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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Sandia Optical Fringe Analysis Slope Tool (SOFAST) Improvement Effort (Final Report)

The Sandia Optical Fringe Analysis Slope Tool (SOFAST) is a tool that has been developed at Sandia to measure the surface slope of concentrating solar power optics. This tool has largely remained of research quality over the past few years. Since SOFAST is important to ongoing tests happening at Sandia as well as an interest to others outside Sandia, there is a desire to bring SOFAST up to professional software standards. The goal of this effort was to make progress in several broad areas including: code quality, sample data collection, and validation and testing. During the course of this effort, much progress was made in these areas. SOFAST is now a much more professional grade tool. There are, however, some areas of improvement that could not be addressed in the timeframe of this work and will be addressed in the continuation of this effort.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Bioenergy Feedstock Library Annual Summary Report 2024

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at Idaho National Laboratory (INL), is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use, as well as samples generated from U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture-funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2024, similar to the 2023 Annual Summary Report , is to focus on the updates to: (1) publicly available analytical data and equipment tracked through the BFNUF, (2) significant increases in the physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities compared to the previous annual summary reports. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗
DOE OSTI2023

Control of Cement Timing, Mineralogy, and Texture on Hydro-chemo-mechanical Coupling from CO2 Injection into Sandstone: A Synthesis

Carbon capture, utilization, and storage (CCUS) has been widely applied to enhance oil recovery (CO2-EOR). A thorough investigation of the impact of injecting CO2 into a heterogeneous reservoir is critical to understanding the overall reservoir robustness and storage performance. We conducted fifteen flow-through tests on Morrow B sandstone that allowed for chemical reactions between a CO2-rich brackish solution and the sandstones, and four creep/flow-through tests that simultaneously allowed for chemical reactions and stress monitoring. From fluid chemistry and X-ray computed tomography, we found that the dissolution of disseminated cements and the precipitation of iron-rich clays did not significantly affect the permeability and geomechanical properties. Minor changes in mechanical properties from Brazilian and creep tests indicated that the matrix structure was well-supported by early diagenetic quartz overgrowth cement and the reservoir’s compaction history at deep burial depths. However, one sample experienced a dissolution of poikilotopic calcite, leading to a permeability increase and significant tensile strength degradation due to pore opening, which overcame the effect of the early diagenetic cements. We concluded that the Morrow B sandstone reservoir is robust for CO2 injection. Most importantly, cement timing, the abundance and texture of reactive minerals, and the reservoir’s burial history are critical in predicting reservoir robustness and storage capacity for CO2 injection.

Wu, Zhidi (ORCID:0000000338869492)↗
DOE OSTI2022

Biomass burning and marine aerosol processing over the southeast Atlantic Ocean: a TEM single-particle analysis

This study characterizes single-particle aerosol composition from filters collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) campaigns. In particular the study describes aged biomass burning aerosol (BBA), its interaction with the marine boundary layer and the influence of biomass burning (BB) air on marine aerosol. The study finds evidence of BBA influenced by marine boundary layer processing as well as sea salt influenced by BB air. Secondary chloride aerosols were observed in clean marine air as well as in BB-influenced air in the free troposphere. Higher-volatility organic aerosol appears to be associated with increased age of biomass burning plumes, and photolysis or oxidation may be a mechanism for the apparent increased volatility. Aqueous processing and interaction with the marine boundary layer air may be a mechanism for the presence of sodium on many aged potassium salts. By number, biomass burning potassium salts and modified sea salts are the most observed particles on filter samples. The most commonly observed BC coatings are inorganic salts. These results suggest that atmospheric processes such as photolysis, oxidation and cloud processing are key drivers in the elemental composition and morphology of aged BBA. Fresh BBA inorganic salt content, as it has an important role in the particles' ability to uptake water, may be a key driver in how aqueous processing and atmospheric aging proceed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SERPENT 2 and TRIPOLI-4 neutronics benchmarking of the Jules Horowitz reactor

Jules Horowitz Reactor (JHR) is a future center for nuclear material testing in Europe, currently under construction at CEA Cadarache in southern France. It has been modelled extensively with CEA's HORUS3D/N neutron calculation package, that includes a Monte-Carlo neutron transport code TRIPOLI-4. In order to support the future computational analyses on the reactor core physics, VTT's Monte Carlo neutronics code SERPENT 2 has been used to create an alternative model of the JHR, taking advantage of the pre-existing Constructive Solid Geometry (CSG) structures on which the TRIPOLI-4 model was built. This work describes a benchmark, in which two JHR core configurations were analyzed using both of these models. The first configuration is a fresh fuel core at the beginning of life, in which aluminum based dummy-devices are installed in the reactor test positions. The second configuration represents the end-of-cycle equilibrium core with a heterogeneous burnup distribution, in which CALIPSO devices containing cladding material samples are installed at the in-core experimental positions, while the reflector positions are occupied by DEN-REP devices containing UO{sub 2} fuel. Neutron flux spectra and heat deposition are the parameters of interest in this study, due to their high importance in creating the desired experimental irradiation environment. The impact of delayed gamma energy deposition will be studied in detail, since the two models account for it with different methods. This work aims to establish a SERPENT 2 model of JHR, understanding its differences and agreements with TRIPOLI-4, and discussing its potential future applications. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Subgalactic Scaling Relations with T e -based Metallicities of Low-metallicity Regions in Galaxies: Metal-poor Gas Inflow May Have Important Effects?

The scaling relationship is a fundamental probe of the evolution of galaxies. Using the integral field spectroscopic data from the Mapping Nearby Galaxies at Apache Point Observatory survey, we select 1698 spaxels with a significant detection of the auroral emission line [O ιιι]λ4363 from 52 galaxies to investigate the scaling relationships at the low-metallicity end. We find that our sample’s star formation rate is higher and its metallicity is lower in the scaling relationship than the star-forming sequence after removing the contribution of the Fundamental Metallicity Relation. We also find that the stellar ages of our sample are younger (<1 Gyr) and the stellar metallicities are also lower. Morphological parameters from the Deep Learning catalog indicate that our galaxies are more likely to be mergers. These results suggest that their low-metallicity regions may be related to interaction; the inflow of metal-poor gas may dilute the interstellar medium and form new metal-poor stars in these galaxies during interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Multi-scale signaling and tumor evolution in high-grade gliomas

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Exploring the relationship between solvent-assisted ball milling, particle size, and sintering temperature in garnet-type solid electrolytes

Garnet-type solid electrolytes, such as Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 (LLZTO), are promising materials for solid-state batteries, but processing remains a challenge, in part due to the high sintering temperature required for densification. Additionally, this temperature can be lowered by decreasing the initial particle size via solvent-assisted ball milling, but the relationship between solvent choice, particle properties, sintering behavior, and ionic conductivity is not well understood. In this work, we systematically explore these parameters, showing that milling in commonly used protic solvents, such as alcohols, effectively decreases the particle size but results in lithium loss (through Li + /H + exchange) that leads to poor sintering. By contrast, milling in aprotic solvents with surfactant reduces the particle size to ~220 nm without lithium loss, enabling the fabrication of dense samples (5.1 g/cm 3 ) with good ionic conductivity (0.43 mS/cm at 25 °C) at a lower sintering temperature (1000 °C). We compare ionic conductivities and activation energies for samples prepared with different particle sizes and sintering temperatures and use multiphase-field simulations to identify the mass transport and microstructural mechanisms responsible for the observed sintering dependence on particle size. These results further clarify the relationship between processing parameters and performance and represent important progress toward overcoming fabrication challenges for these materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Design and Characterization of Metal Nanoparticle Infiltrated Mesoporous Metal–Organic Frameworks

The infiltration of palladium and platinum nanoparticles (NPs) into the mesoporous metal–organic framework (MOF) CYCU-3 through chemical vapor infiltration (CVI) and incipient wetness infiltration (IWI) processes was systematically explored as a means to design novel NP@MOF composite materials for potential hydrogen storage applications. We employed a traditional CVI process and a new "green" IWI process using methanol for precursor infiltration and reduction under mild conditions. Transmission electron microscopy-based direct imaging techniques combined with synchrotron-based powder diffraction (SPD), energy-dispersive X-ray spectroscopy, and physisorption analysis reveal that the resulting NP@MOF composites combine key NP and MOF properties. Room temperature hydrogen adsorption capacities of 0.95 and 0.20 mmol/g at 1 bar and 2.9 and 1.8 mmol/g at 100 bar are found for CVI and IWI samples, respectively. Additionally, hydrogen spillover and/or physisorption are proposed as the dominating adsorption mechanisms depending on the NP infiltration method. Mechanistic insights were obtained through the crystallographic means using SPD-based difference envelope density analysis, providing previously underexplored details on NP@MOF preparations. Consequently, important host–guest correlations influencing the global hydrogen adsorption properties are discussed, and they demonstrate that employing MOFs as platforms for NPs is an alternative approach to the development of versatile materials for improving current hydrogen storage technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)

Abstract Land surface models such as the Community Land Model version 5 (CLM5) seek to enhance understanding of terrestrial hydrology and aid in the evaluation of anthropogenic and climate change impacts. However, the effects of parametric uncertainty on CLM5 hydrologic predictions across regions, timescales, and flow regimes have yet to be explored in detail. The common use of the default hydrologic model parameters in CLM5 risks generating streamflow predictions that may lead to incorrect inferences for important dynamics and/or extremes. In this study, we benchmark CLM5 streamflow predictions relative to the commonly employed default hydrologic parameters for 464 headwater basins over the conterminous United States (CONUS). We evaluate baseline CLM5 default parameter performance relative to a large (1,307) Latin Hypercube Sampling‐based diagnostic comparison of streamflow prediction skill using over 20 error measures. We provide a global sensitivity analysis that clarifies the significant spatial variations in parametric controls for CLM5 streamflow predictions across regions, temporal scales, and error metrics of interest. The baseline CLM5 shows relatively moderate to poor streamflow prediction skill in several CONUS regions, especially the arid Southwest and Central U.S. Hydrologic parameter uncertainty strongly affects CLM5 streamflow predictions, but its impacts vary in complex ways across U.S. regions, timescales, and flow regimes. Overall, CLM5's surface runoff and soil water parameters have the largest effects on simulated high flows, while canopy water and evaporation parameters have the most significant effects on the water balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Suppression of superconductivity by anisotropic strain near a nematic quantum critical point

In most unconventional and high-temperature superconductors, superconductivity emerges as a nearby symmetry-breaking phase is suppressed by chemical doping or pressure. This has led to the belief that the fluctuations associated with the symmetry-breaking phase are beneficial, if not responsible, for the superconducting pairing. A direct test to verify this hypothesis is to observe a decrease of the superconducting critical temperature (T c ) by applying the symmetry-breaking conjugate field that suppresses the dynamic fluctuations of the competing order. However, most of the competing phases in unconventional superconductors break translational symmetry, requiring a spatially modulated conjugate field that is difficult to realize experimentally. Here, we show that anisotropic strain, the conjugate field of nematicity, reduces the T c of an iron pnictide. For optimally doped samples we show a fivefold reduction of T c with less than one per cent of strain. For underdoped samples, T c becomes zero yielding a fully metallic ground state. In addition to providing direct evidence of the role played by the nematic fluctuations in the formation of the superconducting state, these results demonstrate tunable mechanical control of a high-temperature superconductor, an important step forward for technological applications of superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures

The goal of influence maximization is to select k most-influential vertices or seeds in a network, where influence is defined by a given diffusion process. The problem has a number of important applications such as viral marketing, information spread, and epidemic control. Although computing optimal seed set is NP-Hard, due to the submodular nature of the problem efficient approximation algorithms exist. However, even state-of-the-art parallel implementations are limited by a sampling step that incurs large memory footprints. This in turn limits the problem size reach and approximation quality. In this work, we study the memory footprint of the sampling process collecting reverse reachability information in the IMM algorithm over large real-world social networks. We present an adaptive and memory-efficient optimization approach for a state-of-the-art multi-threaded parallel influence maximization algorithm. Our approach,HuffMax, uses a portion of the reverse reachable (RR) sets collected by the algorithm to learn the characteristics of the graph. Then, it compresses the intermediate reverse reachability information with Huffman coding, and queries directly on the compressed data to preserve the memory savings obtained through compression. We also propose an efficient sampling strategy based on the distribution of RR sets, which can further reduce the computation time for typical social networks with long-tail distributions. Considering a NUMA architecture, we scale up our solution on 128-core CPUs and reduce the memory footprint by up to 45.7% with negligible time overhead (or even faster) and without perceivable loss of accuracy.

Chen, Xinyu↗
DOE OSTI2023

Classification Analysis of Southwest Pacific Tropical Cyclone Intensity Changes Prior to Landfall

This study evaluates the ability of a random forest classifier to identify tropical cyclone (TC) intensification or weakening prior to landfall over the western region of the Southwest Pacific Ocean (SWPO) basin. For both Australia mainland and SWPO island cases, when a TC first crosses land after spending ≥24 h over the ocean, the closest hour prior to the intersection is considered as the landfall hour. If the maximum wind speed (V max ) at the landfall hour increased or remained the same from the 24-h mark prior to landfall, the TC is labeled as intensifying and if the V max at the landfall hour decreases, the TC is labeled as weakening. Geophysical and aerosol variables closest to the 24 h before landfall hour were collected for each sample. The random forest model with leave-one-out cross validation and the random oversampling example technique was identified as the best-performing classifier for both mainland and island cases. The model identified longitude, initial intensity, and sea skin temperature as the most important variables for the mainland and island landfall classification decisions. Incorrectly classified cases from the test data were analyzed by sorting the cases by their initial intensity hour, landfall hour, monthly distribution, and 24-h intensity changes. TC intensity changes near land strongly impact coastal preparations such as wind damage and flood damage mitigations; hence, this study will contribute to improve identifying and prioritizing prediction of important variables contributing to TC intensity change before landfall.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Dependence of Solar Wind Proton Temperature on the Polarization Properties of Alfvénic Fluctuations at Ion-kinetic Scales

In this work, we use fluctuating magnetic helicity to investigate the polarization properties of Alfvénic fluctuations at ion-kinetic scales in the solar wind as a function of β p , the ratio of proton thermal pressure to magnetic pressure, and θ vB , the angle between the proton flow and local mean magnetic field, B 0 . Using almost 15 yr of Wind observations, we separate the contributions to helicity from fluctuations with wavevectors, k, quasi-parallel and oblique to B 0 , finding that the helicity of Alfvénic fluctuations is consistent with predictions from linear Vlasov theory. This result suggests that the nonlinear turbulent fluctuations at these scales share at least some polarization properties with Alfvén waves. Furthermore, we also investigate the dependence of proton temperature in the β p –θ vB plane to probe for possible signatures of turbulent dissipation, finding that it correlates with θ vB . The proton temperature parallel to B 0 is higher in the parameter space where we measure the helicity of right-handed Alfvénic fluctuations, and the temperature perpendicular to B 0 is higher where we measure left-handed fluctuations. This finding is inconsistent with the general assumption that by sampling different θ vB in the solar wind we can analyze the dependence of the turbulence distribution on θ kB , the angle between k and B 0 . After ruling out both instrumental and expansion effects, we conclude that our results provide new evidence for the importance of local kinetic processes that depend on θ vB in determining proton temperature in the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

High-Resolution Frequency-Domain Spectroscopic and Modeling Studies of Photosystem I (PSI), PSI Mutants and PSI Supercomplexes

Photosystem I (PSI) is one of the two main pigment–protein complexes where the primary steps of oxygenic photosynthesis take place. This review describes low-temperature frequency-domain experiments (absorption, emission, circular dichroism, resonant and non-resonant hole-burned spectra) and modeling efforts reported for PSI in recent years. In particular, we focus on the spectral hole-burning studies, which are not as common in photosynthesis research as the time-domain spectroscopies. Experimental and modeling data obtained for trimeric cyanobacterial Photosystem I (PSI 3 ), PSI 3 mutants, and PSI 3 –IsiA 18 supercomplexes are analyzed to provide a more comprehensive understanding of their excitonic structure and excitation energy transfer (EET) processes. Detailed information on the excitonic structure of photosynthetic complexes is essential to determine the structure–function relationship. We will focus on the so-called “red antenna states” of cyanobacterial PSI, as these states play an important role in photochemical processes and EET pathways. The high-resolution data and modeling studies presented here provide additional information on the energetics of the lowest energy states and their chlorophyll (Chl) compositions, as well as the EET pathways and how they are altered by mutations. We present evidence that the low-energy traps observed in PSI are excitonically coupled states with significant charge-transfer (CT) character. The analysis presented for various optical spectra of PSI 3 and PSI 3 -IsiA 18 supercomplexes allowed us to make inferences about EET from the IsiA 18 ring to the PSI 3 core and demonstrate that the number of entry points varies between sample preparations studied by different groups. In our most recent samples, there most likely are three entry points for EET from the IsiA 18 ring per the PSI core monomer, with two of these entry points likely being located next to each other. Therefore, there are nine entry points from the IsiA 18 ring to the PSI 3 trimer. We anticipate that the data discussed below will stimulate further research in this area, providing even more insight into the structure-based models of these important cyanobacterial photosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A decay database of coincident γ–γ and γ–X -ray branching ratios for in-field spectroscopy applications

Current fieldable spectroscopy techniques often use single detector systems heavily impacted by interferences from intense background radiation fields. These effects result in low-confidence measurements that can lead to misinterpretation of the collected spectrum. To help improve interpretation of the fission products and short-lived radionuclides produced in a composite sample, a coincidence-database is being developed in support of a robust portable and X-ray coincidence detector system concurrently under development at the Pacific Northwest National Laboratory for in-field deployment. Hitherto, no database exists containing coincident γ–γ and γ–X-ray branching-ratio intensities on an absolute scale that will greatly enhance isotopic identification for in-field applications. As part of this project, software has been developed to parse all radioactive-decay data sets from the Evaluated Nuclear Structure Data File (ENSDF) archive to enable translation into a more useful JavaScript Object Notation (JSON) formats that more readily supports query-based data manipulation. The coincident database described in this work is the first of its kind and contains coincidence γ–γ and γ–X-ray intensities and their corresponding uncertainties, together with auxiliary metadata associated with each decay data set. The new JSON format provides a convenient and portable means of data storage that can be imported into analysis frameworks with relatively low overhead allowing for meaningful comparison with measured data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The Value of Information From Horizontal Distributed Acoustic Sensing Compared to Multicomponent Geophones Via Machine Learning

Abstract Faults play an important role in recharging many geothermal reservoirs, and seismic information can image the locations of these faults. The value of information (VOI) metric is used to objectively quantify and compare the value of two types of seismic receiver data via a machine learning approach. The demonstrated VOI methodology is novel by including spatial models from seismic data and obtaining the information statistics from machine learning. Our two-dimensional numerical experiments compare images created from sparsely spaced (80 m), two-component geophone sampling to high spatial resolution (1 m), single-component DAS. We used a three-fold cross validation of a U-Net convolutional neural networks to achieve average classification statistics. The results suggest that when horizontal sources are utilized, geophones and DAS identify reflectors and non-reflectors at roughly the same rate. The average F1 score for horizontal DAS is 0.939 and 0.931 for geophones. For images created from a vertical source, DAS performed marginally better (F1 = 0.919) than geophones (F1 = 0.877). Our transferrable methodology can provide guidance on which acquisition scenarios can improve images of important structures in the subsurface and present an efficient method for obtaining reliability statistics from high-dimensional, spatial data.

Energy & Fuels↗