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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Solubility Comparison of Cyclotetramethylenetetranitramine (HMX) and Potential Mock-HMX Candidates in Solvents Relevant to Slurry Formulating Polymer-Bonded Materials

Understanding solubility behavior of organic crystalline materials is critical in the development of slurry-formulated plastic bonded composites. In the field of high explosives (HE), a common method for obtaining high density, greater than 95 % theoretical maximum density, is to encapsulate HE in a polymer matrix resulting in the formation of plastic bonded explosive (PBX) prills. Prill formation is highly nuanced and requires understanding of particle size distributions, solvent, antisolvent, and binder system as well as interactions thereof. In this paper, in an effort to create mock-HE that mimics HE in density and mechanical strength, solubility of candidate molecules was compared to cyclotetramethylenetetranitramine (HMX) in binder solvents relevant to prill formation. The results indicate that the mock candidates chosen for this study have different solubilities compared to HMX in water and both organic solvents, 2-butanone and ethyl acetate, investigated. With these solubility differences known, prills to match PBXs based on HMX can be formulated, pressed and tested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Production of highly-enriched 134Ba for a reference material for isotope dilution mass spectrometry measurements

Isotope dilution mass spectrometry (IDMS) is an analytical technique capable of providing accurate and precise quantitation of trace isotope abundance and assay providing measurement uncertainties below 1 %. To achieve these low uncertainties, the IDMS method ideally utilizes chemically pure “spike” solutions that consist of a single highly enriched isotope that is well-characterized relating to the abundance of companion isotopes and concentration in solution. To address a current demand for accurate 137Cs/137Ba ratio measurements for “age” determination of radioactive 137Cs sources, Idaho National Laboratory (INL) is producing enriched 134Ba isotopes that are tobe used for IDMS spikes to accurately determine 137Ba accumulation from the decay of 137Cs. The final objective of this work it to provide a homogenous set of reference materials that the National Institute of Standards and Technology can certify as standard reference materials used for IDMS. The process that was developed at INL for the separation and isolation of Ba isotopes, chemical purification of the isotopes in solution, and the encapsulation of the materials will be described.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

A method to quantify the 37 Ar emanation fraction in powders and rocks

In order to make predictions of the potential 37 Ar signal from an underground nuclear explosion, a value for the 37 Ar emanation fraction is needed. Here, a system was developed to quantify the emanation fraction from samples ranging in size from powder to small rocks. Assorted rock samples were irradiated with Watt fission spectrum neutrons to produce radioactive argon gas via activation of calcium. The argon produced was extracted on a custom apparatus and cryogenically trapped. The extracted gas was then processed to separate the argon and load it into a proportional counter for counting. The emanation fraction of argon gas from the rock samples was then calculated by comparing the measured and predicted activities.

37Ar↗
DOE OSTI2024

Investigating sol–gel matrix loading capacity toward producing surrogate nuclear explosive debris with realistic composition

Post detonation nuclear forensic materials which resemble the size, color, elemental composition, and radionuclide content of real nuclear debris would be valuable for developing and validating new nuclear forensic techniques. As nuclear fallout types vary significantly, the ability to tailor each of these parameters accurately is desired to produce materials capable of testing analytical methods under a wide array of forensic scenarios. Sol–gel synthesis techniques can provide tunability of size, shape and composition for producing a wide variety of solid nuclear forensics benchmarking materials. Further, the sol–gel process consists of forming a metal oxide material, often silica, through polymerization of a metal-alkoxy precursor. In this work, we characterize the ability to load sol–gel particles with secondary elemental components such as iron, aluminum, and calcium toward producing benchmarking materials approximating the elemental composition of historic nuclear debris from the Nevada National Security Site. We also demonstrate quantitative radionuclide encapsulation toward producing benchmarking materials with controllable radionuclide content. Finally, we employ these techniques to produce nuclear debris benchmarking materials with controllable elemental matrix composition and radionuclide content and compare these samples with the composition of a historic fallout sample previously reported from the Nevada National Security Site.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Inclusion complexes formed in lanthanide—amino acid—β-cyclodextrin systems

Interactions in lanthanide—amino acid—β-cyclodextrin systems (amino acid = tryptophan, phenylalanine; lanthanide = Eu{sup 3}+, Pr{sup 3}+) were studied in aqueous solution. An analysis of the chemical shifts observed in the {sup 1}H NMR spectra, as well as the ROESY data suggest the possibility for amino acid—lanthanide ion complexes encapsulated in the β-cyclodextrin cavity to form in solution. According to ROESY data, the indole ring of tryptophan and the phenyl group of phenylalanine enter the β-CD cavity from the wide rim side. Coordination with the metal ion occurs through the amino acid carboxyl group.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Synthesis and Magnetic Properties of Fe–Co–Ni/С Nanocomposites

Nanoparticles of the Fe–Co–Ni ternary alloy, encapsulated in the carbon matrix of nanocomposites, have been synthesized, The structure, phase composition, and magnetic properties of the obtained materials have been determined with the help of diffractometry and magnetometry. It has been established that nanoparticles of the ternary alloy are formed due to solution of cobalt in the Fe–Ni alloy. The composition of the nanoparticles of the alloy depends on the mass percent ratio of the metas in the precursor. With growth of the iron content, nanoparticles of the ternary alloy with various composition are formed with FCC and BCC crystal lattice structure. As the synthesis temperature and relative iron content are increased, the magnetization of the Fe–Co–Ni/C nanocomposites increases from 26 to 157 A·m{sup 2}/kg. The coercive force is determined by the synthesis temperature, the size of the nanoparticles, and the composition of the alloy, and its value varies from 330 to 43 Oe.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Splittings, Satellites and Fine Structure in the Soft X-ray Spectroscopy of the Actinides

Perhaps the most demanding and powerful actinide spectroscopy is that using soft X-ray and VUV photons. Because of the relatively low energy and fairly small sampling depths of these photons and the corresponding electrons, it is necessary to use un-encapsulated samples with highly cleaned and well-prepared surfaces. This causes a myriad of sample containment problems for these radioactive materials. Despite these hindrances and difficulties, the soft-X-ray and ultra-violet spectroscopy of the actinides can provide an amazing level of detailed information, particularly having to do with 5f electronic structure. In this paper, the splittings, satellites and fine structure of the following actinide soft X-ray spectroscopies will be discussed: X-ray photoelectron spectroscopy; X-ray absorption spectroscopy; and inverse photoelectron spectroscopy, including Bremstrahlung isochromat spectroscopy and resonant inverse photoelectron spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Integrating the Fields of Catalysis: Active Site Engineering in Metal Cluster, Metal Organic Framework and Metal Single Site

Research evolved using nanoparticles synthesized and characterized under reaction conditions opened the door to study all three fields of catalysis: heterogeneous, homogenous, and enzyme. Fundamental studies of catalytic reactions ranging from hydrogenation to understand Fischer-Tropsch synthesis and isomerization ultimately led to the integration of three fields of catalysis. Our recent work on bridging heterogeneous, homogenous, and enzymatic catalysis was present including functionalization of dendrimer encapsulated metal clusters surface for lactonization, active site engineering in metal organic framework catalysts for methanol production and oligomerization, and single site catalyst for hydrogen production. We envision that the combination of active site engineering and unifying fields of catalysis could be applied to solve practical issues of science-based technology and develop new fields useful in energy research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Titanium Sheet Fabricated from Powder for Industrial Applications

In collaboration with Ametek and Commonwealth Scientific and Industrial Research Organization (CSIRO), Oak Ridge National Laboratory has evaluated three different methods for converting titanium hydride-dehydride (HDH) powder into thin gauge titanium sheet from a roll compacted preform. Methodologies include sintering, followed by cold rolling and annealing; direct hot rolling of the roll-compacted sheet; and hot rolling of multiple layers of roll compacted sheet that are encapsulated in a steel can. All three methods have demonstrated fully consolidated sheet, and each process route has the ability to produce sheet that meets ASTM B265 specifications. However, not every method currently provides sheet that can be highly formed without tearing. The degree of sintering between powder particles, post processing density, and the particle to particle boundary layer where compositional variations may exist, have a significant effect on the ability to form the sheet into useful components. Uniaxial tensile test results, compositional analysis, bend testing, and biaxial testing of the titanium sheet produced from hydride-dehydride powder will be discussed. Multiple methods of fabrication and the resulting properties can then be assessed to determine the most economical means of making components for industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2017

U-Mo Monolithic Fuel for Nuclear Research and Test Reactors

The metallic fuel selected to replace the current HEU fuels in the research and test reactors is the LEU-10 weight % Mo alloy in the form of a thin sheet or foil encapsulated in AA6061 aluminum alloy with a zirconium interlayer. In order to effectively lead this pursuit, new developments in processing and fabrication of the fuel elements have been initiated, along with a better understanding of material behavior before and after irradiation as a result of these new developments. This editorial note gives an introduction about research and test reactors, need for HEU to LEU conversion, fuel requirements, high uranium density monolithic fuel development and an overview of the four articles published in the December 2017 issue of JOM under a special topic titled “U-Mo Monolithic Fuel for Nuclear Research and Test Reactors”.

LEU fuel development↗
DOE OSTI2019

Therapeutic Potential of DNAzyme Loaded on Chitosan/Cyclodextrin Nanoparticle to Recovery of Chemosensitivity in the MCF-7 Cell Line

Commonly, acquired resistances to anticancer drug are mediated by overexpression of a membrane-associated protein that encode via multi-drug resistance gene-1 (MDR1). Herein, the mRNA-cleaving DNAzyme that targets the mRNA of MDR1 gene in doxorubicin-resistant breast cancer cell line (MCF-7/DR) loaded on the chitosan β-cyclodextrin complexes was used as a tropical agent. Chitosan/β-cyclodextrin complexes were used to deliver DNAzymes into cancer cells. Determination of the physicochemical characteristics of the particles was done by photon correlation spectroscopy and scanning electron microscopy. The encapsulation efficiency of the complexes was tested by using gel retardation assay. Positively charged nanoparticles interacted with DNAzyme that could perform as an efficient DNAzyme transfection system. The rationale usage of this platform is to sensitize MCF-7/DR to doxorubicin by downregulating the drug-resistance gene MDR1. Results demonstrated a downregulation of MDR1 mRNAs in MCF-7/DR/DNZ by real-time PCR, compared to the MCF-7/DR as control. WST1 assay showed the 22-fold decrease in drug resistance on treated cells 24 h after transfection. Results showed the intracellular accumulation of Rh123 increased in the treated cells with DNAzyme. Results suggested a potential platform in association with chemotherapy drug for cancer therapy and indicated extremely efficient at delivery of DNAzyme in restoring chemosensitivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Comparing Empty and Filled Fullerene Cages with High-Resolution Trapped Ion Mobility Spectrometry

We have used trapped ion mobility spectrometry (TIMS) to obtain highly accurate experimental collision cross sections (CCS) for the fullerene C{sub 80}{sup −} and the endohedral metallofullerenes La{sub 2}@C{sub 80}{sup −}, Sc{sub 3}N@C{sub 80}{sup −}, and Er{sub 3}N@C{sub 80}{sup −} in molecular nitrogen. The CCS values of the endohedral fullerenes are 0.2% larger than that of the empty cage. Using a combination of density functional theory and trajectory calculations, we were able to reproduce these experimental findings theoretically. Two effects are discussed that contribute to the CCS differences: (i) a small increase in fullerene cage size upon endohedral doping and (ii) charge transfer from the encapsulated moieties to the cage thus increasing the attractive charge-induced dipole interaction between the (endohedral) fullerene ion and the nitrogen bath gas molecules. .

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. As a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK —a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Predicting path-dependent diffusion barrier spectra in vast compositional space of multi-principal element alloys via convolutional neural networks

The emergent multi-principal element alloys (MPEAs) provide a vast compositional space to search for novel materials for technological advances. How to screen promising compositions from such an ample design space for targeted properties is a grand challenge. In this report, we demonstrate the state-of-the-art deep learning technology—convolutional neural network (CNN)—in predicting path-dependent vacancy migration energy barrier spectra, which are critical to diffusion behavior and many high-temperature properties, in the hyperdimensional composition space of MPEAs. The developed CNN model, fully capturing local chemical features surrounding each vacancy, accurately and efficiently predicts migration energy barrier of MPEAs with different degrees of chemical short-range order and at any unseen compositions. By varying the size of the local region encapsulating vacancy in the CNN model, we reveal that the length scale influencing vacancy migration is surprisingly extensive, up to its six nearest neighboring shells. The efforts of the CNN model make it promising for developing a database of diffusion barriers for various MPEA systems, which would have profound implications for accelerating alloy screening and discovering new compositions with desirable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗
DOE OSTI2012

NSE abundance data

A novel method of calculating nuclear statistical equilibrium (NSE) is presented. Basic equations are carefully solved using arbitrary precision arithmetic. A special interpolation procedure is then used to retrieve all abundances using tabulated results for neutrons and protons, together with basic nuclear data. Proton and neutron abundance tables, basic nuclear data, and partition functions for nuclides used in the calculations are provided. A simple interpolation algorithm using pre-calculated p and n abundances tabulated as functions of kT, {rho} and Y{sub e} is outlined. Unique properties of this method are: (1) ability to pick up out of NSE selected nuclei only, (2) computational time scaling linearly with number of re-calculated abundances, (3) relatively small amount of stored data: only two large tables, (4) slightly faster than solving the NSE equations using traditional Newton-Raphson methods for small networks (few tens of species); superior for huge (800-3000) networks, (5) does not require initial guess; works well on random input, (6) can be tailored to specific application, (7) ability to use third-party NSE solvers to obtain fully compatible tables, and (8) encapsulation of the NSE code for bug-free calculations. A range of applications for this approach is possible: covering tests of traditional NSE Newton-Raphson codes, generating starting values, code-to-code verification, and possible replacement of the old legacy procedures in supernova simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Comprehensive review of 2 β decay half-lives

Here, the double-beta (2 β )-decay is the rarest nuclear physics process, and its experimental half-lives (T 1/2 ) exceed the age of the Universe from nine to fourteen orders of magnitude. Double-beta decay was observed, and its half-life was measured in 14 parent nuclei using direct, radiochemical, and geochemical methods. The decay observables are analyzed using the Evaluated Nuclear Structure Data File (ENSDF) procedures, and the recommended T 1/2 were deduced. Using the calculated values of phase factors, the effective nuclear matrix elements were extracted and compared with available data. Thousands of theoretical and experimental works have been dedicated to these topics in the last 85 years, and we present two data sets of recommended values to encapsulate the results.

2β-decay↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗