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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimal 3D chemical imaging with multimodal electron tomography

Accurate mapping of nanoscale chemistry in three dimensions (3D) has been a longstanding challenge. Modern electron microscopy provides chemical images by electron energy loss spectroscopy (EELS) and energy dispersive x-ray spectrometry (EDX) but requires high fluences that damage specimens. In 3D, the requirements are worse; electron tomography demands many high-fluence chemical maps for reconstruction, creating a tradeoff between resolution, accuracy, and sample survival. Fused multimodal electron tomography (MM-ET) alleviates this requirement by leveraging lower-fluence high-angle annular dark-field (HAADF) images alongside a few chemical maps to dramatically improve chemical resolution. Here, experimental and computational parameter space is systematically explored to determine when MM-ET performs best. Ideal imaging conditions balance sample survival with resolution and chemical specificity; we recommend a tilt range of at least ± 70°, acquiring 40 equally spaced HAADF projections (signal-to-noise > 10), and 7 EELS/EDX maps of each chemistry (signal-to-noise > 4).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗
DOE OSTI2022

Assessing rodents as carriers of pathogenic Leptospira species in the U.S. Virgin Islands and their risk to animal and public health

Leptospirosis is a global zoonotic disease caused by pathogenic bacteria of the genus Leptospira. We sought to determine if rodents in U.S. Virgin Islands (USVI) are carriers of Leptospira. In total, 140 rodents were sampled, including 112 Mus musculus and 28 Rattus rattus. A positive carrier status was identified for 64/140 (45.7%); 49 (35.0%) were positive by dark-field microscopy, 60 (42.9%) by culture, 63 (45.0%) by fluorescent antibody testing, and 61 (43.6%) by real-time polymerase chain reaction (rtPCR). Molecular typing indicated that 48 isolates were L. borgpetersenii and 3 were L. kirschneri; the remaining nine comprised mixed species. In the single culture-negative sample that was rtPCR positive, genotyping directly from the kidney identified L. interrogans. Serotyping of L. borgpetersenii isolates identified serogroup Ballum and L. kirschneri isolates as serogroup Icterohaemorrhagiae. These results demonstrate that rodents are significant Leptospira carriers and adds to understanding the ecoepidemiology of leptospirosis in USVI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials

In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strain-driven oxygen vacancy ordering in LaNiO 3 thin films revealed by integrated differential phase contrast imaging in scanning transmission electron microscopy

Rare-earth nickelates, such as LaNiO 3 (LNO), exhibit complex electronic properties, with ordered oxygen vacancies (OOV) influencing conductivity and magnetic behavior. We investigate the structural stability of strain-induced OOV phases in LNO thin films grown on SrTiO 3 substrates and the impact of Ruddlesden–Popper (RP) faults. Using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and integrated differential phase contrast (iDPC) STEM imaging, we conducted atomic-scale structural and compositional analyses of OOV. Geometric phase analysis (GPA) was employed to measure the strain in fault-free and RP fault regions, while density functional theory (DFT) calculations explored different OOV arrangements in the LNO phase. Simulated iDPC-STEM imaging of energy-stabilized structures was performed to correlate with experimental results. Here, our findings reveal superstructure modulation in the chemical composition and atomic-scale lattice structure in LNO, primarily due to the formation of the OOV in Ni–O layers of the LaNiO 2.5 phase. The out-of-plane compressive strain of about 2% stabilizes this phase, reducing the strain, diminishing OOV, and transforming them into LNO.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multifunctional nanopore electrode array method for characterizing and manipulating single entities in attoliter-volume enclosures

Structurally regular nanopore arrays fabricated to contain independently controllable annular electrodes represent a new kind of architecture capable of electrochemically addressing small collections of matter—down to the single entity (molecule, particle, and biological cell) level. Furthermore, these nanopore electrode arrays (NEAs) can also be interrogated optically to achieve single entity spectroelectrochemistry. Larger entities such as nanoparticles and single bacterial cells are investigated by dark-field scattering and potential-controlled single-cell luminescence experiments, respectively, while NEA-confined molecules are probed by single molecule luminescence. By carrying out these experiments in arrays of identically constructed nanopores, massively parallel collections of single entities can be investigated simultaneously. The multilayer metal–insulator design of the NEAs enables highly efficient redox cycling experiments with large increases in analytical sensitivity for chemical sensing applications. NEAs may also be augmented with an additional orthogonally designed nanopore layer, such as a structured block copolymer, to achieve hierarchically organized multilayer structures with multiple stimulus-responsive transport control mechanisms. Finally, NEAs constructed with a transparent bottom layer permit optical access to the interior of the nanopore, which can result in the cutoff of far-field mode propagation, effectively trapping radiation in an ultrasmall volume inside the nanopore. Furthermore, the bottom metal layer may be used as both a working electrode and an optical cladding layer, thus, producing bifunctional electrochemical zero-mode waveguide architectures capable of carrying out spectroelectrochemical investigations down to the single molecule level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Current advances on Talbot–Lau x-ray imaging diagnostics for high energy density experiments (invited)

Talbot–Lau x-ray interferometry is a refraction-based diagnostic that can map electron density gradients through phase-contrast methods. The Talbot–Lau x-ray deflectometry (TXD) diagnostics have been deployed in several high energy density experiments. To improve diagnostic performance, a monochromatic TXD was implemented on the Multi-Tera Watt (MTW) laser using 8 keV multilayer mirrors (Δθ/θ = 4.5%-5.6%). Copper foil and wire targets were irradiated at 10 14 –10 15 W/cm 2 . Laser pulse length (~10 to 80 ps) and backlighter target configurations were explored in the context of Moiré fringe contrast and spatial resolution. Foil and wire targets delivered increased contrast <30%. The best spatial resolution (<6 μm) was measured for foils irradiated 80° from the surface. Further TXD diagnostic capability enhancement was achieved through the development of advanced data postprocessing tools. The Talbot Interferometry Analysis (TIA) code enabled x-ray refraction measurements from the MTW monochromatic TXD. Additionally, phase, attenuation, and dark-field maps of an ablating x-pinch load were retrieved through TXD. The images show a dense wire core of ~60 μm diameter surrounded by low-density material of ~40 μm thickness with an outer diameter ratio of ~2.3. Attenuation at 8 keV was measured at ~20% for the dense core and ~10% for the low-density material. Instrumental and experimental limitations for monochromatic TXD diagnostics are presented. Enhanced postprocessing capabilities enabled by TIA are demonstrated in the context of high-intensity laser and pulsed power experimental data analysis. Significant advances in TXD diagnostic capabilities are presented. Furthermore, these results inform future diagnostic technique upgrades that will improve the accuracy of plasma characterization through TXD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Proton acceleration in an overdense hydrogen plasma by intense CO 2 laser pulses with nonlinear propagation effects in the underdense pre-plasma

We report on proton acceleration from intense CO 2 laser-irradiated hydrogen plasmas at near-critical densities, with the density gradient steepened by Nd:YAG laser ablation-driven hydrodynamic shocks. While the experimental results, such as the quasi-monoenergetic proton spectra and their scaling with respect to the laser energy, are generally in agreement with the simulations, certain laser shots produced significantly higher proton energies than anticipated during the experiment. The increased proton energy may be linked to nonlinear propagation effects in the steepened plasma density ramp before the critical surface, including relativistic self-focusing and, for the case of temporally-structured laser pulses observed in the experiment, focusing of the trailing pulse through the plasma channel formed by the leading pulse 25 ps ahead. The occurrence of channel focusing in the underdense hydrogen plasma is supported by a subsequent pump-probe experiment with a dark-field imaging technique, where the formation of ion channels was observed after the passage of an intense CO 2 laser pulse

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Interface atomic structures in a cadmium arsenide/III–V semiconductor heterostructure

The interface atomic structure between an epitaxial thin film of the prototype topological semimetal cadmium arsenide (Cd 3 As 2 ) and a III–V semiconductor layer is investigated using high-angle annular dark-field imaging in an aberration-corrected scanning transmission electron microscope. We find that the interface unit cell adopts a defined stoichiometry that is CdSb-like, which is achieved through the insertion of periodically arranged Cd vacancies in the terminating Cd-plane of Cd 3 As 2 . This interface stoichiometry is consistent with the Sb-termination of the III–V layer and the fact that CdSb is the thermodynamically stable phase in the Cd–Sb binary system. We find at least two distinct alignments of the film with respect to the buffer layer, which are characterized by a $\frac{1}{4}$ <100> Cd 3 As 2 shift parallel to the interface. We show that steps of half unit cell height in the III–V layer can produce these distinct interface structures.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Effect of molecular permanent dipole moment on guest aggregation and exciton quenching in phosphorescent organic light emitting diodes

This study explores the effect of molecular permanent dipole moment (PDM) on aggregation of guest molecules in phosphorescent host–guest organic light-emitting diodes (OLEDs). Through a combination of photoluminescence measurements, high-angle annular dark-field scanning transmission electron microscopy analysis, and an Ising model based physical vapor-deposition simulation, we show that higher PDM of tris[2-phenylpyridinato-C2,N]iridium(III) guest can actually lead to a reduced aggregation relative to tris[bis[2-(2-pyridinyl-N)phenyl-C] (acetylacetonato)iridium(III) when doped into a non-polar host 1,3,5-tris(carbazol-9-yl)benzene. This study further explores the effect of host polarity by using a polar host 3′,5′-di(carbazol-9-yl)-[1,1′-biphenyl]-3,5-dicarbonitrile, and it is shown that the polar host leads to reduced guest aggregation. In conclusion, this study provides a comprehensive understanding of the impact of molecular PDM on OLED material efficiency and stability, providing insights for optimizing phosphorescent OLED materials.

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

Influence of excess silicon on polytype selection during metal-mediated epitaxy of GaN nanowires

For this work, we have examined the origins of polytype selection during metal-mediated molecular-beam epitaxy of GaN nanowires (NWs). High-angle annular dark-field scanning transmission electron microscopy reveals [111]-oriented zinc blende (ZB) NWs and [0001]-oriented wurtzite (WZ) NWs, with SixNy at the interface between individual NWs and the Si (001) substrate. Quantitative energy dispersive x-ray spectroscopy reveals a notably higher Si concentration of 7.0% ± 2.3% in zinc blende (ZB) NWs than 2.3% ± 1.2% in wurtzite (WZ) NWs. Meanwhile, density functional theory calculations show that incorporation of 8 at. % Si on the Ga sublattice inverts the difference in formation energies between WZ and ZB GaN, such that the ZB polytype of GaN is stabilized. This identification of Si and other ZB polytype stabilizers will enable the development of polytype heterostructures in a wide variety of WZ-preferring compounds.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Saha, Ambarneil↗
DOE OSTI2021

Fabrication and field emission properties of vertical, tapered GaN nanowires etched via phosphoric acid

The controlled fabrication of vertical, tapered, and high-aspect ratio GaN nanowires via a two-step top-down process consisting of an inductively coupled plasma reactive ion etch followed by a hot, 85% H 3 PO 4 crystallographic wet etch is explored. The vertical nanowires are oriented in the $[0001]$ direction and are bound by sidewalls comprising of $\{33\bar{6}2\}$ semipolar planes which are at a 12° angle from the [0001] axis. High temperature H3PO4 etching between 60 °C and 95 °C result in smooth semipolar faceting with no visible micro-faceting, whereas a 50 °C etch reveals a micro-faceted etch evolution. High-angle annular dark-field scanning transmission electron microscopy imaging confirms nanowire tip dimensions down to 8–12 nanometers. The activation energy associated with the etch process is 0.90 ± 0.09 eV, which is consistent with a reaction-rate limited dissolution process. The exposure of the $\{33\bar{6}2\}$ type planes is consistent with etching barrier index calculations. The field emission properties of the nanowires were investigated via a nanoprobe in a scanning electron microscope as well as by a vacuum field emission electron microscope. Finally, the measurements show a gap size dependent turn-on voltage, with a maximum current of 33 nA and turn-on field of 1.92 V nm -1 for a 50 nm gap, and uniform emission across the array.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Machine Learning-Enabled Image Classification for Automated Electron Microscopy

Abstract Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of “big data” and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.

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 OSTI2023

Reducing Artifacts in BF and HAADF-STEM Images of Pt/C Fuel Cells using MBIR-ARAR

Electron tomography is a powerful tool for characterization of three-dimensional (3D) nanoscale materials and devices. Bright-field (BF) and high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) are two widely used imaging modes in electron tomography. These imaging modalities have proven to be useful for characterizing the structure of carbon-supported platinum (Pt/C) electrocatalysts used in fuel cells, which are an important class of clean energy conversion systems. BF and HAADF-STEM images are typically simultaneously acquired due to the complementary information they contain, as BF-STEM is more suitable for characterizing carbon due to its ability to detect lighter elements, while HAADF-STEM is more suitable for characterizing platinum due to its sensitivity to atomic number. However, the quality of BF- and HAADF-STEM images is often compromised by various artifacts, such as local blurring due to abrupt contrast changes as well as missing wedge artifacts which can severely impact the accuracy of the reconstructed 3D images. The traditional methods of reconstruction, such as Filtered Back-projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT), and Model-Based Iterative Reconstruction (MBIR), are often not suitable for removing these artifacts effectively. Here, to address this challenge, we present a novel approach called MBIR with Artifact Reduction and Adaptive Regularization (MBIR-ARAR).

25 ENERGY STORAGE↗
DOE OSTI2023

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗
DOE OSTI2024

Cone beam neutron interferometry: From modeling to applications

Phase-grating moiré interferometers (PGMIs) have emerged as promising candidates for the next generation of neutron interferometry, enabling the use of a polychromatic beam and manifesting interference patterns that can be directly imaged by existing neutron cameras. However, the modeling of the various PGMI configurations is limited to cumbersome numerical calculations and backward propagation models which often do not enable one to explore the setup parameters. Here we generalize the Fresnel scaling theorem to introduce a k -space model for PGMI setups illuminated by a cone beam, thus enabling an intuitive forward propagation model for a wide range of parameters and experimental setups. The interference manifested by a PGMI is shown to be a special case of the Talbot effect, and the optimal fringe visibility is shown to occur at the moiré location of the Talbot distances. We derive analytical expressions for the contrast and the propagating intensity profiles in various conditions and provide the first analysis of the PGMI dark-field imaging signal when considering sample characterization. The model's predictions are compared to experimental measurements and good agreement is found between them. Last, we propose and experimentally verify a method to recover contrast at typically inaccessible PGMI autocorrelation lengths. The presented work provides a toolbox for analyzing and understanding existing PGMI setups and their future applications, for example extensions to two-dimensional PGMIs and characterization of samples with nontrivial structures. Published by the American Physical Society 2024

Sarenac, D. (ORCID:0000000185753367)↗