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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding the Structure and Dynamics of Complex Biomembrane Interactions by Neutron Scattering Techniques

The membrane is one of the key structural materials of biology at the cellular level. Composed predominantly of a bilayer of lipids with embedded and bound proteins, it defines the boundaries of the cell and many organelles essential to life and therefore is involved in almost all biological processes. Membrane-specific interactions, such as drug binding to a membrane receptor or the interactions of an antimicrobial compound with the lipid matrix of a pathogen membrane, are of interest across the scientific disciplines. Herein we present a review, aimed at nonexperts, of the major neutron scattering techniques used in membrane studies: small-angle neutron scattering, neutron membrane diffraction, neutron reflectometry, quasielastic neutron scattering, and neutron spin echo. Neutron scattering techniques are well suited to studying biological membranes. The nondestructive nature of cold neutrons means that samples can be measured for long periods without fear of beam damage from ultraviolet, electron, or X-ray radiation, and neutron beams are highly penetrating, thus offering flexibility in samples and sample environments. Most important is the strong difference in neutron scattering lengths between the two most abundant forms of hydrogen, protium and deuterium. Changing the relative amounts of protium/deuterium in a sample allows the production of a series of neutron scattering data sets, enabling the observation of differing components within complex membrane architectures. This approach can be as simple as using the naturally occurring neutron contrast between different biomolecules to study components in a complex by changing the solution H 2 O/D 2 O ratio or as complex as selectively labeling individual components with hydrogen isotopes. This review presents an overview of each experimental technique with the neutron instrument configuration, related sample preparation and sample environment, and data analysis, highlighted by a special emphasis on using prominent neutron contrast to understand structure and dynamics. This review gives researchers a practical introduction to the often enigmatic suite of neutron beamlines, thereby lowering the barrier to taking advantage of these large-facility techniques to achieve new understandings of membranes and their interactions with other molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Eulerian finite element simulations of the drop weight impact test with a dislocation Density-based continuum model

During a drop weight impact test, the kinetic energy of the falling weight is transferred into the sample resting on the anvil. The plastic deformation in the sample is an important mechanism for the dissipation of the input kinetic energy. We use Eulerian finite element analysis to simulate the deformation and temperature evolution in a 1,3,5-trinitro-1,3,5-triazine (RDX) sample consisting of multiple crystals. In Eulerian finite element simulations, the mesh moves relative to the material. After every change of position between the mesh and the material, the state variables are interpolated to the new mesh position, i.e., advection. In an effort to reduce the advection errors, we use a rate form of a dislocation density-based continuum model by Luscher et al. Here, the simulations predict localization of plastic deformation, and plastic dissipation as a significant source of heat generation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies

Because natural gas emits less carbon than other fossil fuels, it holds promise as a green energy transition fuel. However, the overall carbon footprint of natural gas is significantly elevated by methane emissions that occur during its production and transmission (Cusworth et al. 2022). Methane “super-emitters,” while comprising only about 1% of sites, are responsible for the majority of oil- and gas-sourced methane emissions, making their detection and mitigation critical in reducing the climate impact of natural gas and in meeting national and global sustainability goals (Sherwin et al. 2024). Yet, despite advancements in detection, significant uncertainties remain regarding the size, frequency, and duration distributions of methane emissions (e.g., Frankenberg et al. 2016, Cusworth et al. 2022, Chen, Sherwin et al. 2022, Conrad et al. 2023, Johnson et al. 2023, Sherwin et al. 2024) underscoring the need for comprehensive emissions inventories segmented by basin across the US. Airborne surveys are well-suited for collecting data to build these comprehensive, basin-level inventories because they allow for extensive spatial coverage, and have the spatial resolution, and the sensitivity to pinpoint individual methane sources. As remote sensing technologies enable rapid basin-scale surveys, it is imperative to establish scientifically and statistically robust standards to generate reliable and actionable emissions inventories. Recent work has shown that differences in airborne sampling strategies, detection technologies, and analysis can lead to large differences between survey conclusions if not correctly accounted for (Chen et al. 2024). This elevates the importance of incorporating proper sampling and analysis techniques when designing a methane emissions monitoring campaign to produce accurate results and facilitate cross-study comparisons. In this paper, we describe a survey strategy designed using the latest conclusions from the literature to align results from different aerial surveys. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions. We present results from a Department of Energy-funded project that deployed this survey strategy in two understudied oil and gas- producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma.

03 NATURAL GAS↗
DOE OSTI2020

Tensile testing and fracture mechanism analysis of polyvinyl alcohol nanofibrous webs

Abstract A tensile properties testing study was conducted to understand the influence of thickness, cross‐head speed (speed of testing), gauge length (GL; specimen test length), and sample shape on important tensile properties of polyvinyl alcohol (PVA) nanofiber webs. The effects of each testing parameter on load at break, extension at break, Young's modulus, and tensile stress–strain curve of PVA nanofiber webs are analyzed. The Welch two sample t ‐tests show the significant difference among tested data. Using interaction plots, two‐way analysis of variance, and margin mean plots, the interaction effects among testing parameters have been analyzed. Of all the factors, cross‐head speed, the interaction among GL, and sample thickness (GL: Thickness) and the interaction among GL, testing speed and sample thickness (GL: Speed: Thickness) have significant influence on the tensile properties of PVA nanofiber webs. Moreover, the hypothesized model of mechanism of tensile strain–stress curve of PVA nanofiber webs has been proposed. Based on the model, the tensile strain–stress curve can be split into three stages: linear elastic, partial break up, and complete breakage. This study will provide a better understanding of tensile testing parameters' effects and their interaction effects on the tensile properties of nanowebs.

Lou, Lihua↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
DOE OSTI2024

A new method for quantifying 64 Cu in nuclear debris samples

Quantifying 64 Cu in post-detonation nuclear debris samples can provide important diagnostic information regarding the structural materials used within a nuclear device. However, this task is challenging due to the weak gamma emissions associated with the decay of 64 Cu, its short half-life (12.701 h), and the presence of interfering fission product radioisotopes. Large quantities of debris sample are generally needed to accurately quantify 64 Cu, which can be problematic in sample-limited scenarios where other radiometric analyses are required. Herein, we present a new method for the separation of 64 Cu from solutions of mixed fission products and demonstrate the quantification of its activity through use of gas-flow proportional beta counting. Here, the new method was validated through a series of rigorous tests and was shown to improve the detection limit of 64 Cu by over two orders of magnitude, from 2.5 × 10 6 to 1.3 × 10 4 atoms/sample for 100 min measurements.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

147 Nd Quantification Using HSCCC-Purified Samples

Quantifying the fission product 147 Nd in nuclear debris samples is an important component of post-detonation nuclear forensics. The most accurate quantifications are obtained when Nd is purified from all other fission products, actinides, activation products, and environmental matrix contained within the debris. In this study, a recently developed method for Nd purification was tested, purifying 147 Nd from solutions of mixed fission products using high-speed counter-current chromatography (HSCCC). Importantly, the new method allowed for faster elution of Nd from the column as compared with established high performance liquid chromatography (HPLC) methods, and resulted in accurate/precise 147 Nd quantification by gamma-ray spectrometry. While the up-front equipment costs associated with HSCCC may be higher, its operational costs are on par with those of HPLC (solvents, extractants, power). Gas-flow proportional beta decay counting revealed contamination from the nearest neighbor lanthanide 143 Pr (a gamma-silent radioisotope) in the HSCCC-purified samples, but the activity contribution from 147 Nd could still be quantified. Remarkably consistent elution profiles were observed for the HSCCC method, spanning rare earth element (REE) loadings of more than 10 orders of magnitude (tracer to mmol quantities). In conclusion, the reliability and speed of the new method suggest utility for the rapid separation and quantification of 147 Nd in unknown samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Accelerated Irradiation and Qualification of Ceramic Nuclear Fuels

Accelerated irradiation efforts are an important topic in accelerated qualification of new nuclear fuel concepts for light water reactor (LWRs), microreactors, and other special purpose reactors. Accelerated fuel qualification combines both experimental and modeling work to expedite the total qualification time from approximately 20-25 years to 5-10 years timeframe. The scope covered under the current work package focuses on the experimental contributions for the neutron irradiations. Accelerated irradiation aims to reduce the total time needed for neutron irradiation to achieve targeted burnup, which is timely using conventional irradiation profiles. The purpose of this report is to detail the samples preparation for such irradiations, which contain standard, medium, and large grain undoped UO 2 , as well as large grain, Cr 2 O 3 -doped UO 2 . The data that will be generated from the irradiation of these samples will yield important information regarding fission gas retention as a function of grain size and the effect that Cr dopants have on diffusivity of fission gases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Room temperature plasma-etching and surface passivation of far-ultraviolet Al mirrors using electron beam generated plasmas

The development of optical systems operating in the far ultraviolet range (FUV, λ=100-200 nm) is limited by the efficiency of passivated aluminum (Al) mirrors. Although it is presently possible to obtain high-reflectivity FUV mirrors through physical vapor deposition, the process involves deposition with substrates at high temperatures, which is technically challenging for large optical elements. A novel passivation procedure for bare Al mirrors is reported. The treatment consisted of using a low-temperature electron-beam generated plasma produced in a gas mixture of Ar and SF6 to etch away the native oxide layer from the Al film, while simultaneously promoting the generation of a thin aluminum tri-fluoride (AlF3) layer on the Al surface. In the first section we analyze the effect of varying both ion energy and SF6 concentration on the FUV reflectance, thickness, composition, and surface morphology of the resulting AlF3 protective layers. In the second section, the reflectivity of samples is optimized at selected important FUV wavelengths for astronomical observations. Notably, samples attained state-of-the-art reflectances of 75% at 108.5 nm (He Lyman γ), 91% at 121.6 nm (H Lyman α), 90% at 130.4 nm (OI), and of 95% at 155.0 nm (C IV). The stability over time of these passivated mirrors is also investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Boron isotopic analysis in bulk silicate materials using the Neoma MS/MS MC-ICP-MS

Boron (B) isotopes are a valuable tracer with applications ranging from geological, environmental, and nuclear studies because B isotopic fractionation is highly sensitive to chemical processes yielding distinct isotopic trends in natural and anthropogenic systems. Despite this wide applicability, there remain relatively few measurements on well-described reference materials and in some cases, poor agreement between various methods. We report a method for boron isotope ratio measurement in solution on the Neoma MS/MS MC-ICP-MS specifically targeting bulk silicates. We evaluate the performance of the method and instrument as it relates to the measurement of the absolute boron isotope ratio ( 10 B/ 11 B). The results indicate that the method produces data in agreement with literature values and that the sample–standard bracketing technique is appropriate for the Neoma MS/MS MC-ICP-MS which has been in use for decades on previous generation instruments. Careful tuning of the MS/MS lenses is required to obtain precision comparable to non MS/MS equipped MC-ICP-MS. With careful tuning, internal and external precisions of ∼0.3‰ were achieved. However, when the MS/MS is not properly tuned external precisions exceed 3‰. Nevertheless, our results for IAEA B-6, BCR-2, BHVO-2 and W-2a reference materials overlap the 1σ range of previously reported 10 B/ 11 B. Data are reported for total boron quantities down to a few tens of nanograms. Our procedure yielded blanks as low as 3 ng but up to 29 ng, making blank corrections important for small samples sizes in the few 10s of nanogram range. We report B isotope ratios for AGV-2G, SL-1G, GSC-2G, GSD-2G, GSE-2G, RLS-132, RLS-140, NKT-1G, and T1-G glass reference materials that have not been previously reported in the literature.

Scott, Sean R. [Pacific Northwest National Laborat↗
DOE OSTI2023

Exploring unsupervised top tagging using Bayesian inference

Recognizing hadronically decaying top-quark jets in a sample of jets, or even its total fraction in the sample, is an important step in many LHC searches for Standard Model and Beyond Standard Model physics as well. Although there exists outstanding top-tagger algorithms, their construction and their expected performance rely on Montecarlo simulations, which may induce potential biases. For these reasons we develop two simple unsupervised top-tagger algorithms based on performing Bayesian inference on a mixture model. In one of them we use as the observed variable a new geometrically-based observable \tilde{A}_{3} A ̃ 3 , and in the other we consider the more traditional \tau_{3}/\tau_{2} τ 3 / τ 2 N N -subjettiness ratio, which yields a better performance. As expected, we find that the unsupervised tagger performance is below existing supervised taggers, reaching expected Area Under Curve AUC \sim 0.80-0.81 ∼ 0.80 − 0.81 and accuracies of about 69% - − 75% in a full range of sample purity. However, these performances are more robust to possible biases in the Montecarlo that their supervised counterparts. Our findings are a step towards exploring and considering simpler and unbiased taggers.

Alvarez, Ezequiel↗
DOE OSTI2021

0D Nanocrystals as Light‐Driven, Localized Charge‐Injection Sources for the Contactless Manipulation of Atomically Thin 2D Materials

A contactless charge‐injection scheme that allows the local and quasi‐permanent manipulation of atomically thin 2D materials, such as monolayer (1L‐)MoS 2 , over spatial extents of several tens of micrometers, is reported. The possibility to precisely position and localize the charge‐injection source to the micrometer scale post‐fabrication allows the investigation of local unperturbed electronic structure of the 2D material. Thanks to this novel approach, the important impact of sample inhomogeneity on the charge‐carrier percolation that occurs over the entire extent of the 2D flake and proliferates up to 40 μm away from the localized charge injection is elucidated. The apparent driving force for carrier relocation is the initial inhomogeneous electronic landscape of the 2D material. These studies demonstrate that local and contactless charge injection with submicrometer precision delivers an alternative route for charge injection and indicates that local 2D material electronic structure can serve as a key element for novel nanoscale device design.

Ghini, Michele↗
DOE OSTI2025

Oxygen stable isotopes in the nuclear fuel cycle: Assessment of the potential for determining the fabrication and provenance history of anhydrous and hydrous uranium oxides

Determining the origin and history of interdicted nuclear materials is a central challenge in nuclear forensics. The oxygen stable isotope composition of uranium oxide compounds has emerged as a promising forensic signature, attracting increasing attention since the early 2000s. This review examines analytical techniques for measuring oxygen isotope compositions in uranium oxides and evaluates how the nuclear fuel production cycle introduces or modifies these isotopic signatures. The potential for forensic geolocation is explored through workflows that calibrate the relationship between environmental water oxygen isotopes and those found in uranium oxides. Key strengths and limitations of this approach are assessed, including gaps in knowledge related to isotope fractionation during specific stages of the fuel cycle, and processing facility water inputs. The importance of proper sample handling and storage under inert atmospheres, as well as a deeper understanding of both intra-sample oxygen isotope heterogeneity, and hydrous uranium oxide phase formation, is highlighted for improving the reliability of forensic interpretations. In conclusion, the development of uranium oxide standards with well-characterized δ 18 O values and international collaboration toward consensus on their use are identified as essential steps for advancing the field.

Attribution↗
DOE OSTI2026

Personal and environmental predictors of polycyclic aromatic hydrocarbon exposure identified through repeated silicone wristband sampling

This study integrates quantitative data on personal exposure to polycyclic aromatic hydrocarbons (PAHs) in 162 silicone wristbands with demographics, behavioral information, and housing characteristics to explore contributions to residential exposure in a superfund-adjacent community over the course of a year. Forty-six residents completed questionnaires and wore silicone wristbands as personal passive samplers for seven consecutive days on up to four separate occasions in alternating months between November 2022 and June 2023. It was hypothesized that individual behaviors and housing characteristics are sources of dependence and correlation between personal PAH exposures. 50 PAHs were detected at least once, 17 of which were alkylated PAHs. Exposure to PAHs of similar molecular weight was often correlated, notably between naphthalenes (2-rings) and higher molecular weight PAHs (3 or more rings). Generalized linear mixed models identified flooring type, participant age, and sampling month as important predictors of increased PAH exposure, and flooring type, and use of wood stoves or heavy machinery as predictors of increased naphthalene exposure relative to higher molecular weight PAHs. Individual chemical models based on concentration data and detection frequencies corroborated these findings across multiple PAHs. We demonstrate that personal exposure is not static and the degree of variability in personal exposure is individual. Hence, identification of influential exposure factors through repeated measures of chemical exposure and characterization of variability in personal exposure as performed in this study, is important in the development of exposure mitigation strategies.

Bonner, Emily↗
DOE OSTI2021

Radiolysis of thermally dehydrated gibbsite

Aluminum hydroxide (gibbsite, Al (OH) 3 ) powders and their thermally dehydrated forms were rehydrated and irradiated with gamma rays to examine the effects of the collapse of the crystalline gibbsite structure as it is converted to alumina on the transport of precursors of molecular hydrogen to the surface. The amount of hydrogen gas, H 2 , production from irradiated gibbsite and its transition phases with adsorbed water increased substantially with increasing temperature for dehydration of the samples, up to a point. Furthermore, the production of H 2 for samples without water was considerably lower than the hydrated samples signifying the importance of surface water and the transport of precursors to the surface. EPR spectroscopy showed that the major radiolytic products are trapped electrons and related O – centers. Thermal gravimetric analysis (TGA) measurements of gibbsite dehydration established the temperatures of phase transitions from gibbsite to alumina. Changes to the surface and structure of gibbsite and its transition phases following irradiation were analyzed using nitrogen adsorption, powder X-ray diffraction (pXRD), Raman spectroscopy, electron paramagnetic resonance (EPR), and scanning electron microscopy (SEM). pXRD and Raman spectra showed amorphorization at about 300 °C, coupled to a substantial increase in specific surface area due to increasing porosity.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Thermal Transport and Mechanical Stress Mapping of a Compression Bonded GaN/Diamond Interface for Vertical Power Devices

Bonding diamond to the back side of gallium nitride (GaN) electronics has been shown to improve thermal management in lateral devices; however, engineering challenges remain with the bonding process and characterizing the bond quality for vertical device architectures. Here, in this study, integration of these two materials is achieved by room-temperature compression bonding centimeter-scale GaN and a diamond die via an intermetallic bonding layer of Ti/Au. Recent attempts at GaN/diamond bonding have utilized a modified surface activation bonding (SAB) method, which requires Ar fast atom bombardment immediately followed by bonding within the same tool under ultrahigh vacuum (UHV) conditions. The method presented here does not require a dedicated SAB tool yet still achieves bonding via a room-temperature metal–metal compression process. Imaging of the buried interface and the total bonding area is achieved via transmission electron microscopy (TEM) and confocal acoustic scanning microscopy (C-SAM), respectively. The thermal transport quality of the bond is extracted from spatially resolved frequency-domain thermoreflectance (FDTR) with the bonded areas boasting a thermal boundary conductance of >100 MW/m 2 ·K. Additionally, Raman maps of GaN near the GaN–diamond interface reveal a low level of compressive stress, <80 MPa, in well-bonded regions. FDTR and Raman were coutilized to map these buried interfaces and revealed some poor thermally bonded areas bordered by high-stress regions, highlighting the importance of spatial sampling for a complete picture of bond quality. Overall, this work demonstrates a novel method for thermal management in vertical GaN devices that maintains low intrinsic stresses while boasting high thermal boundary conductances.

Raman↗
DOE OSTI2023

Cryo-EM structures reveal native GABA A receptor assemblies and pharmacology

Type A γ-aminobutyric acid receptors (GABA A Rs) are the principal inhibitory receptors in the brain and the target of a wide range of clinical agents, including anaesthetics, sedatives, hypnotics and antidepressants. However, our understanding of GABA A R pharmacology has been hindered by the vast number of pentameric assemblies that can be derived from 19 different subunits and the lack of structural knowledge of clinically relevant receptors. Here, we isolate native murine GABA A R assemblies containing the widely expressed α1 subunit and elucidate their structures in complex with drugs used to treat insomnia (zolpidem (ZOL) and flurazepam) and postpartum depression (the neurosteroid allopregnanolone (APG)). Using cryo-electron microscopy (cryo-EM) analysis and single-molecule photobleaching experiments, we uncover three major structural populations in the brain: the canonical α1β2γ2 receptor containing two α1 subunits, and two assemblies containing one α1 and either an α2 or α3 subunit, in which the single α1-containing receptors feature a more compact arrangement between the transmembrane and extracellular domains. Interestingly, APG is bound at the transmembrane α/β subunit interface, even when not added to the sample, revealing an important role for endogenous neurosteroids in modulating native GABA A Rs. Together with structurally engaged lipids, neurosteroids produce global conformational changes throughout the receptor that modify the ion channel pore and the binding sites for GABA and insomnia medications. Our data reveal the major α1-containing GABA A R assemblies, bound with endogenous neurosteroid, thus defining a structural landscape from which subtype-specific drugs can be developed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Neutrons reveal the dynamics of leaf thylakoids in living plants

The study is the first known exploration of photosynthetic membranes dynamics in living plants by high resolution quasielastic neutron scattering spectroscopy. We investigated the mobility and flexibility of thylakoid membranes in common duckweed (Landoltia punctata) and identified dynamics across various length scales corresponding to individual membranes and membranes stack. We employed classical models typically used to study lipid bilayers to characterize the undulation modes and rigidity of the membranes and reveal how structural variations influence the observed complex dynamics. Our findings show that the stacks of thylakoids in duckweed behave as rigid systems, exhibiting an effective bending coefficient in the lower range associated with surfactant membranes. In contrast, the single thylakoid leaflets display greater apparent flexibility and are well situated within the bi-continuous surfactant phase dynamics. While our observations enhance the understanding of the intricate architecture and mobility of photosynthetic cellular machinery, they also highlight the limitations of applying ideal lipid membranes models to describe complex biological systems. This work opens more questions and the need for further investigations across extended length and time scales, as well as the importance of rigorous sample preparation and experimental control.

Applied physics↗