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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Degradation of REBCO coated conductors due to a combination of epoxy impregnation, thermal cycles, and quench: Characteristics and a method of alleviation

REBa2Cu3Ox (REBCO) coated conductors are an enabling technology for >1 GHz nuclear magnetic resonance spectrometers that need >23.5 T solenoids, compact high-field fusion reactors beyond the International Thermonuclear Experimental Reactor, and 20 T class accelerator magnets. An in-depth understanding of stress and strain management is critically needed for these applications. Here, we report experimental data and an analysis of damages of REBCO-coated conductors in several scenarios relevant for their applications in high-field magnets and unique to their multi-layer thin film structure. The examined scenarios include failure induced by quench, failure induced by epoxy impregnation, and failure induced by a combination of epoxy impregnation and quench. The root cause is film blistering and peeling induced by thermally interfacial stresses characteristic of multilayered heteroepitaxial thin film structures on thick substrates utilized. The quantitative stress analysis is introduced using simple and easy to use formulas and clearly indicates how materials and structural characteristics affect the magnitude and the distribution of stresses and deflections. Finally, a simple method is introduced for removing degradation of REBCO coated conductors due to epoxy impregnation. Our data and analysis help our understanding of the practical limit of REBCO-coated conductors and can be utilized as a guidance for the physical design of REBCO coated conductors and high-current cables assembled from them and for minimizing damages.

Yin, Shijian (ORCID:0000000224312274)↗
DOE OSTI2023

Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts

Abstract Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO 2 (111) catalysts, and quantify uncertainty using Bayesian Inference. We discuss extensions for characterizing complex materials towards closing the materials gap.

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

Integrating geophysical monitoring data into multiphase fluid flow reservoir simulation

Simulation of multiphase flow systems are of critical importance in managing hydrological systems. Flow simulations are affected by a number of factors including structure and flow properties including porosity and permeability as well as the anisotropy and heterogeneity of these properties. In many cases traditional hydrological and reservoir data are highly affected by these parameters, but are not directly sensitive to them. As such modellers often adjust these parameters in an ad hoc manner until solutions numerically converge. Simulation models are generally based on structural data from reflection seismics whose physical flow properties are then populated using geostatistical extrapolation techniques utilizing a sparse number of borehole logs and core analysis. In multiphase systems including enhanced oil recovery and carbon capture and sequestration uncertainties regarding phase-dependent physical properties confounds this challenge further. Geophysical methods provide a means by which to gain an improved understanding of phase distributions in the subsurface. In this paper we will look at applications from active carbon capture and sequestration and enhanced oil recovery applications, as well as synthetic examples. Geophysical data including electromagnetic and gravity are inverted using structural constraints from the reservoir model. Inversions are then mapped into flow properties using calibrated relations such as Archie’s Equation. The coupled models can then be used to both verify and improve on the reservoir flow model which improves it’s predictive power and utility as a management tool.

02 PETROLEUM↗
DOE OSTI2016

Pair distribution function analysis: The role of structural degrees of freedom in the high-pressure insulator to metal transition of VO 2

The evolution of the local structure of VO 2 was investigated across the pressure-induced insulator to metal transition (IMT) by means of pair distribution function measurements. The pressure behavior of the V-V and V-O bond lengths have been determined. The data demonstrated that the pressure-driven IMT is not activated by the suppression of the Peierls-type distortion. A clear octahedra symmetrization is observed in the metallic phase, suggesting a link between structural degree of freedom and the metallization process.

36 MATERIALS SCIENCE↗
DOE OSTI2022

BASIN-3D: A brokering framework to integrate diverse environmental data

Diverse observational and simulation datasets are needed to understand and predict complex ecosystem behavior over seasonal to decadal and century time-scales. Integration of these datasets poses a major barrier towards advancing environmental science, particularly due to differences in the structure and formats of data provided by various sources. Here, we describe BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets), a data integration framework designed to dynamically retrieve and transform heterogeneous data from different sources into a common format to provide an integrated view. BASIN-3D enables users to adopt a standardized approach for data retrieval and avoid customizations for the data type or source. We demonstrate the value of BASIN-3D with two use cases that require integration of data from regional to watershed spatial scales. The first application uses the BASIN-3D Python library to integrate time-series hydrological and meteorological data to provide standardized inputs to analytical and machine learning codes in order to predict the impacts of hydrological disturbances on large river corridors of the United States. The second application uses the BASIN-3D Django framework to integrate diverse time-series data in a mountainous watershed in East River, Colorado, United States to enable scientific researchers to explore and download data through an interactive web portal. Thus, BASIN-3D can be used to support data integration for both web-based tools, as well as data analytics using Python scripting and extensions like Jupyter notebooks. The framework is expected to be transferable to and useful for many other field and modeling studies.

Varadharajan, C↗
DOE OSTI2016

Er{sub 1.33}Pt{sub 3}Ga{sub 8}: A modulated variant of the Er{sub 4}Pt{sub 9}Al{sub 24}-structure type

Single crystals of Er{sub 1.33}Pt{sub 3}Ga{sub 8} were synthesized in a molten Ga flux. Er{sub 1.33}Pt{sub 3}Ga{sub 8} can be considered to be a modulated variant of the Er{sub 4}Pt{sub 9}Al{sub 24}-structure type, where the partial occupancies are ordered. Indeed, the presence of weak satellite reflections indicates a complex organization and distribution of the Er and Ga atoms within the [ErGa] slabs. The structure has been solved based on single crystal X-ray diffraction data in the monoclinic superspace group X2/m(0β0)00 with a commensurate modulated vector q=1/3b*. Precession images also indicate diffusion in the perpendicular direction indicating a partial disorder of this arrangement from layer to layer. In addition, Er{sub 1.33}Pt{sub 3}Ga{sub 8} shows antiferromagnetic ordering at T{sub N}~5 K. - Graphical abstract: A precession image of the hk0 zone showing weak, periodic, unindexed reflections indicating modulation and representation of the commensurate [ErGa] layer showing the waving modulated occupation. - Highlights: • Single crystals of Er{sub 1.33}Pt{sub 3}Ga{sub 8} were grown from gallium flux. • The structure of Er{sub 1.33}Pt{sub 3}Ga{sub 8} is compared to Er{sub 4}Pt{sub 9}Al{sub 24}. • Structure has been solved in the monoclinic superspace group X2/m(0β0)00 with a commensurate modulated vector q=1/3b*.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Structural evolution and atomic dynamics in Ni–Nb metallic glasses: A molecular dynamics study

In this work, the composition and temperature dependence of static and dynamic structures in Ni x Nb 1– x ( x = 50–70 at. %) were systematically studied using molecular dynamics with a new-released semi-empirical embedded atom method potential by Mendelev. The calculated pair correlation functions and the structure factor match well with the experimental data, demonstrating the reliability of the potential within relatively wide composition and temperature ranges. The local atomic structures were then characterized by bond angle distributions and Voronoi tessellation methods, demonstrating that the icosahedral $\langle$0,0,12,0$\rangle$ is only a small fraction in the liquid state but increases significantly during cooling and becomes dominant at 300 K. The most abundant clusters are identified as $\langle$0,0,12,0$\rangle$ and distorted icosahedron$\langle$0,2,8,2$\rangle$. The large fraction of these two clusters hints that the relatively good glass forming ability is near the eutectic point. Unlike Cu–Zr alloys, both the self-diffusion coefficient and shear viscosity are insensitive to compositions upon cooling in Ni–Nb alloys. The breakdown of the Stokes-Einstein relation happens at around 1.6 T g ( T g : glass transition temperature). In the amorphous state, the solid and liquid-like atoms can be distinguished based on the Debye-Waller factor $\langle$ u 2 $\rangle$. The insensitivity of the dynamic properties of Ni–Nb alloys to compositions may result from the relatively simple solidification process in the phase diagram, in which only one eutectic point exists in the studied composition range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Microstructural Analysis and Transport Resistances of Low-Platinum-Loaded PEFC Electrodes

In this study, we present microstructural characterization for polymer electrolyte fuel cell (PEFC) cathodes with low platinum loadings (low-PGM). The characterization results are used to quantify the contribution of mass transport resistances to cell voltage losses observed in polarization curve data. Three-dimensional pore morphology and ionomer distribution are resolved using nano-scale X-ray computed tomography (nano-CT). Electrode structural properties are reported along with analysis of the impact of microstructure on the effective charge and reactant transport properties. These characterizations are incorporated with a two-dimensional multi-physics model that accounts for energy, charge, and mass transport along with the effect of liquid water flooding. Defining a total mass transport resistance for the whole polarization curve, contributions of transport mechanisms are identified. Analysis of the experimental polarization curves at different operating pressures and temperatures indicates that the mass transport resistance in the cathode is dominated by the transport processes in the electrode. It is shown that flooding in the electrode is a major contributor to transport losses especially at elevated operating pressures while the pressure-independent resistance at the catalyst surface due to transport through the ionomer film plays a significant role, especially at low temperatures and low catalyst loading. In addition, by performing a parametric study for varying catalyst loadings, the importance of electrode roughness (i.e, electrochemically-active surface area/geometric electrode area) in determining the mass transport losses is highlighted.

25 ENERGY STORAGE↗
DOE OSTI2019

Quantitative Uncertainty Analysis for Diffraction

Current software uses a least squares statistical method. For each model parameter, current software yields a point estimate and estimated standard error for each point estimate. In contrast, we have employed a Bayesian approach with sampling algorithm to provide a full posterior probability density function on each model parameter. This yields a different type of solution (probabilistic) with better fidelity. The Quantitative Uncertainty Analysis for Diffraction (QUAD) package returns a matrix of affect model parameters as a function of iteration through the MCMC analysis. QUAD is a Python code that allows for analysis of X-ray and neutron diffraction data to infer the structure of materials with quantifiable certainty. The code uses Bayesian statistics and Markov chain sampling algorithms to create posterior probability distributions on all material structure parameters that are modeled by a researcher. The statistical packages use the open source GSASII project as a library to calculate model diffraction patterns.

Fancher, ChristopherM↗
DOE OSTI2026

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Pion and kaon structure functions at an electron-ion collider

Pions and kaons are, along with protons and neutrons, the main building blocks of nuclear matter. They are connected to the Goldstone modes of dynamical chiral symmetry breaking, the mechanism thought to generate all hadron mass in the visible universe. The distribution of the fundamental constituents, the quarks and gluons, is expected to be different in pions, kaons, and nucleons. However, experimental data are sparse. As a result, there has been persistent doubt about the behaviour of the pion's valence quark structure function at large Bjorken-$x$ and virtually nothing is known about the contribution of gluons. The Electron-Ion Collider (EIC) with an acceptance optimized for forward physics could provide access to structure functions over a larger kinematic region. This would allow for measurements testing if the origin of mass is encoded in the differences of gluons in pions, kaons, and nucleons, and measurements that could serve as a test of assumptions used in the extraction of structure functions and the pion and kaon form factors. Furthermore, measurements at an EIC would also allow to explore the effect of gluons at high x.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Radiochemistry and the Study of Fission

These are slides from a lecture given at UC Berkeley. Radiochemistry has been used to study fission since its discovery. Radiochemical methods are used to determine cumulative mass yields. These measurements have led to the two-mode fission hypothesis to model the neutron energy dependence of fission product yields. Fission product yields can be used for the nuclear forensics of nuclear explosions. The mass yield curve depends on both the fuel and the neutron spectrum of a device. Recent studies have shown that the nuclear structure of the compound nucleus can affect the mass yield distribution. The following topics are covered: In the beginning: the discovery of fission; forensics using fission products: what can be learned from fission products, definitions of R-values and Q-values, fission bases, K-factors and fission chambers, limitations; the neutron energy dependence of the mass yield distribution (the two mode fission hypothesis); the influence of nuclear structure on the mass yield distribution. In summary: Radiochemistry has been used to study fission since its discovery. Radiochemical measurement of fission product yields have provided the highest precision data for developing fission models and for nuclear forensics. The two-mode fission hypothesis provides a description of the neutron energy dependence of the mass yield curve. However, data is still rather sparse and more work is needed near second and third chance fission. Radiochemical measurements have provided evidence for the importance of nuclear states in the compound nucleus in predicting the mass yield curve in the resonance region.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

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

Concentration-dependent and configuration-dependent interactions of monovalent ions with an RNA tetraloop

Monovalent salt solutions have strongly coupled interactions with biopolymers, from large polyelectrolytes to small RNA oligomers. High salt concentrations have been known to induce transitions in the structure of RNA, producing non-canonical configurations and even driving RNA to precipitate out of solution. Using all-atom molecular dynamics simulations, we model a monovalent salt species (KCL) at high concentrations (0.1–3m) and calculate the equilibrium distributions of water and ions around a small tetraloop-forming RNA oligomer in a variety of structural arrangements: folded A-RNA (canonical) and Z-RNA (non-canonical) tetraloops and unfolded configurations. From these data, we calculate the ion preferential binding coefficients and Donnan coefficients for the RNA oligomer as a function of concentration and structure. We find that cation accumulation is highest around non-canonical Z-RNA configurations at concentrations below 0.5m, while unfolded configurations accumulate the most co-ions in all concentrations. By contrast, canonical A-RNA structures consistently show the lowest accumulations for all ion species. Water distributions vary markedly with RNA configuration but show little dependency on KCL concentration. Based on Donnan coefficient calculations, the net charge of the solution at the surface of the RNA decreases linearly as a function of salt concentration and becomes net-neutral near 2.5–3m KCL for folded configurations, while unfolded configurations still show a positive solution charge. Our findings show that all-atom molecular dynamics can describe the equilibrium distributions of monovalent salt in the presence of small RNA oligomers at KCL concentrations where ion correlation effects become important. Furthermore, these results provide valuable insights into the distributions of water and ions near the RNA oligomer surface as a function of structural configuration.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Power distribution and BER in indoor VLC with PPM based modulation schemes: a comparative study

Visible light communication (VLC) uses an intensity-modulation and direct-detection scheme to transmit data. The light source utilized in VLC structures is constantly switched on and off rapidly, resulting in flickering. Furthermore, most of illumination systems exclude dimming support to permit customers to dim the light source to the desired stage. Therefore, the modulation scheme for information transmission in VLC should consist of flicker mitigation and dimming manage abilities. Double inverse pulse position modulation (DIPPM), sub-carrier pulse position modulation (SC-L-PPM), and M-ary variable pulse position modulation (M-VPPM) are recommended for minimizing the flicker issues and supporting an excessive degree of dimming for VLC systems. In this paper, a comparison is introduced between DIPPM, SC-L-PPM, and M-VPPM according to error performance and bit rate. In addition, a simulation is carried out to measure the optical power distribution for a LED lamp in an indoor room topology for each modulation technique. The obtained results indicated that SC-L-PPM is the best choice regarding the bit error rate (BER) and optical power distribution compared to the other two schemes. A 10{sup −6} BER is achieved with a very low power requirement at L = 8, while a remarkable power distribution of 1.5–6.5 dBm is observed from 3 × 5 × 5 m{sup 3} room corners to the center, respectively. According to the bit rate, it is noticed that, M-VPPM is the most efficient one compared to the two other schemes. It achieves 2.3 × 10{sup 7} bps at a signal to noise ratio (SNR) of 22 dB and M = 8.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Stars in the local galactic thick disc and halo in Gaia EDR3: a catalogue of half a million local main-sequence stars with photometric metallicities

We present a catalogue of 551 214 main-sequence stars in the local (d < 2 kpc) Galactic thick disc and halo, based on a search of stars with large proper motions ($\mu _{\rm tot} \gt 40.0~\rm mas\, yr^{-1}$) in the Gaia Early Data Release 3. We derive photometric metallicity calibrated from the colour–luminosity–metallicity distribution of 20 047 stars with spectroscopic metallicities, collected from various spectroscopic surveys, including SDSS SEGUE/APOGEE, GALAH DR3, and LAMOST DR6. We combine these results to construct an empirical colour–magnitude–metallicity grid, which can be used to estimate photometric metallicities for low-mass metal-poor stars of K and M subtypes from their absolute G magnitude and colour values. We find that low-mass, high-velocity stars in our catalogue share similar kinematics as reported in recent studies of more luminous Galactic halo stars. The pseudo-kinematic analysis of our sample recovers the main local halo structures, including the Gaia–Enceladus Stream and the Helmi stream; aside from these, the local halo stars appear to show a remarkably smooth distribution in velocity space. Since the future Gaia data release will provide radial velocity measurements for only a small number of our sample, our catalogue provides targets of high interest for the future spectroscopic observation programs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Next-to-next-to-leading power corrections to unpolarized Semi-Inclusive Deep Inelastic Scattering

Semi-Inclusive Deep Inelastic Scattering (SIDIS) is a key tool for exploring the three-dimensional structure of the nucleon through Transverse Momentum Dependent parton distributions and fragmentation functions. While leading-power contributions to the SIDIS cross-section are well established, next-to-leading power (NLP) corrections of order 1/Q and next-to-next-to-leading power (NNLP) corrections of order 1/Q 2 to the hadronic tensor have only recently begun to be systematically investigated. These corrections are essential for reliable phenomenology and interpretation of modern high-precision data. In recent papers by one of the authors, NNLP corrections to the Drell-Yan process were derived using the rapidity factorization formalism. In the present work, we extend this approach to SIDIS and obtain analytic expressions for the unpolarized structure functions. We derive NNLP corrections that include convolutions of unpolarized distributions, f 1 , with unpolarized fragmentation functions, D 1 , and Boer-Mulders functions, ${h}_1^{\perp }$, with Collins fragmentation functions, ${H}_1^{\perp }$. We compare our results with previous formulations, provide numerical studies, confront our predictions with HERMES and COMPASS measurements, and present predictions for future experiments at Jefferson Lab and the Electron-Ion Collider.

deep inelastic scattering↗