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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Technical Report on Adjoint Waveform Tomography of East Asia for Improved Waveform Prediction

We present a preliminary version of the East Asia Tomography (EAT) model, an adjoint waveform tomography model of East and Southeast Asia. We used SPiRaL (Simmons et al., 2021) as our starting model and source parameters for 250 earthquakes from the Global Centroid Moment Tensor catalogue (Ekström et al., 2012). Over 198 iterations, we have iterated the EAT model down to a minimum period of 35 seconds. We plan on continuing our iteration technique down to 30 seconds period before updating our misfit function to use a normalized cross correlation-based misfit functions (e.g., Tao et al., 2018) to better constrain Earth structure. We hope to iterate the current extent of the model to 25 seconds minimum period before iterating to shorter periods for a smaller subregion of the full model.

58 GEOSCIENCES↗
DOE OSTI2025

Prototype Hanford Barrier Performance Monitoring Report: Fiscal Year 2024

This report provides an annual update on performance monitoring of the Prototype Hanford Barrier (PHB) at the Hanford Site. The PHB is part of a long-term study that serves as the scientific basis for many of the evapotranspiration-capillary barrier designs currently used globally and for future engineered barrier designs planned for remedial actions over waste and demolition sites at the Hanford Site. The PHB allows us to identify potential future issues and develop better monitoring techniques before these engineered barriers are constructed. Surface barriers like the PHB are essential for preventing water infiltration and curbing the spread of contaminants to groundwater. Effective monitoring of soil moisture levels above and below these barriers is crucial given that performance metrics could span up to 1,000 years. From July 2023 to June 2024, the water flux (as measured by tipping buckets) through the 2-m-thick silt loam layer of the PHB – a fine silty material that stores water under high capillary tension – remained well below the 0.5-mm-per-year performance threshold, demonstrating its effectiveness in preventing water penetration. In 2024, degraded tipping bucket gauges were replaced to ensure the accuracy of future data. Additionally, neutron probes revealed that the wetting front from the rainy season only penetrated to a maximum depth of 1.2 m into the silt loam. This further demonstrated the barrier's efficiency, as the wetting front did not fully penetrate the 2-m-thick capillary barrier. The western gravel slope of the PHB, composed of Hanford Site pit gravel of varying sizes, demonstrated low flux rates. In contrast, the eastern riprap slope exhibited higher flux rates. Zhang (2017) found that the riprap side slope of the PHB had the highest drainage rates in January and the lowest in late summer or early fall, indicating significant summer evaporation. Drainage rates increased significantly under enhanced precipitation conditions, far exceeding the design criterion, which could lead to water infiltration into the waste zone. The study introduced the “edge effect,” where elevated drainage rates from the riprap may migrate laterally beneath the barrier, compromising its ability to isolate waste, and recommended expanding the barrier and conducting further research to mitigate this issue. This report provides a review on surface barrier edge effects and their potential impact to subsurface contaminant migration.

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

The Science, Engineering, and Validation of Marine Carbon Dioxide Removal and Storage

Scenarios to stabilize global climate and meet international climate agreements require rapid reductions in human carbon dioxide (CO 2 ) emissions, often augmented by substantial carbon dioxide removal (CDR) from the atmosphere. While some ocean-based removal techniques show potential promise as part of a broader CDR and decarbonization portfolio, no marine approach is ready yet for deployment at scale because of gaps in both scientific and engineering knowledge. Marine CDR spans a wide range of biotic and abiotic methods, with both common and technique-specific limitations. Further targeted research is needed on CDR efficacy, permanence, and additionality as well as on robust validation methods—measurement, monitoring, reporting, and verification—that are essential to demonstrate the safe removal and long-term storage of CO 2 . Engineering studies are needed on constraints including scalability, costs, resource inputs, energy demands, and technical readiness. Research on possible co-benefits, ocean acidification effects, environmental and social impacts, and governance is also required.

climate mitigation↗
DOE OSTI2025

FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration

Federated learning (FL) is a distributed machine learning approach that enables multiple local clients and a central server to collaboratively train a model while keeping the data on their own devices. First-order methods, particularly those incorporating variance reduction techniques, are the most widely used FL algorithms due to their simple implementation and stable performance. However, these methods tend to be slow and require a large number of communication rounds to reach the global minimizer. We propose FedOSAA, a novel approach that preserves the simplicity of first-order methods while achieving the rapid convergence typically associated with second-order methods. Our approach applies one Anderson acceleration (AA) step following classical local updates based on first-order methods with variance reduction, such as FedSVRG and SCAFFOLD, during local training. This AA step is able to leverage curvature information from the history points and gives a new update that approximates the Newton-GMRES direction, thereby significantly improving the convergence. We establish a local linear convergence rate to the global minimizer of FedOSAA for smooth and strongly convex loss functions. Numerical comparisons show that FedOSAA substantially improves the communication and computation efficiency of the original first-order methods, achieving performance comparable to second-order methods like GIANT.

Feng, Xue [University of California, Davis]↗
DOE OSTI2025

Discovery of Proteoforms Associated With Alzheimer's Disease Through Quantitative Top-Down Proteomics

The complex nature of Alzheimer's disease (AD) and its heterogenous clinical presentation has prompted numerous large-scale - omic analyses aimed at providing a global understanding of the pathophysiological processes involved. AD involves isoforms, proteolytic products, and posttranslationally modified proteins such as amyloid beta (Aβ) and microtubule-associated protein tau. Top-down proteomics directly measures these species and thus, offers a comprehensive view of pathologically relevant proteoforms that are difficult to analyze using traditional proteomic techniques. Here, we broadly explored associations between proteoforms and clinicopathological traits of AD by deploying a quantitative top-down proteomics approach across frontal cortex of 103 subjects selected from the ROS and MAP cohorts. The approach identified 1213 proteins and 11,782 proteoforms, of which 154 proteoforms had at least one significant association with a clinicopathological phenotype. One important finding included identifying Aβ C-terminal truncation state as the key property for differential association between amyloid plaques and cerebral amyloid angiopathy. Furthermore, various N-terminally truncated forms of Aβ had noticeably stronger association with amyloid plaques and global cognitive function. Additionally, we discovered six VGF neuropeptides that were positively associated with cognitive function independent of pathological burden. The database of brain cortex proteoforms provides a valuable context for functional characterization of the proteins involved in AD and other late-onset brain pathologies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

The impact of kinetic and global effects on ideal ballooning 2nd stable pedestals of conventional and low aspect-ratio tokamaks

The EPED model (Snyder et al 2011 Nucl. Fusion 51 103016) has had success in describing the pedestal structure of Type-I ELM and QH-mode plasmas in tokamaks, by combining kinetic ballooning mode (KBM) and peeling–ballooning (PB) constraints. Within EPED, the KBM constraint is often approximated by a technique using calculated ideal ballooning mode (IBM) thresholds, fit to a functional form designed to capture non-local effects. It has been noted that quantitative differences between local ideal MHD and gyro-kinetic (GK) ballooning stability can be larger at low aspect ratio. KBM critical pedestals are consistent with observations in initial studies on conventional and spherical tokamaks. In this work, the application of a reduced model for the calculation of the kinetic ballooning stability boundary is presented based on a novel and newly developed gyro-fluid system (GFS) code (Staebler et al 2023 Phys. Plasmas 30 102501). GFS is observed to capture KBMs in DIII-D as well as the NSTX pedestals, opening a route to integrating this model into EPED. Finally, high but finite $n$ global ballooning modes are observed to limit the access to the local 2nd stability and thus provide a transport mechanism that constrains the pedestal evolution with $β_{p,\textrm{ped}}$. The high $n$ global ballooning stability is approximated by its ideal MHD analog using ELITE. It is shown that nearly-local high $n$ modes with $k_yρ_s$ ~ $0.25 - 0.5$ can provide a proxy for the critical $β_{p,\textrm{ped}}$ when a 2nd stable access exists on DIII-D plasmas. The use of GFS and ELITE scaling in EPED provides improved agreement to EPED1 in an initial comparison with DIII-D pedestal data.

Anastopoulos Tzanis, Michail Savvas [Oak Ridge Nat↗
DOE OSTI2026

Roadmap to Advance Heliostat Technologies for High Temperature Solar-Thermal Systems

Since its establishment, the Heliostat Consortium (HelioCon) has made substantial progress toward closing many of the gaps in concentrating solar power (CSP) research. Numerous techno-economic studies have been performed, investigating topics ranging from the trade-off between size and temperature for industrial process heat applications to optimization of the heliostat design itself for various applications. Significant improvements have been made in optical metrology techniques, with first steps toward in situ measurement of heliostat fields. Several standards have been, and continue to be, developed with the coordination of an international group of CSP industry participants. Training programs have been developed, with universities including CSP in their engineering curricula, and many public webinars have been held to provide broad access to the latest CSP research. Improved CSP components such as mirror facets and wireless communication systems have been developed, and the solar tower at Sandia National Laboratories has been upgraded with a testbed for closed-loop controls research and development. Field deployment challenges involving heliostat foundations and sensitive wildlife habitats have been explored, with progress made toward methods for streamlining project development and permitting. Additional knowledge has been added to the body of work on wind behavior of heliostats and arrays of heliostats, with progress made toward a holistic understanding of wind design methods. Finally, techniques have been developed and demonstrated for assessing soiling conditions at a proposed project site, with predictive models for the soiling rate showing good results. Taking these results together, HelioCon has contributed greatly to the global CSP research and development effort over the past several years.

14 SOLAR ENERGY↗
DOE OSTI2024

Error mitigation, optimization, and extrapolation on a trapped-ion testbed

Current noisy intermediate-scale quantum (NISQ) trapped-ion devices are subject to errors which can significantly impact the accuracy of calculations if left unchecked. A form of error mitigation called zero noise extrapolation (ZNE) can decrease an algorithm’s sensitivity to these errors without increasing the number of required qubits. Here we explore different methods for integrating this error mitigation technique into the Variational Quantum Eigensolver (VQE) algorithm for calculating the ground state of the HeH + molecule at 0.8 Å in the presence of experimental noise. Using the Quantum Scientific Computing Open User Testbed (QSCOUT) trapped-ion device, we test three methods of scaling noise for extrapolation: time stretching the two-qubit gates, scaling the sideband detuning parameter, and inserting two-qubit gate identity operations into the ansatz circuit. We find that time stretching and sideband detuning scaling fail to scale the noise on our particular hardware in a way that can be extrapolated to zero noise. Scaling our noise with global gate identity insertions and extrapolating after variational optimization, we achieve error suppression of 96.8%, resulting in an energy estimate within –0.004 ± 0.04 hartree of the ground state energy. This is an improvement, but still outside the chemical accuracy threshold of 0.0016 hartree. Furthermore, our results show that the efficacy of this error mitigation technique depends on choosing the correct implementation for a given device architecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

ML-AMD/exa-pd

Exa-pd is a highly parallelizable workflow for constructing multi-element phase diagrams (PDs). It uses standard sampling techniques—molecular dynamics (MD) and Monte Carlo (MC)—as implemented in the LAMMPS package, to simultaneously sample multiple phases on a fine temperature–composition mesh for free-energy calculations. The workflow uses Parsl as a global controller to manage the MD/MC jobs to achieve massive parallelization with almost ideal scalability. The resulting free energies of both liquid and solid phases (including solid solutions) are then fed to CALPHAD modeling using the PYCALPHAD package for the construction of a multi-element PD.

Zhang, Feng [Ames Laboratory (AMES), Ames, IA (Uni↗
DOE OSTI2025

Novel Tools for Analyzing Life Cycle Energy Use, Carbon Emissions, and Cost of Additive Manufacturing

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from solid stock as with conventional techniques. This reduces material inputs and generates less waste, which can substantially lower life cycle energy consumption and greenhouse gas emissions. However, AM adoption in the manufacturing sector has been slow, partly due to challenges in making a strong business case compared with more traditional and widely available techniques. This paper highlights the need for the development of simple screening analysis tools to speed the adoption of AM in the manufacturing sector by providing decision-makers easy access to important production life cycle emissions, and cost information. Details on the development of two Microsoft Excel software tools are provided: upgrades to an existing tool on the energy and carbon impacts of AM and a new tool for analyzing the major cost components of AM. A case study applies these two tools to the production of a lightweight aerospace bracket, showing how the tools can be used to estimate the environmental benefits and production costs of AM.

GHG emissions↗
DOE OSTI2025

A Brief Survey on High Performance Computing Systems Power Management

This paper provides a survey of software-based power management techniques in High Performance Computing (HPC) systems. Seven existing power management and monitoring tools and frameworks are discussed. These are: Variorum, dynamic energy-performance optimizer (DEPO), Powersched, Bull Dynamic Power Optimizer (BDPO), Energy Aware Runtime (EAR), Global Extensible Open Power Manager (GEOPM), and PoLiMEr. Each of these tools is evaluated based on hardware abstraction, optimization methods, usability, and experimental validation. This survey highlights the diversity of approaches in managing energy efficiency, from vendor-neutral APIs to algorithm-driven power capping, and dynamic frequency adjustments. Given that energy requirements for large computational systems is increasing quickly, the importance of integrating these tools into existing HPC environments and the need for further research in this rapidly evolving field is also discussed.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗
DOE OSTI2024

Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation

Quantum volume is a full-stack benchmark for near-term quantum computers. It quantifies the largest size of a square circuit which can be executed on the target device with reasonable fidelity. Error mitigation is a set of techniques intended to remove the effects of noise present in the computation of noisy quantum computers when computing an expectation value of interest. Effective quantum volume is a proposed metric that applies error mitigation to the quantum volume protocol to evaluate the effectiveness not only of the target device but also of the error mitigation algorithm. Digital zero-noise extrapolation is an error mitigation technique that estimates the noiseless expectation value using circuit folding to amplify errors by known scale factors and then extrapolating computed expectation values to the zero-noise limit. Here we demonstrate that zero-noise extrapolation, with global and local unitary folding with fractional scale factors, in conjunction with dynamical decoupling, can increase the effective quantum volume over the vendor-measured quantum volume. Specifically, we measure the effective quantum volume of four IBM Quantum superconducting processor units, obtaining values that are larger than the vendor-measured quantum volume on each device. This is the first such increase reported.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Hacking Kilometer-Scale Models: A Participative Model for Climate Information

In May 2025, nearly 700 participants from all around the world coalesced at 10 regional nodes and a few satellite nodes to take part in a global hackathon of kilometer-scale (horizontal grid spacing < 10 km) regional and global Earth system models. Exciting science is emerging from these efforts, ranging across novel model analysis, new ways of integrating with satellite data, and emulation with machine learning. New technologies were trialed that enable the community to work in new and complementary ways to democratize access to global information at a local scale from a set of the world’s highest-resolution climate models. The hackathon demonstrated how exascale data can be organized to be accessible to anyone. Fundamentally, the community could apply these techniques and technologies to move toward more participative models for coproduction and delivery of diverse sources of climate information for climate scientists and citizens alike.

Climate models↗
DOE OSTI2025

Toward the first gluon parton distribution from the LaMET

Abstract We present progress towards the first unpolarized gluon quasi-parton distribution function (PDF) from lattice quantum chromodynamics using high-statistics measurements for hadrons at two valence pion masses M π ≈ 310 and 690 MeV computed on an a ≈ 0.12 fm ensemble with 2 + 1 + 1-flavors of highly improved staggered quark generated by the MILC collaboration. In this study, we consider two gluon operators for which the hybrid-ratio renormalization matching kernels have been recently derived and a third operator that has been used in prior pseudo-PDF studies of the gluon PDFs. We compare the matrix elements for each operator for both the nucleon and pion, at both pion masses, and using two gauge-smearing techniques. Focusing on the more phenomenologically studied nucleon gluon PDF, we compare the ratio and hybrid-ratio renormalized matrix elements at both pion masses and both smearings to those reconstructed from the nucleon gluon PDF from the CT18 global analysis. We identify the best choice of operator to study the gluon PDF and present the first gluon quasi-PDF under some caveats. Additionally, we explore the recent idea of Coulomb gauge fixing to improve signal at large Wilson-line displacement and find it could be a major help in improving the signal in the gluon matrix elements. This work helps identify the best operator for studying the gluon quasi-PDF, shows higher hadron boost momentum is needed to implement hybrid-ratio renormalization reliably, and suggests the need to study more diverse set of operators with their corresponding perturbative calculations for hybrid-ratio renormalization to further gluon quasi-PDF study.

Good, William (ORCID:0000000184281003)↗
DOE OSTI2025

Controlling Host Responses to Infection

Pathogen invasion of host cells causes a myriad of functional changes including alterations of chromatin accessibility often limiting defense responses, shunting of cellular resources to centers of viral replication, and rearrangement of intracellular membranes to facilitate genome reproduction and progeny release. Systems biology approaches provide global snapshots of pathogen induced changes following infection and provide a variety of tools to begin to define how cellular homeostasis is disrupted, but improvements on these tools are required to determine how cellular functions are altered post infection. Chromatin accessibility techniques, biochemical assays to assess the activity of epigenetic enzymes, scalable sample collection platforms, and activity-based probes were used to characterize how human respiratory viruses modify host responses in infected human lungs over time. These studies enhanced our knowledge of how pathogens usurp the host environment during infection and identify additional targets for future evaluations of medical countermeasures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Manufacturing of Continuous Microporous Polymeric Fibers for Separation Applications

Polyolefin plastic waste, particularly polypropylene, is one of the most prevalent components in the plastic waste stream generated globally. However, only a small fraction of this waste is recycled and reintegrated into second applications. These materials have significant embedded energy that could be used for additional productivity if recycled properly. Therefore, there is a critical need to develop scalable processing techniques with high throughput to effectively recycle it. We report the continuous manufacturing of microporous fibers using waste polypropylene plastic and melt-processable lignin, a plant biomass constituent produced as a byproduct in paper mills or biorefineries, as a template to create pores. Further, these filaments with hierarchical porosity─created by controlled microphase separation during high-speed extensional flow followed by removal of lignin─exhibit exceptional capillary action for hydrophobic liquids. The resulting porous fibers can be used for various separation applications. For example, the oil uptake of the fibers is 9.59 ± 0.82 g/g for applications in oil recovery in bodies of water. In addition, polyethylenimine infiltration within these nanoporous fibers introduces cyclic room temperature sorption and thermal desorption potential of acidic gases such as CO 2 in a bench-scale experiment. The fibers exhibit multiple cycles of CO 2 absorption, with a range of 0.15 to 0.17 mmol/g. Thus, these polyethylenimine-infiltered nanoporous polypropylene fibers can also be used in removing acidic gases from a gas mixture.

36 MATERIALS SCIENCE↗