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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine learning reveals strong grid-scale dependence in the satellite N d –LWP relationship

The relationship between cloud droplet number concentration ( N d ) and liquid water path (LWP) is highly uncertain yet crucial for determining the impact of aerosol-cloud interactions (ACI) on Earth's radiation budget. The N d -LWP relationship is examined using a machine learning (ML) random forest model applied to five years of satellite data at grid resolutions ranging from 10° to 0.05° in 12 distinct regions. In the subtropics, the shape of the N d -LWP relationship switches from an inverted-V at 1° grid-resolution to an “M” shape at 0.1° resolution with decreased $\frac{\textrm{dln⁡LWP}}{\textrm{dln⁡}N_d}$ sensitivity. Tropical and midlatitude regions generally show a more positive sensitivity. Cloud sampling and filtering also influence this slope, wherein the exclusion of thin clouds, as commonly performed to reduce retrieval uncertainty, leads to strongly negative sensitivity across all regions. Precipitation is primarily responsible for driving the strength of the sensitivity, with strong positive slopes in raining clouds and negative and/or neutral responses found in non-raining clouds. A new method to compute radiative forcing from the ML model shows a robust Twomey radiative forcing across all regions and grid resolutions. However, LWP and cloud fraction adjustments to the radiative forcing, which are ∼50 % or smaller than the Twomey effect, decrease to negligible values with higher spatial resolution data. As Earth system models move toward higher spatial resolutions in the future, evaluating the LWP and CF adjustment contributions to the radiative forcing budget at these finer resolutions will be essential for evaluation and model development.

Aerosol-Cloud Interactions↗
DOE OSTI2026

Life Cycle Inventories and Data Gap Analysis for Rare Earth Elements: Neodymium and Dysprosium from Mining to Magnets

The United States demand for Neodymium-Iron-Boron (NdFeB) magnets, produced from rare earth elements (REEs) such as (Nd) and Dysprosium (Dy), far exceeds its nascent domestic production capacity, rendering it reliant on vulnerable global supply chains dominated by China. To guide research and development investments in securing U.S. REE supply, defensible benchmark metrics across environmental, economic, and social dimensions are needed. In this study, we built globally-representative, process-based cradle-to-cradle life cycle inventories for Nd and Dy in NdFeB magnets lifecycles, encompassing primary material acquisition, beneficiation, smelting and refining, metal processing, specialty alloy and chemical transformation, subcomponent manufacturing, consumer application (use phase) and end-of-life management. We carried out detailed literature review, and applied process engineering principles to build industry-representative upscaled life cycle inventories for both metals. We used these models to conduct bottom-up literature review and gap analysis on existing literature, compilation of data sources for each life cycle stage (and transformations where necessary), and a preliminary technoeconomic analysis (TEA)/life cycle costing analysis (LCCA). Findings from this work emphasize the need for metal specific, representative REE LCIs to establish robust benchmarks for advancing sustainable REE technologies and guiding R&D in REE supply chains.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

esm_watermasses

A water mass analysis package for gridded ocean and atmospheric data and Earth system model output

Moore-Maley, Ben [@SciDAC-ImPACTS @E3SM-Project @M↗
DOE OSTI2025

Search for dark matter from the center of the Earth with 10 years of IceCube data

The nature of dark matter remains unresolved in fundamental physics. Weakly Interacting Massive Particles (WIMPs), which could explain the nature of dark matter, can be captured by celestial bodies like the Sun or Earth, leading to enhanced self-annihilation into Standard Model particles including neutrinos detectable by neutrino telescopes such as the IceCube Neutrino Observatory. This article presents a search for muon neutrinos from the center of the Earth performed with 10 years of IceCube data using a track-like event selection. We considered a number of WIMP annihilation channels (χχ→τ+τ-$$\chi \chi \rightarrow \tau ^+\tau ^-$$/W+W-$$W^+W^-$$/bb¯$$b\bar{b}$$) and masses ranging from 10 GeV to 10 TeV. No significant excess over background due to a dark matter signal was found while the most significant result corresponds to the annihilation channel χχ→bb¯$$\chi \chi \rightarrow b\bar{b}$$ for the mass mχ=250$$m_{\chi }=250$$ GeV with a post-trial significance of 1.06σ$$1.06\sigma $$. Our results are competitive with previous such searches and direct detection experiments. Our upper limits on the spin-independent WIMP scattering are world-leading among neutrino telescopes for WIMP masses mχ>100$$m_{\chi }>100$$ GeV.

Abbasi, R↗
DOE OSTI2025

Data Files for Runoff Evaluation in an Earth System Land Model for Permafrost Regions

Modeling of hydrological runoff is essential for accurately capturing spatiotemporal feedbacks within the land–atmosphere system, particularly in sensitive regions such as permafrost landscapes. However, substantial uncertainties persist in the terrestrial runoff parameterization schemes used in Earth system and land surface models. This is particularly true in permafrost regions, where landscape heterogeneity is high and reliable observational data are scarce.This data set includes all files that were produced and applied in the paper Runoff Evaluation in an Earth System Land Model for Permafrost Regions [Xiang et al. in review]. The paper is in review as of July 1 2025 in Geoscientific Model Development (GMD). In this study, we evaluate the performance of runoff parameterization schemes in the Energy Exascale Earth System Model (E3SM) land model (ELM). Our proposed framework leverages simulation results from the Advanced Terrestrial Simulator (ATS), which is a physics-rich integrated surface/subsurface hydrologic model that has been successfully evaluated previously in Arctic tundra regions. We used ATS to simulate runoff from 22 representative hillslopes in the Sagavanirktok River basin, located on the North Slope of Alaska, then compared the output with ELM’s parameterized representation of total runoff. This dataset contains 2 figure image files (*.png, *jpg) that describe the study site and methods, as well as folders (Figure*.zip) that contain the associated data files (*.csv, *.dat) and python code notebooks (*.ipynb) for figures 3-7 in the paper. Jupyter notebook (*.ipynb) files that produce the figure files using the associated data files will run within a python environment configured with Jupyter Lab or Notebook packages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗
DOE OSTI2024

Evaluation of dynamical downscaling in a fully coupled regional earth system model

A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere–land–ocean–sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the annual means. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Baseline Climate Variables for Earth System Modelling

The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used elements of the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive. Successive phases of CMIP have supported strong results in science and substantially influence international climate policy formulation. This paper responds to both interest in exploiting CMIP data standards in a broader range of climate modelling activities and a need to achieve greater clarity about the significance and intention of variables in the CMIP Data Request. As Earth system modelling archives grow in scale and complexity, there are emerging problems associated with weak standardisation at the variable collection level. That is, there are good standards covering how specific variables should be archived, but this paper fills a gap in the standardisation of which variables should be archived. The ESM-BCV list is intended as a resource for ESM intercomparison projects (MIPs) developing requests to enable greater consistency among MIPs and as a reference for modelling centres to enhance consistency within MIPs. Provisional planning for the CMIP7 Data Request exploits the ESM-BCVs as a core element. The baseline variable list includes 98 variables which have modest or minor data volume footprints and could be generated systematically when simulations are produced and archived for exploitation by the World Climate Research Programme (WCRP) community. A further 35 variables are classed as “high volume” and are only suitable for production when the resource implications are justified.

Juckes, Martin [University of Oxford (United Kingd↗
DOE OSTI2024

Rare Earth Carbide (Nd-C and Ce-C) Synthesis and Characterization to Inform Phase Equilibrium in Advanced Nuclear Fuels

As advances are being made regarding the performance of nuclear fuels, uranium carbides, and composites, such as (U,Zr)C and UO2 + UCx, have recently gained significant interest for deployment in nuclear space propulsion and high temperature gas-cooled reactors, respectively. However, the phase equilibria of several fission products in carbide systems remain unknown and may impact the overall fuel performance, specifically for particle nuclear fuels that are designed for commercial nuclear energy. Furthermore, comprehensive thermodynamic data on Rare Earth (RE) carbides, such as the Nd-C and Ce-C binary systems, remain limited. Presented in this study are the synthesis methods and characterizations of several Nd-C and Ce-C compositions. The findings from this research provide insights on the stability of RE-C binaries that form in irradiated nuclear fuels and address a critical knowledge gap in the current state of thermodynamics for two key RE-C systems.

Cavazos, Steven J. (ORCID:0009000130329363)↗
DOE OSTI2026

Urban Parameters Los Angeles County 100m version 2

132 Urban parameters based on building physical dimensions and location were generated for the city of Los Angeles at 100m resolution using the NATURF model. To use the binary file with WRF, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way NUDAPT44 would be accessed. The kmz file can be visualized on Google Earth.

Sweet-Breu, Levi [Baylor University]↗
DOE OSTI2025

Code Release for “Unlocking Extreme Space Weather through Advanced Modeling of Legacy Vela Spacecraft” ER

The software being developed for this project has two mains aims. First, a Bayesian Model Calibration (BMC) procedure is being developed to calibrate a spallation model that simulates protons hitting a spacecraft orbiting earth to real data. The procedure will be developed for general data (there is no data release requested as part of this code release). Second, an inverse physics modeling task is being undertaken to map the number of resulting neutrons observed from this process to the expected number of protons that hit the model. This second task is of statistical interest; to publish on it, the code will need to be open source.

Murph, Alexander↗
DOE OSTI2025

Opening doors to physical sample tracking and attribution in Earth and environmental sciences

Physical samples and their associated data and metadata underpin scientific discoveries across disciplines and can enable new science when appropriately archived. However, there are significant gaps in current practices and infrastructure that prevent accurate provenance tracking, reproducibility, and attribution. For most samples, descriptive metadata are often sparse, inaccessible, or absent. Samples and associated data and metadata may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkage or provenance tracking as new information is generated over time. The Earth Science Information Partners (ESIP) Physical Samples Curation Cluster has therefore developed guidance for scientific authors on ‘Publishing Open Research Using Physical Samples.’ This involved synthesizing existing practices, gathering community feedback, and assessing real-world examples. We identified improvements needed to enable authors to efficiently cite and link Earth science samples and related data, and track their use. Our goal is to help improve discoverability, interoperability, and reuse of physical samples, and associated data and metadata. Though primarily focused on the needs of Earth and environmental sciences, these guidelines are broadly applicable.

58 GEOSCIENCES↗
DOE OSTI2026

Geology of the One Earth Energy Site

The One Earth Energy site is one of two sites in the Illinois Storage Corridor (ISC) project. The objectives of the ISC project is to accelerate commercial deployment of carbon capture utilization and storage at two individual sites and receive approvals for Underground Injection Control (UIC) Class VI permits for construction at each site. At the One Earth Energy site, an extensive data collection program was undertaken, which included the drilling of a test well (One Earth Energy #1 [OEE #1]), four 2D seismic lines, and a small 3D seismic survey. The OEE #1 well was drilled in 2022 and acquired extensive core, log, and testing data to characterize the subsurface geology of the site. Coring was focused on the storage interval, the Mt. Simon Sandstone, and the confining interval, the Eau Claire Formation. The core and log data were used to evaluate the sedimentology and sequence stratigraphy, as well as to develop the conceptual geologic model. This report includes the geological summaries of the Mt. Simon Sandstone and the Eau Claire Formation. The extensive analysis of the log data is included in the petrophysical section, showing ranges of porosity, estimated pore size, and the mineral content of selected zones in the well. The separate petrographic technical report entitled “Petrographic and Advanced Geologic Characterization Report on One Earth Energy #1 (API# 1211325373)”, report number DOE-UIUC-0031892-04, details thin section point-counting analysis that includes mineralogical and pore space analysis, including grain size analysis, annotated thin section photomicrographs, scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS), and statistics of grain size analysis on Mt. Simon thin sections from OEE #1. The final OEE #1 well data to be included in this geology report is the routine core analysis of both whole core plugs and rotary sidewall core plugs. In addition to the OEE #1 well, four 2D seismic lines and a small 3D survey were acquired as part of the overall subsurface geological characterization. This geology report references the seismic interpretation report, entitled “One Earth Energy Site Seismic Interpretation Task 5.0”, report number DOE-UIUC-0031892-07. This report details the stratigraphic and structural interpretation of the 2D and 3D seismic data acquired at the One Earth Energy site. The 2D seismic data was acquired in 2019 and 2021, and the 3D survey was acquired in 2022. The objectives of the seismic programs were to contribute to the subsurface characterization of the Mt. Simon-Eau Claire Storage Complex by evaluating the continuity of potential storage reservoirs and containment intervals across the project area, and to determine if any geologic features are present that would increase containment risk to the proposed carbon storage project.

09 BIOMASS FUELS↗
DOE OSTI2025

Comparisons of the v11.1 Orbiting Carbon Observatory‐2 (OCO‐2) X CO2 Measurements With GGG2020 TCCON

The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first Earth observation satellite mission dedicated to studying the sources and sinks of carbon dioxide (CO 2 ) on a global scale. The observations of reflected sunlight are inverted in a retrieval algorithm to produce estimates of the dry air mole-fractions of CO 2 (X CO2 ). The OCO-2 Level 2 data release, version 11.1 (v11.1) retrievals from the Atmospheric Carbon Observations from Space (ACOS) algorithm, includes significant improvements in the X CO2 data product compared to older OCO-2 data versions. This work compares the v11.1 X CO2 from OCO-2 against X CO2 estimates collected from a global ground-based network known as the Total Carbon Column Observing Network (TCCON), OCO-2's primary validation source. The OCO-2 project provides a version of the Level 2 data product, called “lite” files that include calibrated and bias-corrected XCO2 values, accessible together with all OCO-2 data products through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). This work shows that OCO-2 X CO2 observations made between September 2014 and December 2023, after quality filtering and the application of an averaging kernel correction, agree well with coincident TCCON data for all OCO-2 observational modes of land (nadir, glint, target) and ocean (glint). The aggregated, bias-corrected, and quality-filtered absolute average bias values are less than or equal to 0.20 parts per million (ppm) globally for all OCO-2 observation modes, where the biases do not indicate a statistically significant time dependence. The land nadir/glint mode has the lowest bias value of −0.03 ± 0.85 ppm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Surrogate modeling of the leaching process in a rare earth elements recovery plant

The data are summarized in the slides for a poster as presented at the 2024 AIChE annual meeting in San Diego, California, USA. The slides summarize our work on the PrOMMiS project over the past year. The slides describe the systematic design and optimization of a flowsheet for the recovery of critical minerals and rare earth elements. Then, it summarizes the results of our benchmarking of surrogate modeling methodologies for the optimization of these flowsheets.

Fardis, Dimitrios↗
DOE OSTI2025

A genomic view of Earth’s biomes

Microorganisms are essential to all life on Earth through critical roles in key biological processes and diverse interactions with other organisms that shape ecosystems, drive biogeochemical cycles and influence both human health and environmental health. High-throughput sequencing from environmental samples has revolutionized the understanding of microbial diversity and functions. With vast amounts of genomes now available across Earth’s biomes, these data provide a blueprint of microbial life that can be harnessed for a more holistic understanding of microbiome structure and function across the various ecosystems on Earth. Here we review the application of genome-centric approaches, including recent advances in single-cell sequencing and functional profiling, to survey microbial and viral diversity. Furthermore, we highlight some of the most impactful evolutionary and functional discoveries, explore the spatial diversity and temporal dynamics of microorganisms across diverse environments, and discuss genome-enabled insights into host-associated microorganisms.

Ecology↗
DOE OSTI2025

NCAR-RAL Surface Hydrometeorological Observation Network Data for LASSO-CACTI Overview Paper

This data set contains the 15 minute resolution surface meteorology and soils data from the 15 NCAR/RAL weather stations that were operated around central Argentina during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations) Extended Observing Period (EOP). Data providence, citation, and acknowledgement This ARM data set is a copy of v1.0 of the NCAR data set obtained in June 2024 from https://doi.org/10.26023/KW8Z-F2WX-H0Y. The citation for the original data source is: Gochis, D., et al. 2019. NCAR-RAL Surface Hydrometeorological Observation Network Data. Version 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/KW8Z-F2WX-H0Y Accessed June 2024. In addition to the citation reference and any other acknowledgements, please acknowledge NCAR/EOL in your publications with text such as: “Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/”

air temperature↗