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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data for: Subsurface Interface Structure Controlling Local Electronic Properties of Epitaxial Graphene on SiC(0001)

Recently realized high-mobility semiconducting epitaxial graphene on silicon carbide, provided an important step towards integration of the graphene-based system into active components in post-silicon micro- and nano-electronics. However, the exact atomic-scale structure and the complex bonding configurations of the first epitaxial graphene carbon layer remain an open problem. Our recent report has shed new light on understanding this interface, where the external transverse electric field-dependent dynamic switching behavior of the Cbuffer-SiC bonds was observed. Here, using scanning tunneling microscopy and spectroscopy (STM and STS), we present the direct evidence of silicon (Si) vacancies at the interface and provide their distribution at the topmost reconstructed SiC(0001) layer. Experimental STM and density functional theory modeling data were used in the preparation of figures in a published article in the Journal of Physical Chemistry Letters. Files related to the figures and supplementary materials in the article are present in this dataset in .txt format.

Condensed matter imaging↗
DOE OSTI2022

In-beam γ-ray spectroscopy of 32 Mg via direct reactions

Background: The nucleus 32 Mg (N=20 and Z=12) plays a central role in the so-called “island of inversion,” where in the ground states sd-shell neutrons are promoted to the fp-shell orbitals across the shell gap, resulting in the disappearance of the canonical neutron magic number N=20. Purpose: The primary goals of this work are to extend the level scheme of 32Mg, provide spin-parity assignments to excited states, and discuss the microscopic structure of each state through comparisons with theoretical calculations. Method: In-beam γ-ray spectroscopy of 32 Mg was performed using two direct-reaction probes: one-neutron (two-proton) knockout reactions on 33 Mg ( 34 Si). Final-state exclusive cross sections and parallel momentum distributions were extracted from the experimental data and compared with eikonal-based reaction model calculations combined with shell-model overlap functions. Results: Owing to the remarkable selectivity of the one-neutron and two-proton knockout reactions, a significantly updated level scheme for 32 Mg, which exhibits negative-parity intruder and positive-parity normal states, was constructed. The experimental results were confronted with four different nuclear structure models. Conclusions: In some of these models, different aspects of 32 Mg and the transition into the island of inversion are well described. However, unexplained discrepancies remain, and, even with the help of these state-of-the-art theoretical approaches, the structure of this key nucleus is not yet fully captured.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Hardware-Software Complex for Measurement of Energy and Angular Distributions of Charged Particles Formed in Nuclear Reactions

A hardware-software complex for measurement of energy and angular distributions of charged particles formed in nuclear reactions is presented. Hardware and software structures of the complex, the basic set of the modular nuclear-physical apparatus of a multichannel detecting system on the basis of ΔE–E telescopes of silicon detectors, and the hardware of experimental data collection, storage, and processing are presented and described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Quantitative Analysis of the Morphology of {101} and {001} Faceted Anatase TiO 2 Nanocrystals and Its Implication on Photocatalytic Activity

The atomistic structure and morphology (shape and size) of nanomaterials have strong influences on their physical and chemical properties. However, many characterization techniques focus exclusively on one length-scale regime or another when developing quantitative morphology/structural models. In this article, we demonstrate that powder X-ray diffraction and neutron pair distribution function (PDF) can be used to obtain accurate average morphology and atomistic structure of {001} and {101} faceted anatase TiO 2 nanocrystals based on differential evolution refinements using Debye scattering equation calculations. It is also demonstrated that the morphology polydispersity of TiO 2 nanocrystals can be effectively obtained from the diffraction data via a numerical refinement routine. The morphology refinement results are in good agreement with those from transmission electron microscopy and the modeling of small angle neutron scattering data. This method is successfully used to quantify the facet-specified photocatalytic hydrogen evolution activity of anatase TiO 2 nanocrystals with different {001} to {101} ratios. It is found that the sample with an intermediate amount of both {001} and {101} facets shows the best photocatalytic hydrogen evolution reaction (HER) activity. It is expected that the simultaneous structure and morphology refinement technique can be generally used to study the relationship between morphology and functionality of nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Discovering Physically Meaningful Structures from Climate Extreme Data

The original proposal described an interdisciplinary team spanning UC San Diego (lead), Columbia University, and UC Irvine, with Columbia investigators including Pierre Gentine, Elias Bareinboim, and Marcus van Lier-Walqui. The proposal further specified a leadership structure in which Columbia co-investigators contributed across the three aims, with Co-PI Gentine serving as a point of contact with science teams and with responsibilities distributed across aims.

42 ENGINEERING↗
DOE OSTI2023

Progressive Tree-Based Compression of Large-Scale Particle Data

Scientific simulations and observations using particles have been creating large datasets that require effective and efficient data reduction to store, transfer, and analyze. However, current approaches either compress only small data well while being inefficient for large data, or handle large data but with insufficient compression. Toward effective and scalable compression/decompression of particle positions, we introduce new kinds of particle hierarchies and corresponding traversal orders that quickly reduce reconstruction error while being fast and low in memory footprint. Our solution to compression of large-scale particle data is a flexible block-based hierarchy that supports progressive, random-access, and error-driven decoding, where error estimation heuristics can be supplied by the user. For low-level node encoding, we introduce new schemes that effectively compress both uniform and densely structured particle distributions. Our proposed methods thus target all three phases of a tree-based particle compression pipeline, namely tree construction, tree traversal, and node encoding. In conclusion, the improved efficacy and flexibility of these methods over existing compressors are demonstrated through extensive experimentation, using a wide range of scientific particle datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Physics-informed graphical neural network for power system state estimation

State estimation is highly critical for accurately observing the dynamic behavior of the power grids and minimizing risks from cyber threats. However, existing state estimation methods encounter challenges in accurately capturing power system dynamics, primarily because of limitations in encoding the grid topology and sparse measurements. Here, this paper proposes a physics-informed graphical learning state estimation method to address these limitations by leveraging both domain physical knowledge and a graph neural network (GNN). We employ a GNN architecture that can handle the graph-structured data of power systems more effectively than traditional data-driven methods. The physics-based knowledge is constructed from the branch current formulation, making the approach adaptable to both transmission and distribution systems. The validation results of three IEEE test systems show that the proposed method can achieve lower mean square error more than 20% than the conventional methods.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Selenium tolerance, accumulation, localization and speciation in a Cardamine hyperaccumulator and a non-hyperaccumulator

Cardamine violifolia (family Brassicaceae ) is the first discovered selenium hyperaccumulator from the genus Cardamine with unique properties in terms of selenium accumulation, i.e., high abundance of selenolanthionine. In our study, a fully comprehensive experiment was conducted with the comparison of a non-hyperaccumulator Cardamine species, Cardamine pratensis , covering growth characteristics, chlorophyll fluorescence, spatial selenium/sulfur distribution patterns through elemental analyses (synchrotron-based X-Ray Fluorescence and ICP-OES) and speciation data through selenium K-edge micro X-ray absorption near-edge structure analysis (μXANES) and strong cation exchange (SCX)-ICP-MS. The results revealed remarkable differences in contrast to other selenium hyperaccumulators as neither Cardamine pecies showed evidence of growth stimulation by selenium. Also, selenite uptake was not inhibited by phosphate for either of the Cardamine species. Sulfate inhibited selenate uptake, but the two Cardamine species did not show any difference in this respect. However, μXRF derived speciation maps and selenium/sulfur uptake characteristics provided results that are similar to other formerly reported hyperaccumulator and non-hyperaccumulator Brassicaceae species. μXANES showed organic selenium, “C-Se-C”, in seedlings of both species and also in mature C. violifolia plants. In contrast, selenate-supplied mature C. pratensis contained approximately half “C-Se-C” and half selenate. SCX-ICP-MS data showed evidence of the lack of selenocystine in any of the Cardamine plant extracts. Thus, C. violifolia shows clear selenium-related physiological and biochemical differences compared to C. pratensis and other selenium hyperaccumulators.

Environmental Sciences & Ecology↗
DOE OSTI2017

High-energy X-ray applications: current status and new opportunities

Characterization of semi and noncrystalline materials, monitoring structural phase transitions in situ , and obtaining structural information together with spatial distribution of the investigated material are only a few applications that hugely benefitted from the combination of high-energy X-rays and modern algorithms for data processing. This work examines the possibility of advancing these applications by shortening the data acquisition and improving the data quality by using the new high-energy PILATUS3 CdTe detector.

Šišak Jung, Dubravka (ORCID:000000018702183X)↗
DOE OSTI2023

Impedance-Based Detection of NO 2 Using Ni-MOF-74: Influence of Competitive Gas Adsorption

Chemically robust, low-power sensors are needed for the direct electrical detection of toxic gases. Metal–organic frameworks (MOFs) offer exceptional chemical and structural tunability to meet this challenge, though further understanding is needed regarding how coadsorbed gases influence or interfere with the electrical response. To probe the influence of competitive gases on trace NO 2 detection in a simulated flue gas stream, a combined structure–property study integrating synchrotron powder diffraction and pair distribution function analyses was undertaken, to elucidate how structural changes associated with gas binding inside Ni-MOF-74 pores correlate with the electrical response from Ni-MOF-74-based sensors. Data were evaluated for 16 gas combinations of N 2 , NO 2 , SO 2 , CO 2 , and H 2 O at 50 °C. Fourier difference maps from a rigid-body Rietveld analysis showed that additional electron density localized around the Ni-MOF-74 lattice correlated with large decreases in Ni-MOF-74 film resistance of up to a factor of 6 × 10 3 , observed only when NO 2 was present. These changes in resistance were significantly amplified by the presence of competing gases, except for CO 2 . Without NO 2 , H 2 O rapidly (<120 s) produced small (1–3×) decreases in resistance, though this effect could be differentiated from the slower adsorption of NO 2 by the evaluation of the MOF’s capacitance. Furthermore, samples exposed to H 2 O displayed a significant shift in lattice parameters toward a larger lattice and more diffuse charge density in the MOF pore. Evaluating the Ni-MOF-74 impedance in real time, NO 2 adsorption was associated with two electrically distinct processes, the faster of which was inhibited by competitive adsorption of CO 2 . Together, this work points to the unique interaction of NO 2 and other specific gases (e.g., H 2 O, SO 2 ) with the MOF’s surface, leading to orders of magnitude decrease in MOF resistance and enhanced NO2 detection. Finally, understanding and leveraging these coadsorbed gases will further improve the gas detection properties of MOF materials.

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

KiDS-1000 cosmology: Combined second- and third-order shear statistics

Aims.In this work, we perform the first cosmological parameter analysis of the fourth release of Kilo Degree Survey (KiDS-1000) data with second- and third-order shear statistics. This paper builds on a series of studies aimed at describing the roadmap to third-order shear statistics. Methods.We derived and tested a combined model of the second-order shear statistic, namely, the COSEBIs and the third-order aperture mass statistics 〈ℳ ap 3 〉 in a tomographic set-up. We validated our pipeline withN-body mock simulations of the KiDS-1000 data release. To model the second- and third-order statistics, we used the latest version of HMCODE2020 for the power spectrum and BIHALOFITfor the bispectrum. Furthermore, we used an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering only equal smoothing radii for the 〈ℳ ap 3 〉 part of the data vector. This makes it possible to carry out a data analysis of the KiDS-1000 data release using a combined analysis of COSEBIs and third-order shear statistics. Results.We first validated the accuracy of our modelling by analysing a noise-free mock data vector, assuming the KiDS-1000 error budget, finding a shift in the maximum of the posterior distribution of the matter density parameter, ΔΩ m < 0.02 σ Ω m , and of the structure growth parameter, ΔS 8 < 0.05 σ S 8 . Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained Ω m = 0.248 −0.055 +0.062 andS 8 = σ 8 √(Ω m /0.3 )= 0.772 ± 0.022. The geometric average on the errors of Ω m andS 8 of the combined statistics decreases, compared to the second-order statistic, by a factor of 2.2.

Astronomy & Astrophysics↗
DOE OSTI2020

Self-radiography of imploded shells on OMEGA based on additive-free multi-monochromatic continuum spectral analysis

Radiographs of pure-DT cryogenic imploding shells provide critical validation of progress toward ignition-scalable performance of inertial confinement fusion implosions. Cryogenic implosions on the OMEGA Laser System can be self-radiographed by their own core spectral emission near ≈2 keV. Utilizing the distinct spectral dependences of continuum emissivity and opacity, the projected optical-thickness distribution of imploded shells, i.e., the shell radiograph, can be distinguished from the structure of the core emission distribution in images.Importantly, this can be done without relying on spectral additives (shell dopants), as in previous applications of implosion self-radiography. Furthermore, demonstrations with simulated data show that this technique is remarkably well-suited to cryogenic implosions and can also be applied to self-radiography of imploded room-temperature CH shells at higher spectral energy (hv ≈ 3–5 keV) based on the very similar continuum spectrum of carbon. Experimental demonstration of additive-free self-radiography with warm CH shell implosions on OMEGA will provide an important proof of principle for future applications to cryogenic DT implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Deconstruction of the Ras switching cycle through saturation mutagenesis

Ras proteins are highly conserved signaling molecules that exhibit regulated, nucleotide-dependent switching between active and inactive states. The high conservation of Ras requires mechanistic explanation, especially given the general mutational tolerance of proteins. Here, we use deep mutational scanning, biochemical analysis and molecular simulations to understand constraints on Ras sequence. Ras exhibits global sensitivity to mutation when regulated by a GTPase activating protein and a nucleotide exchange factor. Removing the regulators shifts the distribution of mutational effects to be largely neutral, and reveals hotspots of activating mutations in residues that restrain Ras dynamics and promote the inactive state. Evolutionary analysis, combined with structural and mutational data, argue that Ras has co-evolved with its regulators in the vertebrate lineage. Overall, our results show that sequence conservation in Ras depends strongly on the biochemical network in which it operates, providing a framework for understanding the origin of global selection pressures on proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Nucleon Tomography Studies at Jefferson Lab

Protons and neutrons, are the building blocks of atomic nuclei. They constitute over 99 percent of the mass of the matter in the visible universe. A fundamental challenge of modern nuclear physics is to understand the structure of these constituents. The 12 GeV Upgrade of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab and the construction of state-of-the-art detector systems make it a unique facility in the world to address this challenge. Electron scattering is a superb experimental tool to study the internal structure of nucleons at differing distance scales, as the resolving power of the probe can be varied. The CEBAF Upgrade was completed in September 2017 and the new generation of experiments has started. These experiments will enable a collaboration of scientists from around the world to perform precise experiments of exclusive processes covering a large range in kinematics to effectively engage in nuclear imaging, revealing hidden aspects of its internal structure, and providing insight into quark confinement forces in the nucleon, one of the greatest mysteries of modern physics. The Generalized Parton Distributions (GPDs) provide the theoretical framework to interpret the experimental data in terms of 3-dimensional imaging. In addition, recent development demonstrated that the GPD formalism enables access to the nucleon's Gravitational Form Factors that encode its mechanical properties. We will focus on the study of the Deeply Virtual Compton Scattering (DVCS), the most effective way to access GPDs. We will review the landscape of both theory and experiment, and discuss the latest results from Jefferson Lab at 6 GeV in comparison with results from other facilities, and present a first look at the new experiments with the 12 GeV Upgrade.

Elouadrhiri, Latifa↗
DOE OSTI2017

Local Chemical Ordering and Negative Thermal Expansion in PtNi Alloy Nanoparticles

An atomic insight into the local chemical ordering and lattice strain is particular interesting to recent emerging bimetallic nanocatalysts such as PtNi alloys. Here in this paper, we reported the atomic distribution, chemical environment and lattice thermal evolution in full-scale structural description of PtNi alloy nanoparticles (NPs). The different segregation of elements in the well-faceted PtNi nanoparticles is convinced by extended X-ray absorption fine structure (EXAFS). Atomic pair distribution function (PDF) study evidences the co-existence of the face-centered cubic and tetragonal ordering parts in the local environment of PtNi nanoparticles. Further reverse monte carlo (RMC) simulation with PDF data obviously exposed the segregation as Ni and Pt in the centers of {111} and {001} facets respectively. Layer-by-layer statistical analysis up to 6 nm for the local atomic pairs revealed the distribution of local tetragonal ordering on the surface. This local coordination environment facilitates the distribution of heteroatomic Pt-Ni pairs, which plays an important role in the negative thermal expansion of Pt 41 Ni 59 NPs. The present study on PtNi alloy NPs from local short-range coordination to long-range average lattice provides a new perspective on tailoring physical properties in nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Partnership for Edge Physics Simulation

A major goal of our participation in the Edge Physics Simulation project has been to contribute to the understanding of the self-organization of tokamak turbulence fluctuations resulting in the formation of a staircase structure in the ion temperature. A second important goal is to demonstrate how small scale turbulence in plasmas self-organizes with dynamically driven quasi-stationary flow shear. These goals have been accomplished through the analyses of the statistical properties of XGC1 flux driven Gyrokinetic electrostatic ion temperature gradient (ITG) turbulence simulation data in which neutrals are included. The ITG turbulence data, and in particular fluctuation data, were obtained from a massively parallel flux-driven gyrokinetic full-f particle-in-cell simulation of a DIII-D like equilibrium. Below some the findings are summarized. It was observed that the emergence of staircase structure is related to the variations in the normalized temperature gradient length (R/LT) and the poloidal flow shear. Average turbulence intensity is found to be large in the vicinity of minima in R/LTi, where ITG growth is expected to be lower. The distributions of the occurrences of potential fluctuation are found to be Gaussian away from the staircase-step locations, but they are found to be non-Gaussian in the vicinity of staircase-step locations. The results of analytically derived expressions for the distribution of the occurrences of turbulence intensity and intensity flux were compared with the corresponding quantities computed using XGC1 simulation data and good agreement is found. The derived expressions predicts inward and outward propagation of turbulence intensity flux in an intermittent fashion. The outward propagation of turbulence intensity flux occurs at staircase-step locations and is related to the change in poloidal flow velocity shear and to the change in the ion temperature gradient. The standard deviation, skewness and kurtosis for turbulence quantities were computed and found to be large in the vicinity of the staircase-step structures. Large values of skewness and kurtosis can be explained by a temporary opening and closing of the structure which allows turbulence intensity events to propagate. The staircase patterns may reduce the ion heat transport and a manipulation of these patterns may be used to optimize heat transport in tokamaks. An additional objective of the research in support of the Edge Physics Simulation initiative has been to improve the understanding of scrape-off layer thermal transport. In planning experiments and designing future tokamaks, it is important to understand the physical effects that contribute to divertor heat-load fluxes. The research accomplished will contribute to developing new models for the scrape-off layer region. The XGC0 code was used to compute the heat fluxes and the heat-load width in the outer divertor plates of C-Mod and DIII-D tokamaks. It was observed that the width of the XGC0 neoclassical heat-load was approximately inversely proportional to the total plasma current. Anomalous transport in the H-mode pedestal region of five Alcator C-Mod discharges, representing a collisionality scan, was analyzed. The understanding of anomalous transport in the pedestal region is important for the development of a comprehensive model for the H-mode pedestal slope. It was found that the electron thermal anomalous diffusivities at the pedestal top increase with the electron collisionality. This dependence can point to the DRIBM as the modes that drive the anomalous transport in the plasma edge of highly collisional discharges. The effects of plasma shaping on the H-mode pedestal structure was also investigated. The differences in the predicted H-mode pedestal width and height for the DIII-D discharges with different elongation and triangularities were discussed. For the discharges with higher elongation, it was found that the gradients of the plasma profiles in the H-mode pedestal reach semi-steady states. In these simulations, the pedestal slowly continued to evolve to higher pedestal pressures and bootstrap currents until the peeling ballooning stability conditions were satisfied. The discharges with lower elongation do not reach the semi-steady state, and ELM crashes were triggered at earlier times. The plasma elongation was found to have a stronger stabilizing effect than the plasma triangularity. For the discharges with lower elongation and lower triangularity, the ELM frequency was large, and the H-mode pedestal evolves rapidly. It was found that the temperature of neutrals in the scrape-off-layer region can affect the dynamics of the H-mode pedestal buildup. However, the final pedestal profiles were nearly independent of the neutral temperature. The elongation and triangularity affected the pedestal widths of plasma density and electron temperature profiles differently. This study illustrated a new mechanism for controlling the pedestal bootstrap current and the pedestal stability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Identifying structural changes with unsupervised machine learning methods

In this work, unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems.

42 ENGINEERING↗