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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Distinguishing Leptothrix and Sphaerotilus genera by an integrated genomic-phenotypic analysis supported by new Leptothrix genomes

The Sphaerotilus-Leptothrix group of bacteria includes one of the first described microorganisms, Leptothrix ochracea, an uncultured type strain, plus isolates of Leptothrix and Sphaerotilus. This group is unified by the ability to form sheaths and oxidize metals, although L. ochracea exhibits obvious ecological, morphological, and functional differences from the rest of Sphaerotilus-Leptothrix. Recently, there have been calls to combine the group into one genus, Sphaerotilus; however, these studies lacked adequate genomic representation of L. ochracea. Here, we present a comprehensive comparative genomic analysis of the Sphaerotilus-Leptothrix group, including expanded representation of L. ochracea, a closely related novel species, Leptothrix toolikensis, and two new isolates (Leptothrix mechoopdaensis). Analysis of 38 genomes resolves three phylogenetic and functional groups: the ochracea-type Leptothrix (Group 1), the mobilis-type Leptothrix (Group 2), and Sphaerotilus (Group 3). Group 1 genomes form a separate genus based on average nucleotide identity and alignment fraction. The genomes clearly diverge from the rest of Sphaerotilus-Leptothrix in phylogeny, size, and metabolic potential. Group 1 genomes are much smaller (2.59–3.04 Mb) than those of Groups 2 (4.55–6.06 Mb) and 3 (3.94–5.07 Mb), while encoding more metal oxidases and fewer carbohydrate-active enzymes. Group 2 clusters with Group 3 phylogenetically and is similar in organic carbon metabolisms but maintains more metal oxidation genes. Group 2 members lack homogeneity in phenotype and genotype, suggesting that additional isolates and genomes are needed for confident classification. However, Group 1 genomes (L. ochracea and L. toolikensis) show clear divergence, precluding their inclusion in Sphaerotilus and supporting the retention of the genus Leptothrix.

Leptothrix↗
DOE OSTI2025

Resilient State Recovery Using Prior Measurement Support Information

Resilient state recovery of cyber-physical systems has attracted much research attention due to the unique challenges posed by the tight coupling between communication, computation, and the underlying physics of such systems. By modeling attacks as additive adversary signals to a sparse subset of measurements, this resilient recovery problem can be formulated as an error correction problem. To achieve exact state recovery, most existing results require less than 50% of the measurement nodes to be compromised, which limits the resiliency of the estimators. In this paper, we show that observer resiliency can be further improved by incorporating data-driven prior information. Here, we provide an analytical bridge between the precision of prior information and the resiliency of the estimator. By quantifying the relationship between the estimation error of the weighted ℓ 1 observer and the precision of the support prior, this quantified relationship provides guidance for the estimator’s weight design to achieve optimal resiliency. Several numerical simulations and an application case study are presented to validate the theoretical claims.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

CO 2 Electrolysis Using Metal-Supported Solid Oxide Cells with Infiltrated Pr 0.5 Sr 0.4 Mn 0.2 Fe 0.8 O 3-$δ$ Catalyst

Electrochemical conversion of CO 2 to CO is demonstrated with symmetric-structured metal supported solid oxide cells (MS-SOC). Perovskite Pr 0.5 Sr 0.4 Mn 0.2 Fe 0.8 O 3-δ (PSMF) and Pr 6 O 11 catalysts were infiltrated into the MS-SOC cathode and anode, using 3 cycles with firing at 850 °C and 8 cycles with firing at 800 °C, respectively. Upon reduction during operation, the perovskite PSMF was transformed to Ruddlesden–Popper structure with a highly efficient electrocatalytic activity. The impact of operating temperature (600–800 °C) and overpotential (0–1.8 V) on the CO 2 conversion was investigated. The highest CO 2 conversion of 57.2% was achieved at 750 °C and 1.8 V. During extended operation for 150 h at 750 °C and 1.2 V, a cell demonstrated relatively stable performance, with initial current density of 535 mA cm -2 and CO 2 conversion of 23%. Degradation mechanisms were studied by posttest characterization.

25 ENERGY STORAGE↗
DOE OSTI2026

Decision Support System

Forest-based value chains involve decisions that begin at the landscape level and extend through processing, product manufacturing, and end-use markets. However, these decisions are often made independently across sectors, with limited visibility into how upstream resource conditions, incentives, and land management choices influence downstream production systems. In forested regions of the United States, wildfire risk, fragmented ownership, and uncertain markets for low-value residues complicate efforts to align extraction, processing, and utilization decisions. Without tools that link these stages, stakeholders may overlook opportunities to improve resource utilization or inadvertently shift impacts elsewhere in the value chain. This repository introduces a decision support system (DSS) that applies a system-impact-analysis approach to forest biomass residues and co-products. The framework integrates forest inventory data, geospatial resource assessments, and economic modeling to evaluate how biomass extraction decisions influence downstream product pathways. By linking regional feedstock avail- ability with market incentives and processing options—such as fuels, wood products, or soil amendments like biochar—the tool allows decision-makers to compare value chain outcomes across multiple utilization strategies.

Davis, Maggie [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

PaRSEC: Scalability, flexibility, and hybrid architecture support for task-based applications in ECP

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system’s adaptability and performance across varied computing environments.

Bouteiller, Aurelien↗
DOE OSTI2024

Advances in ArborX to support exascale applications

ArborX is a performance portable geometric search library developed as part of the Exascale Computing Project (ECP). In this paper, we explore a collaboration between ArborX and a cosmological simulation code HACC. Large cosmological simulations on exascale platforms encounter a bottleneck due to the in-situ analysis requirements of halo finding, a problem of identifying dense clusters of dark matter (halos). This problem is solved by using a density-based DBSCAN clustering algorithm. With each MPI rank handling hundreds of millions of particles, it is imperative for the DBSCAN implementation to be efficient. In addition, the requirement to support exascale supercomputers from different vendors necessitates performance portability of the algorithm. We describe how this challenge problem guided ArborX development, and enhanced the performance and the scope of the library. We explore the improvements in the basic algorithms for the underlying search index to improve the performance, and describe several implementations of DBSCAN in ArborX. Further, we report the history of the changes in ArborX and their effect on the time to solve a representative benchmark problem, as well as demonstrate the real world impact on production end-to-end cosmology simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Supporting Data for "Constraints on magnetism and correlations in RuO2 from lattice dynamics and Mössbauer spectroscopy"

Contents of this DOI are data for the research paper "Constraints on magnetism and correlations in RuO2 from lattice dynamics and Mossbauer spectroscopy" by the authors: George Yumnam, et. al. The dataset contains data from inelastic x-ray scattering measurements of RuO2 single crystals performed at the Advanced Photon Source in Argonne National Lab. This dataset also contains data from inelastic neutron scattering experiments of RuO2 powder performed at the ARCS spectrometer at Spallation Neutron Source at ORNL. Supporting theoretical calculations based on density functional theory with r2SCAN and DFT+U methods is also included in this dataset. Please see the README.txt files for more information of the dataset and file contents. For comments and questions, please contact: George Yumnam (yumnamg@ornl.gov) and/or Raphael P Hermann (hermannrp@ornl.gov)

density functional theory↗
DOE OSTI2025

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability: Supporting Data and Code

This repository contains R code and associated datasets for reproducing the analysis described in the manuscript titled “Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability” (DOI: 10.1029/2024JG008604). The provided scripts facilitate a comprehensive analysis of snow depth variability influenced by microtopography and vegetation distribution in a subarctic watershed. Included datasets are high-resolution spatial maps of snow depth, terrain elevation, vegetation height, and distance from shrubs taller than 1 meter, all formatted as text files (.txt). These data are fully describe in doi:10.15485/2316038. Users can adapt the provided R scripts to accommodate different data formats or larger spatial domains, noting that some output files may require modification due to their size.The code includes implementations for boosted regression tree analysis adapted from methods outlined in Elith et al. (2008). Users interested in understanding or modeling landscape-scale snow distribution patterns, particularly in Arctic or subarctic ecosystems, will find this package useful. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Files and scripts to support manuscript Needham et al. Canopy Gradients of Respiration

This dataset includes the parameter files, relevant output files, and scripts to perform analysis with Jupyter notebooks that support the manuscript Needham et al 2025 “Canopy Gradients of Respiration Drive Plant Carbon Budgets and Leaf Area Index.” We add functionality to the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) to allow flexible vertical gradients of leaf maintenance respiration (Rdark) and maximum carboxylation rate (Vcmax) through the canopy. We test the sensitivity of FATES to canopy gradients in Rdark, both in global simulations to assess broad scale impacts on leaf area index (LAI) and vegetation carbon, and in single site simulations where we assess impacts on plant functional type (PFT) competitive dynamics. Parameter files are netcdf files that can be converted to human readable .cdl files using NCO tools. Analysis scripts are Jupyter notebook files. These can be opened and run using the open source Jupyter notebook software. Model outputs are netcdf files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Supporting Growth of a Skilled Workforce in the Building Energy Efficiency Industry (Final Technical Report)

The Interstate Renewable Energy Council (IREC), having worked for well over a decade to develop national networks and best practices focused on attracting and training high quality workers for the clean energy industries, sought to address shortfalls in skilled workers who build, retrofit, operate, and maintain energy efficient buildings. Through this project, IREC created and promoted a Green Buildings Career Map (GBCM)—a career awareness and recruitment tool—that seeks to boost the nationwide growth of workers entering the energy efficiency (EE) industry. Working with a team of subject matter experts and our partner organizations—Building Performance Association (BPA), Building Performance Institute (BPI), Community Action Partnership (CAP), and the National Institute of Building Sciences (NIBS)—IREC produced an interactive, engaging career map to attract and motivate individuals into pursuing careers in energy efficiency, and in support of the Weatherization Assistance Program. The GBCM was designed for a broad audience including educators, career advisors, employers, policymakers, workforce professionals, and jobseekers who may otherwise have little or no awareness of the exciting and rewarding opportunities within targeted industry sectors. Most individuals seeking careers do not know about the breadth of careers awaiting them in the built environment and the same is true for most career and guidance counselors, educators, and parents. The GBCM provides this broad audience with a vision of the myriad jobs that could lead to a long-standing career in energy efficiency. The GBCM describes diverse occupations across the EE industry, charts possible progression between those occupations, and identifies the training, skills, and credentials necessary to do them well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Soil Gas Survey Results Supporting Groundwater Correction Action Plan (GCAP) Development for the Moab Site

A soil gas survey was performed at the Moab Uranium Mill Tailings Remedial Action (UMTRA) Project Site during the week of November 6, 2023. Soil gas surveys are used to characterize residual subsurface sources of volatile contaminants, such as volatile organic compounds, as well as contaminants that generate a surrogate indicator gas or otherwise influence soil gas composition. The primary objective of the Moab soil gas survey was to confirm, identify, quantify, and refine secondary contaminant source area locations for uranium and ammonium/ammonia (NH 4 + /NH 3 ) in the vadose zone and shallow groundwater. The overarching goal was to provide information to assist in developing the technical basis for the Groundwater Compliance Action Plan (GCAP). Specifically, the soil gas data will support the deployment of source control technologies; e.g., where supplementary capping, removal actions, or amendments might be beneficial.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analysis of Tank 38H (HTF-38-24-53, -56) and Tank 43H (HTF-43-24-54, -55) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory analyzed samples from Tank 38H and Tank 43H to support the Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous Tank 38H surface sample. The current Tank 38H subsurface sample shows similar Na, free hydroxide, and anions in comparison to the previous subsurface sample. However, the 38H subsurface sample shows lower concentrations of Al, Ca, Fe, Mn, and Si in comparison to the previous Tank 38H subsurface sample. Measurement of the wt.% insoluble solids in the Tank 38H subsurface sample and associated uncertainty analysis indicates that the calculated average wt.% insoluble solids is 0.45 ± 0.75 wt.%. Significant differences in the concentrations of major components between the Tank 38H surface and subsurface samples indicate significant stratification of solution species between these two locations within Tank 38H.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A Geodatabase Designed to Inform and Support Safe CO2 Transport-Route Planning

The National Energy Technology Laboratory developed the Carbon Capture and Storage (CCS) Pipeline Route Planning Database to inform safe and sustainable CO2 transport planning in support of decarbonization efforts. This comprehensive Esri Geodatabase contains over 90 GBs of data and 60+ spatial layers representing key considerations including natural hazards, infrastructure, energy, and social justice. Leveraging ArcGIS Pro, nationwide raster, and vector datasets containing millions of features were processed to be easily digestible for users and complex modeling software.

Romeo, Lucy↗
DOE OSTI2024

Supporting ARPA-E Power Grid Optimization (Final Report)

Pacific Northwest National Laboratory (PNNL), Arizona State University (ASU), Georgia Institute of Technology (Georgia Tech), Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), The University of Texas at Austin (UT), and the University of Wisconsin-Madison (UW-M) supported the ARPA-E Grid Optimization (GO) Competition by providing a common problem formulation, data format, datasets, evaluation mechanism, scoring, rules, and results that resulted in the awarding of $\$9.24$ million dollars to teams from academia, industry, and national labs for solving three sets of increasingly difficult non-linear, security- constrained AC Optimal Powerflow (AC-OPF) optimization problems in order to increase the efficiency of the US Electric Grid. It is estimated that a 1% increase in efficiency can save $\$1$ billion. Current industry practices typically use a linear DC model (DC-OPF) in order solve the OPF problem within the time constraints of the operation schedule. The GO Competition challenges the best power engineers, mathematicians, and computer scientists to make possible operational decisions based on accurate physical models. To accomplish this, the GO Competition created a series of Challenges and funded teams to produce the best solver. Challenge 1 was to solve the security constrained Alternating Current Optimal Power Flow (ACOPF) problem. Challenge 2 extended that to by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment (UC). Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. While Challenge 3 was being developed, the entrants were invited to find better solutions to the Challenge 2 synthetic datasets with no restrictions on time, hardware, or algorithms. The Challenge 2 solutions turned out to be very good. Challenge 3 expanded the Challenge 2 problem further by using multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. These problems included active bid-in demand and topology optimization. Together the Challenges used nearly 30 million CPU hours. Since each team was working on the same problem, using the same data, and running on the same hardware, fair comparisons could be drawn as to the best solver. The datasets were varied enough, however, that the best solver for one dataset was not necessarily the best at another, so cumulative scores were used. The process was managed by the PNNL maintained website https://GOCompetition.energy.gov, where Entrants could find information about the problem, the data, the rules, submit their solver for evaluation, and see the scores of all the competing teams on a Leaderboard. Interest was world-wide but only American teams were eligible for prizes. The Competition has produced 34 journal articles 115 papers and been cited over 500 times in the literature, including 12 dissertations (4 from foreign countries; Columbia (2), Germany, and Italy) and 3 from the DOE ExaScale project. Software developed by Pearl Street Technologies for Challenges 1 and 2 is now deployed by Southwest Power Pool (SPP) and Midcontinent Independent Service Operator (MISO). Other teams have received inquiries from venture capitalists. Google DeepMind has thanked the Competition for making the datasets developed for the Competition public. They are using it to train machine learning models. The larger datasets have billions of unknowns to be solved for, but only a small percent matter in the final solution. Knowing what unknowns are important can dramatically speedup the solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

LBNF Internal Cryogenics Supports Design

This poster presents requirements, methodology, and results of the LBNF Internal Cryogenics External Supports conceptual design. Forces and flexibility analyses, membrane cryostat restrictions, and simplicity were all taken into consideration for the design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Support of domain decomposition-based solvers in Chroma

In multilevel integration, the correlation functions are decomposed into factors that depend only on fields localized into lattice subdomains so that they can be independently integrated. Although the standard formulation of the LQCD action is not local in the presence of fermions, past studies have shown approximations of the quark propagator and the fermionic determinant dependent on the gauge fields within specific subdomains can still be effective. We will present our current progress in supporting domain decomposition within Chroma, which is necessary for multilevel integration approaches. The efforts are focused on extending the code base to efficiently manipulate subdomains for lattice fields and operators and performing inversions and eigendecompositions within domains.

Alcalde, Eloy Romero↗