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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Requirements and sensitivity analysis for temporally- and spatially-resolved thermometry using neutron resonance spectroscopy

Neutron resonance spectroscopy (NRS) has been used extensively to make temperature measurements that are accurate, absolute, and nonperturbative within the interior of material samples under extreme conditions applied quasistatically. Yet NRS has seldom been used in dynamic experiments. There is a compelling incentive to do so because of the significant shortcomings of alternative techniques. An important barrier to adopting dynamic NRS thermometry is the difficulty in fielding it with conventional spallation neutron sources. To enable time-dependent and spatially resolved temperature measurements in dynamic environments, more compact neutron sources that can be used at user facilities in conjunction with other diagnostic probes (such as x-ray light sources) are required. Such sources may be available using ultrafast high-intensity optical lasers. We evaluate such possibilities by determining the sensitivities of the temperature estimate on neutron-beam and diagnostic parameters. Based on that evaluation, requirements are set on a pulsed neutron-source and diagnostics to make a meaningful dynamic temperature measurement. Dynamic thermometry measurements are examined in this context when driven by two alternative fast-neutron sources: the Los Alamos Neutron Scattering Center (LANSCE) proton accelerator driving isotropic spallation neutrons as a baseline and a laser-plasma ion accelerator driving a neutron beam from deuterium breakup. Strategies to close the gap between the required and demonstrated performance of laser-based fast-neutron sources are presented. A short-pulse high-intensity laser with state-of-the-art pulse contrast and an energy of a few hundred Joules would drive a compact neutron source suitable for NRS thermometry that could transform the dynamic study of materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Thermomechanical response of thickly tamped targets and diamond anvil cells under pulsed hard x-ray irradiation

In the laboratory study of extreme conditions of temperature and density, the exposure of matter to high intensity radiation sources has been of central importance. Here, we interrogate the performance of multi-layered targets in experiments involving high intensity, hard x-ray irradiation, motivated by the advent of extremely high brightness hard x-ray sources, such as free electron lasers and 4th-generation synchrotron facilities. Intense hard x-ray beams can deliver significant energy in targets having thick x-ray transparent layers (tampers) around samples of interest for the study of novel states of matter and materials’ dynamics. Heated-state lifetimes in such targets can approach the microsecond level, regardless of radiation pulse duration, enabling the exploration of conditions of local thermal and thermodynamic equilibrium at extreme temperature in solid density matter. The thermal and mechanical responses of such thick layered targets following x-ray heating, including hydrodynamic relaxation and heat flow on picosecond to millisecond timescales, are modeled using radiation hydrocode simulation, finite element analysis, and thermodynamic calculations. Assessing the potential for target survival over one or more exposures and resistance to damage arising from heating and resulting mechanical stresses, this study doubles as an investigation into the performance of diamond anvil high pressure cells under high x-ray fluences. Long used in conjunction with synchrotron x-ray radiation and high power optical lasers, the strong confinement afforded by such cells suggests novel applications at emerging high intensity x-ray facilities and new routes to studying thermodynamic equilibrium states of warm, very dense matter.

Meza-Galvez, J. (ORCID:000000032699849X)↗
DOE OSTI2023

Solvation of furfural at metal–water interfaces: Implications for aqueous phase hydrogenation reactions

Metal–water interfaces are central to understanding aqueous-phase heterogeneous catalytic processes. However, the explicit modeling of the interface is still challenging as it necessitates extensive sampling of the interfaces’ degrees of freedom. Herein, we use ab initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal–water interfaces (Pt, Rh, Pd, Cu, and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal–water interfaces compared to the metal–gas interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural, further evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy as a good descriptor to estimate the solvation energies of furfural. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption prevent surface poisoning. In conclusion, our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates.

aqueous-phase hydrogenation↗
DOE OSTI2023

Dynamic mode decomposition for extrapolating nonequilibrium Green's-function dynamics

The Hartree-Fock generalized Kadanoff-Baym ansatz (HF-GKBA) offers an approximate numerical procedure for propagating the two-time nonequilibrium Green's function (NEGF). Here, using the GW self-energy, we compare the HF-GKBA to exact results for a variety of systems with long- and short-range interactions, different two-body interaction strengths, and various nonequilibrium preparations. We find excellent agreement between the HF-GKBA and exact time evolution in models when more realistic long-range exponentially decaying interactions are considered. Furthermore, this agreement persists for long times and for intermediate to strong interaction strengths. In large systems, HF-GKBA becomes prohibitively expensive for long-time evolutions. For this reason, we look at the use of dynamical mode decomposition (DMD) to reconstruct long-time NEGF trajectories from a sample of the initial trajectory. Using no more than 16% of the total time evolution, we reconstruct the total trajectory with high fidelity. Our results show the potential for DMD to be used in conjunction with HF-GKBA to calculate long-time trajectories in large-scale systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Dynamical tuning of the chemical potential to achieve a target particle number in grand canonical Monte Carlo simulations

We present a method to facilitate Monte Carlo simulations in the grand canonical ensemble given a target mean particle number. The method imposes a fictitious dynamics on the chemical potential, to be run concurrently with the Monte Carlo sampling of the physical system. Corrections to the chemical potential are made according to time-averaged estimates of the mean and variance of the particle number, with the latter being proportional to thermodynamic compressibility. Here, we perform a variety of tests, and in all cases find rapid convergence of the chemical potential—inexactness of the tuning algorithm contributes only a minor part of the total measurement error for realistic simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand–maximize–compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Ecological Assembly Processes Are Coordinated between Bacterial and Viral Communities in Fractured Shale Ecosystems

The ecological drivers that concurrently act upon both a virus and its host and that drive community assembly are poorly understood despite known interactions between viral populations and their microbial hosts. Hydraulically fractured shale environments provide access to a closed ecosystem in the deep subsurface where constrained microbial and viral community assembly processes can be examined. Here, we used metagenomic analyses of time-resolved-produced fluid samples from two wells in the Appalachian Basin to track viral and host dynamics and to investigate community assembly processes. Hypersaline conditions within these ecosystems should drive microbial community structure to a similar configuration through time in response to common osmotic stress. However, viral predation appears to counterbalance this potentially strong homogeneous selection and pushes the microbial community toward undominated assembly. In comparison, while the viral community was also influenced by substantial undominated processes, it assembled, in part, due to homogeneous selection. When the overall assembly processes acting upon both these communities were directly compared with each other, a significant relationship was revealed, suggesting an association between microbial and viral community development despite differing selective pressures. These results reveal a potentially important balance of ecological dynamics that must be in maintained within this deep subsurface ecosystem in order for the microbial community to persist over extended time periods. More broadly, this relationship begins to provide knowledge underlying metacommunity development across trophic levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Measurement of Degree of Compaction of Fine-Grained Soil Subgrade Using Light Dynamic Penetrometer

To determine the degree of compaction of subgrades filled with fine-grained soil, the compaction test and light dynamic penetrometer (LDP) test were carried out for low liquid-limit clay samples with different water contents in laboratory. Then, a prediction equation of the penetration ratio (PR) defined as the depth per drop of the hammer of LDP, degree of compaction ( K ), and water content ( ω ) was built. After that, the existing fine-grained soil subgrades on LDP-based field tests were excavated. The on-site PR values, water contents, and degrees of compaction of slopes were obtained. The estimated degrees of compaction using the prediction equation were compared with measured values of the degree of compaction in field. The results show that there is good consistency between them, and an error within 3.5% was obtained. In addition, the water content should be determined firstly while using the prediction equation which is proposed in this study. Therefore, a numerical method of the water content of a subgrade was developed, and the predicted and measured water contents were compared, which shows a relatively high relativity. Then, the degree of compaction of fine-grained soil subgrades can be calculated according to the predicting equation, which involves the penetration ratio (PR) and the numerically calculated water content as input instead of the measured value in the field.

Zhang, Junhui↗
DOE OSTI2016

Genetic Variability of West Nile Virus in U.S. Blood Donors from the 2012 Epidemic Season

West Nile virus (WNV) is an arbovirus maintained in nature in a bird-mosquito enzootic cycle which can also infect other vertebrates including humans. WNV is now endemic in the United States (U.S.), causing yearly outbreaks that have resulted in an estimated total of 4–5 million human infections. Over 41,700 cases of West Nile disease, including 18,810 neuroinvasive cases and 1,765 deaths, were reported to the CDC between 1999 and 2014. In 2012, the second largest West Nile outbreak in the U.S. was reported, which caused 5,674 cases and 286 deaths. WNV continues to evolve, and three major WNV lineage I genotypes (NY99, WN02, and SW/WN03) have been described in the U.S. since introduction of the virus in 1999. We report here the WNV sequences obtained from 19 human samples acquired during the 2012 U.S. outbreak and our examination of the evolutionary dynamics in WNV isolates sequenced from 1999–2012. Maximum-likelihood and Bayesian methods were used to perform the phylogenetic analyses. Selection pressure analyses were performed with the HyPhy package using the Datamonkey web-server. Using different codon-based and branch-site selection models, we detected a number of codons subjected to positive pressure in WNV genes. Thirteen of the 19 completely sequenced isolates from 10 U.S. states were genetically similar, sharing up to 55 nucleotide mutations and 4 amino acid substitutions when compared with the prototype isolate WN-NY99. Altogether, these analyses showed that following a brief contraction in 2008–2009, WNV genetic divergence in the U.S. continued to increase in 2012, and that closely related variants were found across a broad geographic range of the U.S., coincident with the second-largest WNV outbreak in U.S. history.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Scripts and data associated with a manuscript linking soil and sediment elemental composition with dissolved organic matter chemistry across CONUS

This data package provides scripts and geochemical data for a manuscript titled “Linkages between mineral element composition of soils and sediments with hyporheic zone dissolved organic matter chemistry across the contiguous United States” (preprint: doi: 10.22541/essoar.169447343.31694990/v1). This data is associated with the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS, https://whondrs.pnnl.gov) and is an extension of the Summer 2019 Sampling campaign which crowdsourced samples from rivers and sediment across the continental United States. Data from this study can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719. The main objective of this manuscript was to couple sediment water extractable dissolved organic matter chemistry, defined by ultra-high resolution mass spectrometry, with localized sediment elemental composition and watershed scale soil elemental characteristics. This data package contains one main folder with four subfolders. The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) an R markdown to reproduce manuscript figures and analyses; (5) a pdf of instructions to reproduce NGS interpolations with ArcGIS software; and (6) a python script to reproduce NGS extrapolations with python. The four subfolders contain files required to reproduce NGS extrapolations include (1) ‘CONUS_boundaries’ containing boundary layers (.shp) for the Continental United States; (2) ‘ngs_project’ containing files (.shp) with point level NGS soil elemental data (Grossman et al., 2004); (3) ‘raster_outputs’ containing the interpolated raster output files for various soil elements; and (4) ‘NGS_Chemistry_Final’ contain final extracted soil elemental data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Linking the Codependence of Grain Boundary Structure and Density to Defect Evolution Mechanisms during Radiation Damage

There is little understanding of the direct link between grain boundary character and density, and defect denuded zones. For example, the role of reduced grain size to the nanocrystalline regime and subsequent increase in grain boundary density is not fully understood in the context of dislocation or void behavior near grain boundaries. In addition, little is understood experimentally on how defect absorption changes the structure of the grain boundary during irradiation and may play a role in the migration of defects and solutes. This work aims to define a framework for understanding the origin of radiation damage mechanisms in model BCC and FCC nanocrystalline materials, on which a foundation of radiation tolerant material development can be built. The key questions that will be addressed by this work are: 1. What is the influence of GB density and GB character (GBC) on radiation damage accumulation near grain boundaries in model nanocrystalline FCC and BCC alloys; how are these two effects connected? 2. In the context of radiation induced segregation (RIS), what effect does species dependent interstitial diffusion have on the GB chemistry in light of these two dependencies? 3. How does grain boundary sink efficiency evolve with radiation over time? In situ and analytical transmission electron microscopy techniques are used to study both pure and alloy nanocrystalline materials under irradiation. TEM samples prepared from thin films will be irradiated in-situ, allowing for dynamic observation of the behavior of the alloy under ion irradiation. The key findings from this program were (1) the control of thin film texture via sputtering; (2) the development of characterization tools for defects and grain boundary quantification; (3) the development of new techniques for defect characterization toward high throughput analysis; (4) a mapped out parameter space for defect evolution as a function of grain size and grain boundary character; and finally (5) an indication of sink efficiency and its stability during irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Iodine Waste Form Corrosion: PNNL Summary Testing Report

A test method to correlate the laboratory corrosion behavior of iodine-containing waste forms (IWFs) to a conceptual long-term corrosion models is required. Several candidate methods have been evaluated previously, and each method presents unique challenges and limitations. Dynamic leach tests have emerged as the preferred candidate test method to evaluate IWFs and parameterize an eventual long-term corrosion model. This report was prepared in support of this effort to define the test suite to evaluate the corrosion of IWFs, with the goal of defining and parameterizing a conceptual long-term corrosion model. A review was presented highlighting the high degree of variability between the IWF corrosion data that is available in the literature and the need for a standardized test suite. The targeted test suite is composed of a single interval screening test, a dynamic leach test, and post-test solid characterization of the monolithic IWF samples. The data presented serves two purposes: to expand the range of IWFs evaluated with the test suite to assess method variability and to further understand the corrosion of IWFs to best inform conceptual long-term corrosion model development. A series of IWF types were included in the testing, including hot isostatically pressed Ag-mordenite, silver functionalized silica-based aerogels, iodosodalites (hot isostatic pressing, sintered, glass bonded ceramic), iodoapatite, tellurite glass and glass composite materials.

42 ENGINEERING↗
DOE OSTI2021

Efficient Learning of Accurate Surrogates for Simulations of Complex Systems

Machine learning methods are increasingly deployed to construct surrogate models for complex physical systems at a reduced computational cost. However, the predictive capability of these surrogates degrades in the presence of noisy, sparse, or dynamic data. We introduce an online learning method empowered by optimizer-driven sampling that has two advantages over current approaches: it ensures that all local extrema (including endpoints) of the model response surface are included in the training data and it employs a continuous validation and update process in which surrogates undergo retraining when their performance falls below a validity threshold. We find, using benchmark functions, that optimizer-directed sampling generally outperforms traditional sampling methods in terms of accuracy around local extrema even when the scoring metric is biased towards assessing overall accuracy. Finally, the application to dense nuclear matter demonstrates that highly accurate surrogates for a nuclear equation of state model can be reliably auto-generated from expensive calculations using few model evaluations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data (Sup3rWind) and Application to Ukraine [Slides]

In this work we present a novel deep learning-based downscaling method, using generative adversarial networks (GANs), for generating high-resolution wind resource data from ECMWF Reanalysis v5 data (ERA5). We show that by training a GAN model on ERA5, as opposed to coarsened high-resolution data, we achieve results that are competitive with conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. All GANs are trained on data sampled from CONUS, selected to provide a diverse sampling of terrain conditions, and validated on observational data along with data held out from training. This cross-validation shows low error and high correlations with observations and excellent agreement with hold out data across physical distributions. Our approach is finally used to downscale 30km hourly ERA5 to 2-km 5-minute wind data, for January 2000 through December 2023, at multiple hub heights, over Ukraine, Moldova, and part of Romania. Comparisons against observational data from Meteorological Assimilation Data Ingest System (MADIS) and multiple wind farms show the same level of performance as for CONUS validation. This 24 year data record is the first member of the "super resolution for renewable energy resource data with wind from reanalysis data" dataset (Sup3rWind).

17 WIND ENERGY↗
DOE OSTI2022

Updated HIV-1 Consensus Sequences Change but Stay Within Similar Distance From Worldwide Samples

HIV consensus sequences are used in various bioinformatic, evolutionary, and vaccine related research. Since the previous HIV-1 subtype and CRF consensus sequences were constructed in 2002, the number of publicly available HIV-1 sequences have grown exponentially, especially from non-EU and US countries. Here, we reconstruct 90 new HIV-1 subtype and CRF consensus sequences from 3,470 high-quality, representative, full genome sequences in the LANL HIV database. While subtypes and CRFs are unevenly spread across the world, in total 89 countries were represented. For consensus sequences that were based on at least 20 genomes, we found that on average 2.3% (range 0.8–10%) of the consensus genome site states changed from 2002 to 2021, of which about half were nucleotide state differences and the rest insertions and deletions. Interestingly, the 2021 consensus sequences were shorter than in 2002, and compared to 4,674 HIV-1 worldwide genome sequences, the 2021 consensuses were somewhat closer to the worldwide genome sequences, i.e., showing on average fewer nucleotide state differences. Some subtypes/CRFs have had limited geographical spread, and thus sampling of subtypes/CRFs is uneven, at least in part, due to the epidemiological dynamics. Thus, taken as a whole, the 2021 consensus sequences likely are good representations of the typical subtype/CRF genome nucleotide states. The new consensus sequences are available at the LANL HIV database.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Efficient SABRE-SHEATH Hyperpolarization of Potent Branched-Chain-Amino-Acid Metabolic Probe [1-13C]ketoisocaproate

Efficient 13C hyperpolarization of ketoisocaproate is demonstrated in natural isotopic abundance and [1-13C]enriched forms via SABRE-SHEATH (Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei). Parahydrogen, as the source of nuclear spin order, and ketoisocaproate undergo simultaneous chemical exchange with an Ir-IMes-based hexacoordinate complex in CD3OD. SABRE-SHEATH enables spontaneous polarization transfer from parahydrogen-derived hydrides to the 13C nucleus of transiently bound ketoisocaproate. 13C polarization values of up to 18% are achieved at the 1-13C site in 1 min in the liquid state at 30 mM substrate concentration. The efficient polarization build-up becomes possible due to favorable relaxation dynamics. Specifically, the exponential build-up time constant (14.3 ± 0.6 s) is substantially lower than the corresponding polarization decay time constant (22.8 ± 1.2 s) at the optimum polarization transfer field (0.4 microtesla) and temperature (10 °C). The experiments with natural abundance ketoisocaproate revealed polarization level on the 13C-2 site of less than 1%—i.e., one order of magnitude lower than that of the 1-13C site—which is only partially due to more-efficient relaxation dynamics in sub-microtesla fields. We rationalize the overall much lower 13C-2 polarization efficiency in part by less favorable catalyst-binding dynamics of the C-2 site. Pilot SABRE experiments at pH 4.0 (acidified sample) versus pH 6.1 (unaltered sodium [1-13C]ketoisocaproate) reveal substantial modulation of SABRE-SHEATH processes by pH, warranting future systematic pH titration studies of ketoisocaproate, as well as other structurally similar ketocarboxylate motifs including pyruvate and alpha-ketoglutarate, with the overarching goal of maximizing 13C polarization levels in these potent molecular probes. Finally, we also report on the pilot post-mortem use of HP [1-13C]ketoisocaproate in a euthanized mouse, demonstrating that SABRE-hyperpolarized 13C contrast agents hold promise for future metabolic studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1971

On quasar evolution.

We examine the consequences for quasar statistics of a class of models describing the evolution of individual strong sources. The continuity equation for the change of density and luminosity with cosmological epoch determines the population, once a model for the evolution of an individual object is chosen. A dynamical model of spinning objects seems to agree satisfactorily with the present observational sample, both in density and in luminosity function; such a model requires that an individual object strongly brightens as time goes on. A genetic relationship between quasars and radio galaxies which qualitatively fits the observations is suggested by the model.

Cavaliere, A.↗
NASA NTRS1982

Modeling of human operator dynamics in simple manual control utilizing time series analysis

Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.

Agarwal, G. C.↗