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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The design of a photoionization front experiment using the Z-Machine as a driving source and estimated measurements

Radiation-driven heat fronts are present in the early universe during reionization, the circumstellar medium of supernovae, and in high-energy-density physics experiments. Dedicated experiments to observe and diagnose the behavior of these types of heat fronts can improve our understanding of these phenomena. A simulation study of photoionization fronts using the HELIOS-CR radiation hydrodynamics code provides an experimental design for the Z-Machine at Sandia National Laboratory using a measurement-calibrated input radiation flux to drive the photoionization front. The simulations use detailed atomic physics and non-diffusive radiation transport in 1D to determine an optimal gas pressure of 0.75 atm for an experiment in N gas as well as the effects of increasing the thickness of the window that seals the gas cell. Post-processing of these simulations demonstrates that ratios of atomic rate coefficients place the heat front in a physics regime where photoionization dominates the energy deposition. Here, to see the sensitivity of the simulations to changes in the model and spatial grid, this analysis performed resolution, atomic model detail, and radiation transport angular grid studies showing less than 10% deviation from the nominal model for increased complexity, when possible. An effort to emulate 3D geometric effects on the radiation flux using an artificial attenuation scheme has shown that, even for conservative estimates of the flux, simulations still produce a photoionization front. Estimations of a streaked, visible spectroscopy measurement using SPECT3D showed that line emission measurements are present early in time and that later in time thermal emission should become dominant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1998

Determining the Molecular Packing Arrangements on Protein Crystal Faces by Atomic Force Microscopy

Periodic Bond Chain (PBC) analysis of the packing of tetragonal lysozyme crystals have revealed that there are two possible molecular packing arrangements for the crystal faces. The analysis also predicted that only one of these, involving the formation of helices about the 4(sub 3) axes, would prevail during crystal growth. In this study high resolution atomic force microscopy (AFM) was employed to verify these predictions for the (110) crystal face. A computer program was developed which constructs the expected AFM image for a given tip shape for each possible molecular packing arrangement. By comparing the actual AFM image with the predicted images the correct packing arrangement was determined. The prediction of an arrangement involving 4(sub 3) helices was confirmed in this manner,"while the alternate arrangement was not observed. The investigation also showed the protein molecules were packed slightly closer about the 4(sub 3) axes than in the crystallographic arrangement of the crystal interior. This study demonstrates a new approach for determining the molecular packing arrangements on protein crystal faces. It also shows the power of combining a theoretical PBC analysis with experimental high resolution AFM techniques in probing protein crystal growth processes at the molecular level.

Li, Huayu↗
DOE OSTI2025

Microstructural features and deuterium diffusion in lithium penta-aluminate pellets under He + and D + ion irradiation

Lithium (Li) penta-aluminate (LiAl 5 O 8 ) is investigated as a potential tritium (T) breeding material, with a focus on microstructural response to ion irradiation and deuterium (D) diffusion behavior. Under high-fluence ion irradiation (2 x 10 17 (He + +D + )/cm 2 ) at 773 K, LiAl 5 O 8 exhibits significant disorder on the Li sublattice, as revealed by atomic-resolution scanning transmission electron microscopy, while the Al and O sublattices remain stable, demonstrating strong resistance to structural amorphization. Irradiation induces the formation of platelet-shaped antiphase boundaries (APBs), which may serve as effective D trapping sites. Atom probe tomography suggests the presence of 6 LiD clusters in the mass spectra, though definite conclusions regarding APB composition are hindered by signal overlap and limited data statistics. Time-of-flight secondary ion mass spectrometry reveals that D retention approaches to saturation at 3 x 10 17 (He + +D + )/cm 2 . Isothermal and isochronal annealing studies determine an average diffusivity of 1.6 x 10 -13 at 773 K and an effective activation energy of 0.8 ± 0.1 eV for D migration. Compared to γ-LiAlO 2 , LiAl 5 O 8 demonstrates superior irradiation resistance, minimal Li loss, and enhanced D retention, underscoring its potential as a durable breeder material for T production. In conclusion, these findings provide key insights into the microstructural evolution, defect dynamics, and D retention mechanisms in LiAl 5 O 8 under reactor-relevant conditions.

42 ENGINEERING↗
DOE OSTI2026

Atomic Evolution of Hydrogen Intercalation Wave Dynamics in Palladium Nanocrystals Revealed by Liquid-Phase Transmission Electron Microscopy

Solute-intercalation-induced phase separation creates spatial heterogeneities in host materials, a phenomenon ubiquitous in batteries, hydrogen storage, and other energy devices. Despite many efforts, probing intercalation processes at the atomic scale has been a significant challenge. By utilizing liquid-phase transmission electron microscopy (TEM), we study hydrogen (de)intercalation in palladium nanocrystals as a model system and have achieved unprecedented atomic-resolution imaging of hydrogen intercalation wave dynamics. Our observations reveal that intercalation wave mechanisms, instead of shrinking-core mechanisms, prevail at ambient temperature for palladium nanocubes ranging from ∼60 nm down to ∼10 nm. Systematic image analysis uncovers the atomic evolution of the hydrogen intercalation wave, transitioning from nonplanar and inclined boundaries to those closely aligned with {100} planes. Our kinetic Monte Carlo simulations demonstrate that the observed intercalation wave dynamics correspond to sorption pathways minimizing the lattice mismatch strain at the phase boundary. In conclusion, unveiling the atomic intercalation pathways holds profound implications for engineering intercalation-mediated devices and advancements in energy sciences.

Lee, Daewon [Lawrence Berkeley National Laboratory↗
NASA NTRS1990

Design and calibration of a vacuum compatible scanning tunneling microscope

A vacuum compatible scanning tunneling microscope was designed and built, capable of imaging solid surfaces with atomic resolution. The single piezoelectric tube design is compact, and makes use of sample mounting stubs standard to a commercially available surface analysis system. Image collection and display is computer controlled, allowing storage of images for further analysis. Calibration results from atomic scale images are presented.

Abel, Phillip B.↗
DOE OSTI2021

Correlating 3D Surface Atomic Structure and Catalytic Activities of Pt Nanocrystals

Active sites and catalytic activity of heterogeneous catalysts is determined by their surface atomic structures. However, probing the surface structure at an atomic resolution is difficult, especially for solution ensembles of catalytic nanocrystals, which consist of heterogeneous particles with irregular shapes and surfaces. In this study, we constructed 3D maps of the coordination number (CN) and generalized CN ($\bar{C}\bar{N}$) for individual surface atoms of sub-3 nm Pt nanocrystals. Our results reveal that the synthesized Pt nanocrystals are enclosed by islands of atoms with nonuniform shapes that lead to complex surface structures, including a high ratio of low-coordination surface atoms, reduced domain size of low-index facets, and various types of exposed high-index facets. 3D maps of $\bar{C}\bar{N}$ are directly correlated to catalytic activities assigned to individual surface atoms with distinct local coordination structures, which explains the origin of high catalytic performance of small Pt nanocrystals in important reactions such as oxygen reduction reactions and CO electro-oxidation.

3D atomic structure↗
DOE OSTI2021

High-Resolution Imaging of Unstained Polymer Materials

Electron microscopy has played an important role in polymer characterization. Traditionally, electron diffraction is used to study crystalline polymers while transmission electron microscopy is used to study microphase separation in stained block copolymers and other multiphase systems. We describe developments that eliminate the barrier between these two approaches - it is now possible to image polymer crystals with atomic resolution. The focus of this Review is on high-resolution imaging (30 Å and smaller) of unstained polymers. Recent advances in hardware allow for capturing numerous (as many as 105) low-dose images from an unperturbed specimen; beam damage is a significant barrier to high-resolution electron microscopy of polymers. Machine-learning-based software is then used to sort and average the images to retrieve pristine structural information from a collection of noisy images. Acknowledging the heterogeneity in polymer samples prior to averaging is essential. Molecular conformations in a wide range of amphiphilic block copolymers, polymerized ionic liquids, and conjugated polymers can be gleaned from two-dimensional projections (2D), three-dimensional (3D) tomograms, and four-dimensional (4D) scanning transmission electron microscopy (STEM) data sets where 2D diffraction patterns are taken as a function of position. Some methods such as phase contrast STEM have been used to image closely related materials such as metal-organic frameworks but not polymers. With improvements in hardware and software, such methods may soon be applied to polymers. Our goal is to provide a comprehensive understanding of the strategies toward the high-resolution imaging of radiation sensitive polymer materials at different length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mending cracks atom-by-atom in rutile TiO2 with electron beam radiolysis

Abstract Rich electron-matter interactions fundamentally enable electron probe studies of materials such as scanning transmission electron microscopy (STEM). Inelastic interactions often result in structural modifications of the material, ultimately limiting the quality of electron probe measurements. However, atomistic mechanisms of inelastic-scattering-driven transformations are difficult to characterize. Here, we report direct visualization of radiolysis-driven restructuring of rutile TiO 2 under electron beam irradiation. Using annular dark field imaging and electron energy-loss spectroscopy signals, STEM probes revealed the progressive filling of atomically sharp nanometer-wide cracks with striking atomic resolution detail. STEM probes of varying beam energy and precisely controlled electron dose were found to constructively restructure rutile TiO 2 according to a quantified radiolytic mechanism. Based on direct experimental observation, a “two-step rolling” model of mobile octahedral building blocks enabling radiolysis-driven atomic migration is introduced. Such controlled electron beam-induced radiolytic restructuring can be used to engineer novel nanostructures atom-by-atom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Atomic-Scale Imaging of Lithium Vacancies in a Battery Cathode by Multislice Electron Ptychography

Atomic-resolution imaging of battery materials is critical for identification of local defects and structural variations, which are tied to battery performance. However, since battery materials are, by design, optimized to allow ion motion in response to an applied electric field, they are also very sensitive to radiation damage by an electron beam. Image resolution is therefore severely constrained by the dose applied. Here, we show that multislice electron ptychography (MEP) can provide sub-ångström lateral resolution images of both light and heavy elements of a Li-ion battery cathode, along with nanometer-scale depth information and greater dose efficiency than conventional electron microscopy methods. Using the depth-sectioning capability of MEP, we have been able to obtain direct visualizations of Li vacancy clusters, atom column by atom column, in Li x Ni 0.33 Mn 0.33 Co 0.33 O 2 (NMC111) cathodes. This capability to track Li distributions will be valuable in understanding, informing, and optimizing electrode material design for ion storage and transfer.

batteries↗
DOE OSTI2021

Synergic grain boundary segregation and precipitation in W- and W-Mo-containing high-entropy borides

The structures of W- and W-Mo-containing high-entropy borides (HEBs) are systematically studied by combining atomic-resolution transmission electron microscopy imaging, electron diffraction, and chemical analysis. Here, we reveal that W or W-Mo addition in HEBs leads to segregation of these elements to the grain boundaries (GBs). In the meantime, W- or W-Mo-rich precipitates also form along the GBs. Crystallographic analysis and atomic-scale imaging show that the GB precipitates in both W- and W-Mo-containing HEBs have a cube-on-cube orientation relationship with the matrix. With further strain analysis, the coherency of the precipitate/matrix interface is validated. Nanoindentation tests show that the simultaneous GB segregation and coherent precipitation, as a supplement to the grain hardening, provide additional hardening of the HEBs. Our work provides an in-depth understanding of the GB segregation and precipitation behaviors of HEBs. It suggests that GB engineering could be potentially used for optimizing the performance of high-entropy ceramics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Probing atom dynamics of excited Co-Mo-S nanocrystals in 3D

Advances in electron microscopy have enabled visualizations of the three-dimensional (3D) atom arrangements in nano-scale objects. The observations are, however, prone to electron-beam-induced object alterations, so tracking of single atoms in space and time becomes key to unravel inherent structures and properties. Here, we introduce an analytical approach to quantitatively account for atom dynamics in 3D atomic-resolution imaging. The approach is showcased for a Co-Mo-S nanocrystal by analysis of time-resolved in-line holograms achieving ~1.5 Å resolution in 3D. The analysis reveals a decay of phase image contrast towards the nanocrystal edges and meta-stable edge motifs with crystallographic dependence. These findings are explained by beam-stimulated vibrations that exceed Debye-Waller factors and cause chemical transformations at catalytically relevant edges. This ability to simultaneously probe atom vibrations and displacements enables a recovery of the pristine Co-Mo-S structure and establishes, in turn, a foundation to understand heterogeneous chemical functionality of nanostructures, surfaces and molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Improving the picture of atomic structure in nonoriented polymer domains using the pair distribution function: A study of polyamide 6

Abstract Investigations of the atomic structures within polyamides started over 80 years ago and continue today. These weakly ordered materials diffract X‐rays poorly and typically require postprocessing to obtain idealized samples for structural studies. An important goal remains to develop techniques to study the local structure in its natural state, with atomic resolution, and with sensitivity to subtle changes due to synthesis conditions or other technologically relevant processing procedures. Here, we compare the structures of as‐produced, nonoriented polyamide 6 ([C 6 H 11 NO] n ) from both hydrolytic and anionic processes. A total scattering pair distribution function approach is used to elucidate information about the atomic bonding, molecular conformation, chain packing, crystallite size, and ratio of ordered to disordered domain content. The results are compared with those from standard analytical methods.

Terban, Maxwell W.↗
DOE OSTI2022

Probing Electronic and Structural Transformations during Thermal Reduction of the Promising Water Splitting Perovskite BaCe 0.25 Mn 0.75 O 3

Here, in this report, we investigate the thermal reduction of the octahedral perovskite BaCe 0.25 Mn 0.75 O 3 (BCM) using in situ electron energy loss spectroscopy (EELS) in an aberration-corrected transmission electron microscope (TEM). The 12R-polytype of BCM is known to demonstrate high solar thermochemical hydrogen production capacity. In situ EELS measurements show that Mn is the active redox cation in BCM, undergoing thermal reduction from Mn 4+ to Mn 3+ during heating to 700 °C inside the TEM under a high vacuum. The progressive reduction of Mn 4+ during oxygen vacancy (O v ) formation was monitored as a function of temperature. Additionally, atomic-resolution scanning transmission electron microscopy identified two different types of twin boundaries present in the oxidized and reduced form of 12R-BCM, respectively. These two types of twin boundaries were shown, via computational modeling, to modulate the site-specific O v formation energies in 12R-BCM. It is concluded that these types of atomic defects provide sites more energetically favorable for O v formation during thermal reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Synthesis of Co‐Doped MoS 2 Monolayers with Enhanced Valley Splitting

Abstract Internal magnetic moments induced by magnetic dopants in MoS 2 monolayers are shown to serve as a new means to engineer valley Zeeman splitting (VZS). Specifically, successful synthesis of monolayer MoS 2 doped with the magnetic element Co is reported, and the magnitude of the valley splitting is engineered by manipulating the dopant concentration. Valley splittings of 3.9, 5.2, and 6.15 meV at 7 T in Co‐doped MoS 2 with Co concentrations of 0.8%, 1.7%, and 2.5%, respectively, are achieved as revealed by polarization‐resolved photoluminescence (PL) spectroscopy. Atomic‐resolution electron microscopy studies clearly identify the magnetic sites of Co substitution in the MoS 2 lattice, forming two distinct types of configurations, namely isolated single dopants and tridopant clusters. Density functional theory (DFT) and model calculations reveal that the observed enhanced VZS arises from an internal magnetic field induced by the tridopant clusters, which couples to the spin, atomic orbital, and valley magnetic moment of carriers from the conduction and valence bands. The present study demonstrates a new method to control the valley pseudospin via magnetic dopants in layered semiconducting materials, paving the way toward magneto‐optical and spintronic devices.

Zhou, Jiadong↗
DOE OSTI2020

On the redistribution of charge in La 0.7 Sr 0.3 CrO 3 /La 0.7 Sr 0.3 MnO 3 multilayer thin films

The atomic and electronic structures of La 0.7 Sr 0.3 MnO 3 (LSMO)/La 0.7 Sr 0.3 CrO 3 (LSCO) multilayer thin films are investigated using aberration corrected scanning transmission electron microscopy (STEM) imaging and spectroscopy. Atomic resolution high angle annular dark-field reveals that LSMO layers have an expanded out-of-plane lattice parameter compared to compressed LSCO layers, contrasting with x-ray diffraction measurements. The expansion is found to result from preferential oxygen vacancy formation in LSMO during STEM sample preparation as determined by electron energy-loss spectroscopy. The La/Sr atom column intensity is also found to oscillate by about 4% between the LSMO and LSCO layers, indicative of La/Sr concentration variation. Using energy-dispersive x-ray spectroscopy in combination with image simulations, we confirm the La/Sr inhomogeneity and elucidate the origin of charge redistribution within the multilayer. These results illuminate the sensitivity of the technique to subtle structural, chemical, and electronic features that can arise to compensate charge imbalances in complex oxide heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Large Scale MD to Predict Epitope Regions in HIV Env [Slides]

Highly dense carbohydrates located on the surface of the HIV Env protein play a key role in immune evasion. Such evolutionary adaptation hampers any attempt to obtain a full mechanistic understanding of the role played by the glycans in protecting the virus against an effective immune response. Moreover, and due to their chemical variability, an accurate molecular understanding of the so called “glycan shield” is still limited by the lack of effective resolution of state-of-the-art experimental technics. Here, we have used extensive computational modelling in order to fill this gap, addressing the presence of a large glycan variability as observed experimentally. Based on an automated pipeline, we were able to assemble, set-up and simulate via Molecular dynamics hundreds of different glycosylated Env variants at nearly atomic resolution, recapitulating the glycosylation distributions observed experimentally. Results from these simulations were subjected to machine learning and very accurate prediction of simulation derived glycan shielding areas of each glycan as a function of static sequence features. Such predictive models of per-glycan shielding, incorporating both glycan dynamics and heterogeneity, were used to develop a novel sequence-based glycan shield mapping strategy. Parallel to these studies, we also developed an accurate machine learning approach to predict glycan heterogeneity data using sequence features and found good prediction accuracy.

59 BASIC BIOLOGICAL SCIENCES↗