and normalized water table depth that are summarized on a daily, weekly, monthly, and annual basis for each of the SPRUCE plots. Observations span 2015-2024. This dataset draws on several datasets (Hanson et al. 2016; Hanson et al. 2020; and Warren, unpublished data) and compiles these environmental observations into useful formats for data analysis. These environmental metrics can be used to understand the environmental conditions inside SPRUCE environmental chambers throughout the durations of the experiment and can be paired with other data for modeling and analysis. R code used to generate these files is provided as part of the data package. This dataset contains four data files in comma separate (.csv) format and a compressed folder (*.zip) containing three R (*.r) scripts. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. User note: Users must cite the original dataset/s along with this dataset when publishing any analyses using this dataset. Details on the dataset used to compile each variable are available in the header row of the files and in the user guide.

air temperature↗
DOE OSTI2025

SPRUCE Surface N2O fluxes measured with LI-7820, 2024

This dataset contains N2O (nitrous oxide) efflux rates measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements were made manually with a LiCor N2O/H2O analyzer (LI-7820) and paired SmartChamber (LI-8200-01S) in June, August, and October (2024-06-24 to 2024-10-22). During each measurement, the SmartChamber was placed on 8” PVC collars that were installed in May 2024. N2O flux was derived from 10-minute flux measurements processed using SoilFluxPro software (v5.3.1) and fit to a linear model. Model slope and R2 are reported along with soil water, soil temperature, and air temperature observations made with SmartChamber sensors. N2O is a gaseous N species formed during the microbial processes of denitrification and ammonia oxidation, and is a powerful greenhouse gas. This dataset contains one data file in comma-separate values (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SPRUCE Aboveground Vegetation Coverage in Root Ingrowth Core Plots, Marcell Experimental Forest, Minnesota, August 2022

This dataset contains vegetation survey measurements from root ingrowth core plots (Määttä et al. 2025) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. Vegetation surveys were conducted in 0.25 meter2 plots containing root ingrowth cores on August 8th and 9th, 2022 (2022-08-08 to 2022-08-09). The warming and elevated carbon dioxide (CO2) treatments in the dataset include the full treatment gradient: +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +2.25 degrees C (+0 and +500 ppm), +4.5 degrees C (+0 and +500 ppm elevated CO2), +6.75 degrees C (+0 and +500 ppm) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows. This dataset includes measurements of the height and absolute coverage (%) for each vascular plant and moss species, as well as organic litter and dead overstory vascular plants, and the distance from the grid center to the nearest tree and the species of the nearest tree. These data were used as species-specific aboveground plant metadata for assessing the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2025

SPRUCE Redox-Active Subsurface Organic Matter, Marcell Experimental Forest, Minnesota, 2023

This dataset contains measurements that report on the effects of the SPRUCE experimental treatments on redox-active organic matter (RAOM) reduction (Valenzuela and Cervantes, 2021). Measurements occurred at the SPRUCE Experiment site in the Marcell Experimental Forest in northern Minnesota, USA. This work is also a follow-up to Rush et al. (2021a) which investigated effects of temperature on RAOM reduction after two years of experimental warming (Rush et al. 2021b). This follow-up dataset addresses two main questions; (i) How does warming and elevated carbon dioxide (CO2) directly affect in situ RAOM reduction, and subsequent methane (CH4) and CO2 production, across the peat depth profile? and (ii) How has long-term warming and elevated CO2 changed the total RAOM pool, and subsequent CH4 and CO2 production, across the peat depth profile? This dataset reports electron shuttling capacity (a proxy for RAOM reduction; Keller, and Takagi, 2013) and carbon dioxide (CO2) and methane (CH4) concentrations both in one-week in situ incubations (2023-05-31 to 2023-08-01) and 42-day laboratory incubations from peat collected in 2023 (2023-05-31 to 2023-06-26). Laboratory incubations also measured acetate concentrations. The 2023 laboratory incubations were also compared with laboratory incubations conducted on peat collected in 2016 (Rush et al. 2021b). This dataset contains three data files in comma-separate (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

exfor_client

A lightweight Python client and CLI for interacting with the [EXFOR Web API](https://nds.iaea.org/exfor/x4guide/API/). This tool enables searching, retrieving, and parsing experimental nuclear data — including uncertainties, covariance information, and metadata — while preserving provenance.

Grosskopf, Mike [Los Alamos National Laboratory]↗