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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Energy-Dispersive X-ray Spectroscopy and Atom-probe Tomography Data Quantifying Component-Ratios of Multicomponent Nano-Precipitates in Ion-Irradiated Ceria

Samples of ~1 µm films of CeO2 doped with 2 wt% Mo, 1.5 wt% Ru, 0.75 wt% Pd, 0.5 wt% Re and 0.25 wt% Rh grown with pulsed laser deposition were irradiated with I2+ ions (610°C and 730°C, 1016 and 5×1016 I2+/cm2). For selected samples post-irradiation heat treatment was conducted (900°C, 1100°C). The specimens were sectioned with focussed ion beam milling and characterized in a transmission electron microscope with energy dispesive x-ray spectroscopy, and with atom-probe tomography. Energy dispersive x-ray spectroscopy was used to obtain elemental maps showing the distribution of dopants in the specimen after exposure. Some of these maps are discussed in detail in our companion article “Formation of multicomponent alloy particles in doped ceria under I2+ ion irradiation and thermal annealing” in the Journal of Nuclear Materials [REF]. Advanced computational analysis could be used to more accurately quantify local compositions. Data is provided for additional regions of interest and one additional irradiation condition. The doped Ceria film that was heat treated at 1100 °C delaminated from the substrate in most places. Samples were extracted from the underside of a delaminated piece and analyzed with atom-probe tomography. The resulting data show Ceria and a Mo-rich particle and demonstrate that this approach is feasable in principle to study local compositions in a sample exposed to such extreme conditions.

multicomponent alloys, epsilon phase, EDS, atom pr↗
DOE OSTI2024

CryoTRANS: predicting high-resolution maps of rare conformations from self-supervised trajectories in cryo-EM

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Atomic-Scale Scanning of Domain Network in the Ferroelectric HfO 2 Thin Film

Ferroelectric HfO 2 -based thin films have attracted much interest in the utilization of ferroelectricity at the nanoscale for next-generation electronic devices. However, the structural origin and stabilization mechanism of the ferroelectric phase are not understood because the film is typically nanocrystalline with active yet stochastic ferroelectric domains. Here, in this study, electron microscopy is used to map the in-plane domain network structures of epitaxially grown ferroelectric Y:HfO 2 films in atomic resolution. The ferroelectricity is confirmed in free-standing Y:HfO 2 films, allowing for investigating the structural origin for their ferroelectricity by 4D-STEM, high-resolution STEM, and iDPC-STEM. At the grain boundaries of <111>-oriented Pca2 1 orthorhombic grains, a high-symmetry mixed-(R3m, Pnm2 1 ) phase is induced, exhibiting enhanced polarization due to in-plane compressive strain. Nanoscale Pca2 1 orthorhombic grains and their grain boundaries with mixed-(R3m, Pnm2 1 ) phases of higher symmetry cooperatively determine the ferroelectricity of the Y:HfO 2 film. It is also found that such ferroelectric domain networks emerge when the film thickness is beyond a finite value. Furthermore, in-plane mapping of oxygen positions overlaid on ferroelectric domains discloses that polarization is suppressed at vertical domain walls, while it is active when domains are aligned horizontally with subangstrom domain walls. In addition, randomly distributed 180° charged domain walls are confined by spacer layers.

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

A Three-dimensional Map of the Heliosphere from IBEX

The Interstellar Boundary Explorer (IBEX) mission has shown that variations in the energetic neutral atom (ENA) flux from the outer heliosphere are associated with the solar cycle and longer-term variations in the solar wind (SW). In particular, there is a good correlation between the dynamic pressure of the outbound SW and variations in the later-observed IBEX ENA flux. The time difference between observations of the outbound SW and the heliospheric ENAs with which they correlate ranges from approximately 2 to 6 yr or more, depending on ENA energy and look direction. This time difference can be used as a means of "sounding" the heliosheath, that is, finding the average distance to the ENA source region in a particular direction. Here, we apply this method to build a 3D map of the heliosphere. We use IBEX ENA data collected over a complete solar cycle, from 2009 through 2019, corrected for survival probability to the inner heliosphere. Here we divide the data into 56 "macropixels" covering the entire sky. As each point in the sky is sampled once every 6 months, this gives us a time series of 22 points macropixel –1 on which to time-correlate. Consistent with prior studies and heliospheric models, we find that the shortest distance to the heliopause, d HP , is slightly south of the nose direction (d HP ~ 110–120 au), with a flaring toward the flanks and poles (d HP ~ 160–180 au). The heliosphere extends at least ~350 au tailward, which is the distance limit of the technique.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

X-ray fluorescence mapping: Insights into mesoscale structure impact on battery functional electrochemistry

Abstract Electron transfer and ion transport occurs over multiple-length scales ranging from the atomic to mesoscale within battery materials and electrodes. Micro-X-ray fluorescence (µ-XRF) is an important characterization tool as it can resolve structural, compositional, and redox information while providing insight into the spatial distribution of an electroactive material. In this work, µ-XRF mapping is used to probe the distribution of iron within thin planar slurry-based and thick porous carbon nanotube (CNT)-based magnetite (Fe 3 O 4 ) electrodes. Notably, the porous CNT-based electrode showed homogenous distribution of Fe within the electrode whereas the planar electrode demonstrated distinct Fe aggregates. This information was used to rationalize the electrochemistry observed by cyclic voltammetry and galvanostatic cycling. The thick porous electrode delivered 215% more capacity per gram of magnetite during the first discharge, consistent with increased electrode homogeneity enabling effective ion access and electron transfer. Graphical Abstract

Sadique, Nahian↗
DOE OSTI2023

Multiple-core-hole resonance spectroscopy with ultraintense X-ray pulses

Understanding the interaction of intense, femtosecond X-ray pulses with heavy atoms is crucial for gaining insights into the structure and dynamics of matter. One key aspect of nonlinear light–matter interaction was, so far, not studied systematically at free-electron lasers—its dependence on the photon energy. Here, we use resonant ion spectroscopy to map out the transient electronic structures occurring during the complex charge-up pathways of xenon. Massively hollow atoms featuring up to six simultaneous core holes determine the spectra at specific photon energies and charge states. We also illustrate how different X-ray pulse parameters, which are usually intertwined, can be partially disentangled. The extraction of resonance spectra is facilitated by the possibility of working with a constant number of photons per X-ray pulse at all photon energies and the fact that the ion yields become independent of the peak fluence beyond a saturation point. Our study lays the groundwork for spectroscopic investigations of transient atomic species in exotic, multiple-core-hole states that have not been explored previously.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Experimental and theoretical investigation of the crystalline surface, film, and interface properties of antiperovskite Mn 3 GaN grown by molecular beam epitaxy on MgO(001)

Here, we present a study of the epitaxial growth, characterization, and theoretical modeling of thin film antiperovskite Mn 3 GaN, an antiferromagnetic material with kagome structure which is grown on MgO (001) substrates using N-plasma-assisted molecular beam epitaxy. Reflection high energy electron diffraction is used to assess the in-plane evolution of the film structure during growth, and the surface is investigated in-situ using scanning tunneling microscopy and Auger electron spectroscopy. These results are combined with precision measurements done ex-situ determining the film lattice constants using a combination of x-ray diffraction with reciprocal space mapping and scanning transmission electron microscopy. Overall, a uniform, homogeneous film with an atomically smooth vacuum surface and atomically sharp substrate interface is found having very small in-plane tensile strain and mild out-of-plane compressive strain. First-principles theoretical calculations are applied in order to ascertain the lowest energy models for both the Mn 3 GaN surface and the Mn 3 GaN/MgO film/substrate interface. Models including MnGa versus MnN surface layers and MnGa versus MnN interfacial layers are considered as functions of both the Mn and Ga chemical potentials. The predictions are discussed in comparison to the experimental results. The overall findings suggest that Mn 3 GaN on MgO(001) is a viable epitaxial film which can be further explored in connection with antiferromagnetic spintronics.

Density functional theory↗
DOE OSTI2025

Digital quantum simulation of cavity quantum electrodynamics: insights from superconducting and trapped ion quantum testbeds

We explore the potential for hybrid development of quantum hardware where currently available quantum computers simulate open cavity quantum electrodynamical (CQED) systems for applications in optical quantum communication, simulation and computing. Our simulations make use of a recent quantum algorithm that maps the dynamics of a singly excited open Tavis–Cummings model containing N atoms coupled to a lossy cavity. We report the results of executing this algorithm on two noisy intermediate-scale quantum computers: a superconducting processor and a trapped ion processor, to simulate the population dynamics of an open CQED system featuring N = 3 atoms. By applying technology-specific transpilation and error mitigation techniques, we minimize the impact of gate errors, noise, and decoherence in each hardware platform, obtaining results which agree closely with the exact solution of the system. These results can be used as a recipe for efficient and platform-specific quantum simulation of cavity–emitter systems on contemporary and future quantum computers.

cavity QED↗
DOE OSTI2022

Inspecta Annual Technical Report

Sandia National Laboratories (SNL) is designing and developing an Artificial Intelligence (AI)-enabled smart digital assistant (SDA), Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant). The goal is to provide inspectors an in-field digital assistant that can perform tasks identified as tedious, challenging, or prone to human error. During 2021, we defined the requirements for Inspecta based on reviews of International Atomic Energy Agency (IAEA) publications and interviews with former IAEA inspectors. We then mapped the requirements to current commercial or open-source technical capabilities to provide a development path for an initial Inspecta prototype while highlighting potential research and development tasks. We selected a highimpact inspection task that could be performed by an early Inspecta prototype and are developing the initial architecture, including hardware platform. This paper describes the methodology for selecting an initial task scenario, the first set of Inspecta skills needed to assist with that task scenario and finally the design and development of Inspecta’s architecture and platform.

42 ENGINEERING↗
DOE OSTI2024

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impacts of Curing-Induced Phase Segregation in Silicon Nanoparticle-Based Electrodes

We report the investigation of silicon nanoparticle composite anodes for Li-ion batteries, using a combination of two nm-scale atomic force microscopy-based techniques: scanning spreading resistance microscopy for electrical conduction mapping and contact resonance and force volume for elastic modulus mapping, along with scanning electron microscopy-based energy dispersion spectroscopy, nanoindentation, and electrochemical analysis. Thermally curing the composite anode—made of polyethylene oxide-treated Si nanoparticles, carbon black, and polyimide binder—reportedly improves the anode electrochemical performance significantly. This work demonstrates phase segregation resulting from thermal curing, where alternating bands of carbon and silicon active material are observed. This electrode morphology is retained after extensive cycling, where the electrical conduction of the carbon-rich bands remains relatively unchanged, but the mechanical modulus of the bands decreases distinctly. These electrical and mechanical factors may contribute to performance improvement, with carbon bands serving as a mechanical buffer for Si deformation and providing electrical conduction pathways. This work motivates future efforts to engineer similar morphologies for mitigating capacity loss in silicon electrodes.

25 ENERGY STORAGE↗
DOE OSTI2025

Spectral Properties of Globally Distributed ENA Fluxes across Diverse Regions of the Heliosphere

This study analyzes energetic neutral atom (ENA) spectral properties across distinct regions of globally distributed flux (GDF) sky maps, using Interstellar Boundary Explorer data from a full solar cycle, corrected for time dispersion. By time-shifting the data to the heliosheath using GDF source distances from D. B. Reisenfeld et al., we achieve a more accurate representation of heliosheath GDF energy spectra. We quantify ENA spectral characteristics, heliosheath line-of-sight-integrated proton pressure, and heliosheath proton temperature, comparing these to solar wind properties at 1 au and interplanetary scintillation-derived solar wind data. Our findings show that the spectral index is generally anticorrelated with heliosheath proton temperature and pressure, except in the central tail, where a partial positive correlation is observed. The lowest spectral index values occur when high-latitude heliosheath regions are dominated by fast solar wind from polar coronal holes. The south pole exhibits the flattest energy spectra due to plasma heating from both fast solar wind and a late-2014 pressure pulse. The central tail shows shorter variability (5–6 yr) for spectral index and heliosheath proton temperature, while proton pressure follows the 11 yr solar cycle. Most spectral shapes exhibit a “knee” distribution, peaking during solar maximum, with an “ankle” shape observed only at the south pole during solar cycle transitions. Asymmetry in proton pressure in the lobes is driven by the draping effect of the local interstellar magnetic field. This study provides insights into the energetic properties of GDF across the heliosphere, enhancing our understanding of the heliospheric environment.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Structural Amorphization-Induced Topological Order

Electronic properties of crystals are inherently pertained to crystalline symmetry, so that amorphization that lowers and breaks symmetry is detrimental. One important crystalline property is electron band topology which is known to be weakened and destroyed by structural disorder. Here, we report a counterintuitive theoretical discovery that atomic structural disorder by amorphization can in fact induce electronic order of topology in an otherwise topologically trivial crystal. The resulting nontrivial topology is characterized by a nonzero spin Bott index, associated with robust topological edge states and quantized conductance. Further, the underlying topological phase transition (TPT) from a trivial crystal to a topological amorphous is analyzed by mapping out a phase diagram in the degree of structural disorder using an effective medium theory. The atomic disorder is revealed to induce topological order by renormalizing the spectral gap toward nontriviality near the phase boundary. As a concrete example, we further show such TPT in amorphous stanane by first-principles calculations. Our findings point to possible observation of an electronic ordering transition accompanied by a structural disorder transition.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Understanding Formation of Irradiation-Induced Defects through 4D-STEM, Electron Tomography, and WBDF-STEM

A major challenge in advancing nuclear materials for next-generation fission and proposed fusion reactors is to comprehensively understand the formation of irradiation-induced defects. Here it is essential to correlate the evolution of irradiation-induced defects and the degradation of mechanical properties, as they collectively dictate the material's lifespan and ensure nuclear safety. Scanning transmission electron microscopy (STEM) based techniques have emerged as indispensable tools for irradiation-induced defect characterization, offering high spatial resolution imaging and chemical analysis, such as electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDXS). These techniques have been effectively used to obtain an atomic-scale view of the defect structure. Recent advances in electron microscopy, particularly in 4D-STEM, offer detailed insight into microstructural evolution by capturing full 2D diffraction patterns at every pixel position. Using high-speed direct electron detectors, this technology generates a four-dimensional dataset, overcoming the limitations of traditional STEM imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2026

pyDiSCaMB : enabling the use of multipolar scattering factors in Phenix

Multipolar scattering models, such as the transferable aspherical atom model, account for atomic chemical interactions and provide a more accurate representation of experimental data. However, the simpler independent atom model (IAM), which assumes non-interacting atoms, is the only model available in the most widely used macromolecular refinement programs. This is primarily because IAM offers a hard-to-beat combination of computational efficiency and modelling power at typical macromolecular resolutions. By contrast, more accurate multipolar modelling has historically been limited due to its computational cost and the absence of an interface between software capable of calculating structure factors and gradients based on multipolar models and software designed for macromolecular refinement. This work introduces pyDiSCaMB , a Python software package designed to integrate between the computational crystallography toolbox ( cctbx ) and the quantum crystallography library DiSCaMB ( Densities in Structural Chemistry and Molecular Biology ), thus enabling multipolar scattering models in Phenix 's toolkit. The implementation, features and capabilities of pyDiSCaMB are presented, the runtimes for the calculation of structure factor and target gradients with respect to atomic parameters are explored, and Fourier images of electrostatic potential, electron density and deformation maps are computed as illustrative examples. The pyDiSCaMB library will make multipolar modelling widely available to the structural biology community, potentially transforming refinement and model-building for both crystallography and cryogenic electron microscopy (cryoEM).

MATTS data bank↗
DOE OSTI2023

Improved joint X-ray and neutron refinement procedure in Phenix

Neutron diffraction is one of the three crystallographic techniques (X-ray, neutron and electron diffraction) used to determine the atomic structures of molecules. Its particular strengths derive from the fact that H (and D) atoms are strong neutron scatterers, meaning that their positions, and thus protonation states, can be derived from crystallographic maps. However, because of technical limitations and experimental obstacles, the quality of neutron diffraction data is typically much poorer (completeness, resolution and signal to noise) than that of X-ray diffraction data for the same sample. Further, refinement is more complex as it usually requires additional parameters to describe the H (and D) atoms. The increase in the number of parameters may be mitigated by using the `riding hydrogen' refinement strategy, in which the positions of H atoms without a rotational degree of freedom are inferred from their neighboring heavy atoms. However, this does not address the issues related to poor data quality. Therefore, neutron structure determination often relies on the presence of an X-ray data set for joint X-ray and neutron (XN) refinement. In this approach, the X-ray data serve to compensate for the deficiencies of the neutron diffraction data by refining one model simultaneously against the X-ray and neutron data sets. To be applicable, it is assumed that both data sets are highly isomorphous, and preferably collected from the same crystals and at the same temperature. However, the approach has a number of limitations that are discussed in this work by comparing four separately re-refined neutron models. To address the limitations, a new method for joint XN refinement is introduced that optimizes two different models against the different data sets. This approach is tested using neutron models and data deposited in the Protein Data Bank. The efficacy of refining models with H atoms as riding or as individual atoms is also investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Complex water networks visualized by cryogenic electron microscopy of RNA

The stability and function of biomolecules are directly influenced by their myriad interactions with water. Here we investigated water through cryogenic electron microscopy (cryo-EM) on a highly solvated molecule: the Tetrahymena ribozyme. By using segmentation-guided water and ion modelling (SWIM), an approach combining resolvability and chemical parameters, we automatically modelled and cross-validated water molecules and Mg 2+ ions in the ribozyme core, revealing the extensive involvement of water in mediating RNA non-canonical interactions. Unexpectedly, in regions where SWIM does not model ordered water, we observed highly similar densities in both cryo-EM maps. In many of these regions, the cryo-EM densities superimpose with complex water networks predicted by molecular dynamics, supporting their assignment as water and suggesting a biophysical explanation for their elusiveness to conventional atomic coordinate modelling. Our study demonstrates an approach to unveil both rigid and flexible waters that surround biomolecules through cryo-EM map densities, statistical and chemical metrics, and molecular dynamics simulations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Multiwavelength anomalous X-ray diffraction for combined imaging of atomic displacement and strain

The X-ray Bragg coherent diffractive imaging (CDI) technique assumes that the structure factor holds constant over the measured crystal. This approximation breaks down for materials exhibiting variations in the unit-cell configuration, such as piezo- and ferroelectrics. In that case, the strain field cannot be reliably determined from the reconstruction because the lattice deformation and the structure factor contribute concomitantly. Proposed here is a solution to this problem achieved by combining Bragg CDI and the multiwavelength anomalous diffraction approach that measures a Friedel pair of reflections at two different photon energies near an absorption edge. Comparing the obtained reconstructions with a parametric model that includes calculating the scattering amplitude as a function of wavelength and the unit-cell configuration, the contributions of the lattice deformation and the structure factor are separated. Simulations of the ferroelectric material BaTiO 3 demonstrate the possibility of simultaneous probing of the strain and displacement of the Ti atoms. The proposed method opens up an opportunity to apply coherent X-ray diffraction for nanoscale-resolved 3D mapping of polarization domains in micro- and nanocrystals.

lattice deformation↗