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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

On the morphological behavior of ABC miktoarm stars containing poly(cis 1,4-isoprene), poly(styrene), and poly(2-vinylpyridine)

Fundamental understanding of microphase separation in ABC miktoarm copolymers is vital to access a plethora of nonconventional morphologies. Miktoarm stars based on poly(cis 1,4–isoprene) (I), poly(styrene) (S), and poly(2–vinylpyridine) (V) are model systems, which allow systematic studies of the effects of composition, chemical microstructure, and temperature on the thermodynamics of microphase separation. Eleven ISV–x (I:S:V = 1:1:x, v:v:v) miktoarm copolymers were synthesized by anionic polymerization affording well-defined copolymers with a variable V arm. Equilibrium bulk morphologies of all samples, as evidenced by small–angle X–ray scattering, transmission electron microscopy (TEM), and self–consistent field theory, showed a systematic transition from lamellae (x ≈ 0–0.2) to [8.8.4] tiling (x ≈ 0.6–0.9) to cylinders in undulating lamellae (x ≈ 2–4) and, finally, to hexagonally packed core–shell cylinders (x ≈ 5–8). Chemical microstructure of the I arm [poly(cis 1,4–isoprene)] versus poly(3,4–isoprene) is shown to play important role in affecting morphological behavior. Furthermore, to reconcile differences between ISV–x star morphologies reported in the literature and those reported herein, even for the same composition, effects of the microstructure of I arm on the Flory–Huggins parameter between I and V arms were taken into account in a qualitative manner.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparison of greenhouse gas emission estimates from six hydropower reservoirs using modeling versus field surveys

As with most aquatic ecosystems, reservoirs play an important role in the global carbon (C) cycle and emit greenhouse gases (GHG) as carbon dioxide (CO 2 ) and methane (CH 4 ). However, GHG emissions from reservoirs are poorly quantified, especially in temperate systems, resulting in high uncertainty. We compared reservoir C emission estimates and uncertainty of diffusive, ebullitive, and degassing pathways in six hydropower reservoirs in the southeastern United States among four data sources: two field-based surveys and two models (including the GHG Reservoir “G-res” Tool). We found that CH 4 diffusion was most similar across data sources (modeled minus observed, bias = - 21 g CO 2-eq m -2 y -1 ) and had low relative uncertainty (coefficient of variation, CV = 0.98). On the other hand, CO 2 diffusion was least consistent across data sources (bias = - 518 g CO 2-eq m -2 y -1 ). Both field surveys indicated strong negative CO 2 diffusion (i.e., CO 2 uptake) at all reservoirs, while G-res estimated positive CO 2 diffusion. By extension, total C emissions showed similar discrepancies, leading to high uncertainty in upscaling and interpreting reservoir source-sink dynamics. Finally, CH 4 ebullition had the highest relative uncertainty (CV = 2.77) due to high variability across sites. We discuss limitations of field surveys and these models, including temperature-based annualization methods, varying definitions of ebullition zones, low sampling resolution, and lack of dynamism. Future field efforts focused on capturing variability in CO 2 diffusion and CH 4 ebullition will be especially valuable in reducing uncertainty and improving models to advance our understanding reservoir GHG emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Resilient information and inference networks under mixed-trust sensing

With ubiquitous digitization, sensing, and computational intelligence deployed in increasingly more and broader domains, including critical infrastructure, potentially misleading and destabilizing effects of multimodal anomalies and adversarial behavior are growing in importance. Here, we develop randomized and reinforcement learning-based strategies for strategically recruiting and utilizing deployed (and, thus, vulnerable and potentially faulty and/or compromised) nodes from information and inference networks, while defending against adversaries that attempt to misguide assessments of inferred variables. Recognizing that, besides communication and other costs, sampling from any observable node can either provide true data or dangerously expose our inference to misinformation (without being easily distinguishable what actually happens), the proposed strategies proceed by progressively recruiting nodes and cautiously scaling their information contribution based on assumed, or, in our reinforcement learning approach, intelligently weighed trustworthiness, with the learning approach also considering network-wide, threat-inclusive risk/value tradeoffs. While avoiding the hardware, communication, analytical and computational burden of explicit redundancy, the proposed defensive schemes enable on-the-fly assessments of underlying processes, and system-wide situational awareness with demonstrable resilience against adversarial activities.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2018

DeePCG: Constructing coarse-grained models via deep neural networks

We introduce a general framework for constructing coarse-grained potential models without ad hoc approximations such as limiting the potential to two- and/or three-body contributions. The scheme, called the Deep Coarse-Grained Potential (abbreviated DeePCG), exploits a carefully crafted neural network to construct a many-body coarse-grained potential. The network is trained with full atomistic data in a way that preserves the natural symmetries of the system. The resulting model is very accurate and can be used to sample the configurations of the coarse-grained variables in a much faster way than with the original atomistic model. As an application, we consider liquid water and use the oxygen coordinates as the coarse-grained variables, starting from a full atomistic simulation of this system at the ab initio molecular dynamics level. We find that the two-body, three-body, and higher-order oxygen correlation functions produced by the coarse-grained and full atomistic models agree very well with each other, illustrating the effectiveness of the DeePCG model on a rather challenging task

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Evaluating the active site-substrate interplay between x-ray crystal structure and molecular dynamics in chorismate mutase

Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows.

Chemistry↗
DOE OSTI2024

Optical conductivity of overdoped cuprates from ab initio out-of-plane impurity potentials

Dopant impurity potentials determined by ab initio supercell density functional theory calculations are used to calculate the optical conductivity of overdoped La 2-x ⁢Sr x CuO 4 (LSCO) and Tl 2 ⁢Ba 2⁢ CuO 6+δ (Tl-2201) in the superconducting and normal states. Vertex corrections are included to account for the effect of forward scattering on two-particle properties. This approach was previously shown to provide good, semiquantitative agreement with measurements of superfluid density in LSCO. Here, in this study, we compare calculations of conductivity with measurements of terahertz conductivity on LSCO using identical impurity, band, and correlation parameters and find similarly good correspondence with experiment. In the process, we delineate the impact of the different disorder mechanisms on single-particle and transport relaxation processes. In particular, we reveal the critical role of apical oxygen vacancies in transport scattering and show that transport relaxation rates in LSCO are significantly reduced when apical oxygen vacancies are annealed out. These considerations are shown to be crucial for understanding the variability of experimental results for overdoped LSCO in samples of nominally identical doping but different types. Finally, we give predictions for Tl-2201 terahertz conductivity experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Moleculo Long-Read Sequencing Facilitates Assembly and Genomic Binning from Complex Soil Metagenomes

ABSTRACT Soil metagenomics has been touted as the “grand challenge” for metagenomics, as the high microbial diversity and spatial heterogeneity of soils make them unamenable to current assembly platforms. Here, we aimed to improve soil metagenomic sequence assembly by applying the Moleculo synthetic long-read sequencing technology. In total, we obtained 267 Gbp of raw sequence data from a native prairie soil; these data included 109.7 Gbp of short-read data (~100 bp) from the Joint Genome Institute (JGI), an additional 87.7 Gbp of rapid-mode read data (~250 bp), plus 69.6 Gbp (>1.5 kbp) from Moleculo sequencing. The Moleculo data alone yielded over 5,600 reads of >10 kbp in length, and over 95% of the unassembled reads mapped to contigs of >1.5 kbp. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. We mapped three replicate metatranscriptomes derived from the same parent soil to the Moleculo subassembly and found that 95% of the predicted genes, based on their assignments to Enzyme Commission (EC) numbers, were expressed. The Moleculo subassembly also enabled binning of >100 microbial genome bins. We obtained via direct binning the first complete genome, that of “ Candidatus Pseudomonas sp. strain JKJ-1” from a native soil metagenome. By mapping metatranscriptome sequence reads back to the bins, we found that several bins corresponding to low-relative-abundance Acidobacteria were highly transcriptionally active, whereas bins corresponding to high-relative-abundance Verrucomicrobia were not. These results demonstrate that Moleculo sequencing provides a significant advance for resolving complex soil microbial communities. IMPORTANCE Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental perturbations. This knowledge gap is largely due to the difficulty in culturing the majority of soil microbes. Thus, use of culture-independent approaches, such as metagenomics, promises the direct assessment of the functional potential of soil microbiomes. Soil is, however, a challenge for metagenomic assembly due to its high microbial diversity and variable evenness, resulting in low coverage and uneven sampling of microbial genomes. Despite increasingly large soil metagenome data volumes (>200 Gbp), the majority of the data do not assemble. Here, we used the cutting-edge approach of synthetic long-read sequencing technology (Moleculo) to assemble soil metagenome sequence data into long contigs and used the assemblies for binning of genomes. Author Video : An author video summary of this article is available.

De Novo assembly↗
DOE OSTI2024

Subsurface microbial community structure shifts along the geological features of the Central American Volcanic Arc

Subduction of the Cocos and Nazca oceanic plates beneath the Caribbean plate drives the upward movement of deep fluids enriched in carbon, nitrogen, sulfur, and iron along the Central American Volcanic Arc (CAVA). These compounds fuel diverse subsurface microbial communities that in turn alter the distribution, redox state, and isotopic composition of these compounds. Microbial community structure and functions vary according to deep fluid delivery across the arc, but less is known about how microbial communities differ along the axis of a convergent margin as geological features (e.g., extent of volcanism and subduction geometry) shift. Here, we investigate changes in bacterial 16S rRNA gene amplicons and geochemical analysis of deeply-sourced seeps along the southern CAVA, where subduction of the Cocos Ridge alters the geological setting. We find shifts in community composition along the convergent margin, with communities in similar geological settings clustering together independently of the proximity of sample sites. Microbial community composition correlates with geological variables such as host rock type, maturity of hydrothermal fluid and slab depth along different segments of the CAVA. This reveals tight coupling between deep Earth processes and subsurface microbial activity, controlling community distribution, structure and composition along a convergent margin.

Science & Technology - Other Topics↗
DOE OSTI2022

Technical Guidance on Use of the Linseis Vertical Dilatometer L75

Linseis vertical Dilatometer L75 thermal expansion equipment is a complete system which can be used for measuring change of the absolute length of a sample, determination of the thermal expansion coefficient (CTE), shrinkage, and sintering. The 238 Pu Supply Program is interested in re-establishing the capability to determine CTE and measuring the change of the absolute length of various 237 Np Al/cermet samples during heating. The change in length of the measured sample is recorded using a highly sensitive Linear Variable Differential Transformer (LVDT). The dilatometer is user-friendly and simple to operate which will allow technicians to be trained easily on its use. This equipment was designed to be used specifically for ceramics. It has a highly vacuum tight push rod dilatometer, a high-resolution inductive transducer using innovative and comprehensive temperature controls which provide excellent performance as a measurement system yielding high accuracy, reproducibility, and long-term stability.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Report on technical development in ANL for innovative creep testing and measurement

This report summarizes a research effort undertaken by Argonne National Laboratory to accelerate the development of creep data package for ASME code qualification. Progress on the fabrication of a 3-sample load train and the application of a direct current potential drop (DCPD) technique to measure large creep strains are reported. Specifically: (1) The 3-sample load train, with three sets of Linear Variable Differential Transformers (LVDT), has been fabricated and assembled. (2) A DCPD method for creep-strain measurement up to 50% has been demonstrated. The DCPD data matches very well to LVDT results, suggesting its potential application in future creep testing. The technical developments contribute towards shortening the time needed to generate a creep data package for an ASME code case of the laser powder bed fusion 316H stainless steel, an effort under the US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Radiocarbon measurements of ecosystem respiration and soil pore-space CO 2 in Utqiagvik (Barrow), Alaska

Radiocarbon measurements of ecosystem respiration and soil pore space CO 2 are useful for determining the sources of ecosystem respiration,identifying environmental controls on soil carbon cycling rates, and parameterizing and evaluating models of the carbon cycle. We measured flux rates and radiocarbon content of ecosystem respiration, as well as radiocarbon in soil profile CO 2 in Utqiagvik (Barrow), Alaska, during the summers of 2012, 2013, and 2014.We found that radiocarbon in ecosystem respiration(Δ 14 C Reco ) ranged from +60.5 to –160‰ with a median value of +23.3‰. Ecosystem respiration became more depleted in radiocarbon from summer to autumn, indicating increased decomposition of old soil organic carbon and/or decreased CO 2 production from fast-cycling carbon pools. Across permafrost features,ecosystem respiration from high-centered polygons was depleted in radiocarbon relative to other polygon types. Radiocarbon content in soil pore-space CO 2 varied between –7.1 and –280‰, becoming more negative with depth in individual soil profiles. These pore-space radiocarbon values correspond to CO 2 mean ages of 410 to 3350 years, based on a steady-state, one-pool model. Together, these data indicate that deep soil respiration was derived primarily from old, slow-cycling carbon, but that total CO 2 fluxes depended largely on autotrophic respiration and heterotrophic decomposition of fast-cycling carbon within the shallowest soil layers. The relative contributions of these different CO 2 sources were highly variable across microtopographic features and time in the sampling season. The highly negative Δ 14 C values in soil pore-space CO 2 and autumn ecosystem respiration indicate that when it is not frozen, very old soil carbon is vulnerable to decomposition.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1970

Normally Expected Aberrations in the 8-hour Dynamic EKG

The establishment of norms for interpreting long term dynamic electrocardiograms is attempted by correlating a completely disease symptom and cardiac risk factor free sample with a non-pure sample in the direction of normality on various variables. Out of a population of 362 subjects exposed to dynamic electrocardiogram testing, a discrimination between normals and abnormals in terms of traditional risk factors was observed. The two groups differed significantly on the following variables: cholesterol, smoking, systolic blood pressure, white blood count, fasting blood sugar, uric acid, resting EKG, year of birth, and coronary insufficiency.

Fleck, R. L.↗
NASA NTRS1979

Lunar sample analysis

The surface composition of two samples from the highly shocked, glass-coated lunar basalt (12054) and from four glass-coated fragments from the 1-2 mm (14161) fines were examined by X-ray photoemission spectroscopy to determine whether the agglutination process itself is responsible for the difference between their surface and bulk compositions. Auger electron spectroscopy of glass balls from the 15425 and 74001 fines were analyzed to understand the nature, extent, and behavior of volatile phases associated with lunar volcanism. Initial results indicate that (1) volatiles, in the outer few atomic layers sampled, vary considerably from ball to ball; (2) variability over the surface of individual balls is smaller; (3) the dominant volatiles on the balls are S and Zn; and (4) other volatiles commonly observed are P, Cl, and K.

Housley, R. M.↗
NASA NTRS1982

Solar and late-type dwarfs

The Einstein Observatory's and the IUE's contributions to knowledge of coronal formation in late-type stars are discussed. The HR diagram of stars seen as X-ray sources by these observatories is presented, and the influence of rotation on X-ray emission is reviewed. Emission from the Alpha Cen system and from active stars with quiescent coronae is examined, and the extent of the contribution of emission from normal stars to the soft X-ray background is addressed. The quiescent and flare emission from Alpha Cen, the temporal variability of X-ray emission from a sample of active chromosphere stars, and the predicted contribution of chromospheric emission to the diffuse soft X-ray background are depicted. Chromospheric indicators of activity are discussed, the connection between surface magnetic fields and X-ray emission in the chromosphere is briefly reviewed, and the quantitative links between X-ray data and magnetic fields is summarily presented.

Golub, L.↗
NASA NTRS1993

Nonlinear probabilistic finite element models of laminated composite shells

A probabilistic finite element analysis procedure for laminated composite shells has been developed. A total Lagrangian finite element formulation, employing a degenerated 3-D laminated composite shell with the full Green-Lagrange strains and first-order shear deformable kinematics, forms the modeling foundation. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed and results are presented in the form of mean and variance of the structural response. The effects of material nonlinearity are included through the use of a rate-independent anisotropic plasticity formulation with the macroscopic point of view. Both ply-level and micromechanics-level random variables can be selected, the latter by means of the Aboudi micromechanics model. A number of sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. Experimental data is compared in many cases, and the Monte Carlo simulation method is used to check the probabilistic results. In general, the procedure is quite effective in modeling the mean and variance response of the linear and nonlinear behavior of laminated composite shells.

Engelstad, S. P.↗
NASA NTRS1996

Quantification of Bone Growth Rate Variability in Rats Exposed to Micro- (near zero G) and Macrogravity (2G)

Our stated primary objective is to quantify the growth rate variability of rat lamellar bone exposed to micro and macrogravity (2G). The primary significance of the proposed work is that an elegant method will be established that unequivocally characterizes the morphological consequences of gravitational factors on developing bone. The integrity of this objective depends upon our successful preparation of thin sections suitable for imaging individual bone lamellae, and our imaging and quantitation of growth rate variability in populations of lamellae from individual bone samples.

Bromage, Timothy G.↗
NASA NTRS1997

Quantitation of Bone Growth Rate Variability in Rats Exposed to Micro-(near zero G) and Macrogravity (2G)

Our stated primary objective is to quantify the growth rate variability of rat lamellar bone exposed to micro- (near zero G: e.g., Cosmos 1887 & 2044; SLS-1 & SLS-2) and macrogravity (2G). The primary significance of the proposed work is that an elegant method will be established that unequivocally characterizes the morphological consequences of gravitational factors on developing bone. The integrity of this objective depends upon our successful preparation of thin sections suitable for imaging individual bone lamellae, and our imaging and quantitation of growth rate variability in populations of lamellae from individual bone samples.

Bromage, Timothy G.↗