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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Defect-mediated ripening of core-shell nanostructures

Abstract Understanding nanostructure ripening mechanisms is desirable for gaining insight on the growth and potential applications of nanoscale materials. However, the atomic pathways of nanostructure ripening in solution have rarely been observed directly. Here, we report defect-mediated ripening of Cd-CdCl 2 core-shell nanoparticles (CSN) revealed by in-situ atomic resolution imaging with liquid cell transmission electron microscopy. We find that ripening is initiated by dissolution of the nanoparticle with an incomplete CdCl 2 shell, and that the areas of the Cd core that are exposed to the solution are etched first. The growth of the other nanoparticles is achieved by generating crack defects in the shell, followed by ion diffusion through the cracks. Subsequent healing of crack defects leads to a highly crystalline CSN. The formation and annihilation of crack defects in the CdCl 2 shell, accompanied by disordering and crystallization of the shell structure, mediate the ripening of Cd-CdCl 2 CSN in the solution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Imaging atomic-scale chemistry from fused multi-modal electron microscopy

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR) recovery of material chemistry at nano- and atomic-resolution by coupling correlated information encoded within both elastic scattering (high-angle annular dark-field (HAADF)) and inelastic spectroscopic signals (electron energy loss (EELS) or energy-dispersive x-ray (EDX)). By linking these simultaneously acquired signals, or modalities, the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector hardware. In many cases, the dose requirements can be reduced by over one order of magnitude. This high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Stratification of fluoride uptake among enamel crystals with age elucidated by atom probe tomography

Dental enamel is subjected to a lifetime of de- and re-mineralization cycles in the oral environment, the cumulative effects of which cause embrittlement with age. However, the understanding of atomic scale mechanisms of dental enamel aging is still at its infancy, particularly regarding where compositional differences occur in the hydroxyapatite nanocrystals and what underlying mechanisms might be responsible. Here, we use atom probe tomography to compare enamel from a young (22 years old) and a senior (56 years old) adult donor tooth. Findings reveal that the concentration of fluorine is elevated in the shells of senior nanocrystals relative to young, with less significant differences between the cores or intergranular phases. It is proposed that the embrittlement of enamel is driven, at least in part, by the infusion of fluorine into the nanocrystals and that the principal mechanism is de- and re-mineralization cycles that preferentially erode and rebuild the nanocrystals shells.

36 MATERIALS SCIENCE↗
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 OSTI2024

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗
DOE OSTI2024

Discovering invariant spatial features in electron energy loss spectroscopy images on the mesoscopic and atomic levels

Over the last two decades, Electron Energy Loss Spectroscopy (EELS) imaging with a scanning transmission electron microscope has emerged as a technique of choice for visualizing complex chemical, electronic, plasmonic, and phononic phenomena in complex materials and structures. The availability of the EELS data necessitates the development of methods to analyze multidimensional data sets with complex spatial and energy structures. Traditionally, the analysis of these data sets has been based on analysis of individual spectra, one at a time, whereas the spatial structure and correlations between individual spatial pixels containing the relevant information of the physics of underpinning processes have generally been ignored and analyzed only via the visualization as 2D maps. Here, we develop a machine learning-based approach and workflows for the analysis of spatial structures in 3D EELS data sets using a combination of dimensionality reduction and multichannel rotationally invariant variational autoencoders. This approach is illustrated for the analysis of both the plasmonic phenomena in a system of nanowires and in the core excitations in functional oxides using low loss and core-loss EELS, respectively. The code developed in this manuscript is open sourced and freely available and provided as a Jupyter notebook for the interested reader.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Barrierless nucleation in glassy precursors drives zeolite formation

Zeolites are crystalline, microporous silicates widely used in catalysis and separations, yet the molecular mechanisms of their formation remain unresolved. Experiments indicate that hydrothermal synthesis of silica zeolites from clear solution proceeds through amorphous nanoaggregates that gradually develop zeolite order in an apparently continuous amorphous to crystal transformation. Here, we combine molecular simulations with advanced algorithms that identify zeolite order and computer vision to elucidate the pathway from clear solution to zeolite nanocrystal. We show that at conditions of hydrothermal synthesis of silica zeolites, the transformation of precursor aggregate into zeolite is not limited by nucleation barriers but by the slow dynamics of reorganization in the glassy precursor matrix. The negligible nucleation barriers result in spinodal-like crystallization that leads to a gradual formation of a mosaic of small crystallites that explain the seemingly continuous character of zeolite crystallization and the catalytic activity of X-ray amorphous, protozeolites and embryonic zeolites. We find that zeolite-like porosity and short-range order emerge early within glassy precursors, well before crystallinity is detected in transmission electron microscopy (TEM) images or X-ray diffraction. The nanoaggregate’s temperature-size phase diagram reveals a convergence of the zeolite–amorphous equilibrium and maximum crystallization rate at ~3 nm diameter nanoparticle diameters and ~200 °C. This convergence signals the termination of the first-order amorphous-to-zeolite transition. Our results provide a unifying framework for understanding nucleation of silica zeolites from solution and suggest that barrierless nucleation may govern the formation of other nanoparticle systems, including minerals and oxides synthesized far below their bulk melting points.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Fast widefield imaging of neuronal structure and function with optical sectioning in vivo

Optical microscopy, owing to its noninvasiveness and subcellular resolution, enables in vivo visualization of neuronal structure and function in the physiological context. Optical-sectioning structured illumination microscopy (OS-SIM) is a widefield fluorescence imaging technique that uses structured illumination patterns to encode in-focus structures and optically sections 3D samples. However, its application to in vivo imaging has been limited. In this study, we optimized OS-SIM for in vivo neural imaging. We modified OS-SIM reconstruction algorithms to improve signal-to-noise ratio and correct motion-induced artifacts in live samples. Incorporating an adaptive optics (AO) module to OS-SIM, we found that correcting sample-induced optical aberrations was essential for achieving accurate structural and functional characterizations in vivo. With AO OS-SIM, we demonstrated fast, high-resolution in vivo imaging with optical sectioning for structural imaging of mouse cortical neurons and zebrafish larval motor neurons, and functional imaging of quantal synaptic transmission at Drosophila larval neuromuscular junctions.

42 ENGINEERING↗
DOE OSTI2022

Twin-free, directly synthesized MFI nanosheets with improved thickness uniformity and their use in membrane fabrication

Zeolite nanosheets can be used for the fabrication of low-defect-density, thin, and oriented zeolite separation membranes. However, methods for manipulating their morphology are limited, hindering progress toward improved performance. We report the direct synthesis (i.e., without using exfoliation, etching, or other top-down processing) of thin, flat MFI nanosheets and demonstrate their use as high-performance membranes for xylene isomer separations. Our MFI nanosheets were synthesized using nanosheet fragments as seeds instead of the previously used MFI nanoparticles. The obtained MFI nanosheets exhibit improved thickness uniformity and are free of rotational and MEL intergrowths as shown by transmission electron microscopy (TEM) imaging. The nanosheets can form well-packed nanosheet coatings. Upon gel-free secondary growth, the obtained zeolite MFI membranes show high separation performance for xylene isomers at elevated temperature (e.g., p-xylene flux up to 1.5 × 10 –3 mol m –2 s –1 and p-/o-xylene separation factor of ~600 at 250°C).

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

GraphEM

An unsupervised segmentation method for structural analysis of Scanning Transmission Electron Microscopy (STEM) images

Pope, Jenna↗
DOE OSTI2020

Nucleation, growth, and superlattice formation of nanocrystals observed in liquid cell transmission electron microscopy

This work reviews the advancements and prospects of liquid cell transmission electron microscopy (TEM) imaging and analysis methods in understanding the nucleation, growth, etching, and assembly dynamics of nanocrystals. The bonding of atoms into nanoscale crystallites produces materials with nonadditive properties unique to their size and geometry. The recent application of in situ liquid cell TEM to nanocrystal development has initiated a paradigm shift, (1) from trial-and-error synthesis to a mechanistic understanding of the “synthetic reactions” responsible for the emergence of crystallites from a disordered soup of reactive species (e.g., ions, atoms, molecules) and shape-defined growth or etching; and (2) from post-processing characterization of the nanocrystals’ superlattice assemblies to in situ imaging and mapping of the fundamental interactions and energy landscape governing their collective phase behaviors. Imaging nanocrystal formation and assembly processes on the single-particle level in solution immediately impacts many existing fields, including materials science, nanochemistry, colloidal science, biology, environmental science, electrochemistry, mineralization, soft condensed-matter physics, and device fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves

A thorough understanding of the neuroanatomy of peripheral nerves is required for a better insight into their function and the development of neuromodulation tools and strategies. In biophysical modeling, it is commonly assumed that the complex spatial arrangement of myelinated and unmyelinated axons in peripheral nerves is random, however, in reality the axonal organization is inhomogeneous and anisotropic. Present quantitative neuroanatomy methods analyze peripheral nerves in terms of the number of axons and the morphometric characteristics of the axons, such as area and diameter. In this study, we employed spatial statistics and point process models to describe the spatial arrangement of axons and Sinkhorn distances to compute the similarities between these arrangements (in terms of first- and second-order statistics) in various vagus and pelvic nerve cross-sections. We utilized high-resolution transmission electron microscopy (TEM) images that have been segmented using a custom-built high-throughput deep learning system based on a highly modified U-Net architecture. Our findings show a novel and innovative approach to quantifying similarities between spatial point patterns using metrics derived from the solution to the optimal transport problem. We also present a generalizable pipeline for quantitative analysis of peripheral nerve architecture. Our data demonstrate differences between male- and female-originating samples and similarities between the pelvic and abdominal vagus nerves.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Advanced Instrumentation for Metal Additive Manufacturing

Laser powder bed fusion (LPBF) is the most widely used process for metal additive manufacturing (AM), particularly where complex geometries provide performance advantages unattainable with traditional manufacturing techniques. However, LPBF is highly sensitive to innate variability in both the powder spreading and fusion steps, often leading to defects such as pores that are difficult to detect yet significantly impair component mechanical properties and fatigue life. This thesis presents a range of novel instruments enabling both precise assessment of powder layer characteristics and in-situ thermal metrology of metal AM to advance the quality control of LPBF. First, leveraging a custom X-ray microscope and a radiation-transport model developed through this work, transmission X-ray imaging is used to study spreading of thin metal powder layers. Effective layer depth is directly mapped at a process-relevant size scale, surpassing optical techniques that can only estimate local deposition from layer surface topography. Layer packing density and quality are shown to be influenced by powder flowability and particle size relative to nominal powder layer thickness. Layer quality is additionally connected to the geometry of the spreading implement and its velocity. This technique and its presented findings enable pairing feedstocks with spreading strategies that create layers with consistent packing density and uniformity. Second, a twofold approach is employed to optically interrogate the laser fusion step of LPBF for observing signatures of defect formation. Aperture division multiplexing is conceptualized, providing for simultaneous laser delivery and high-fidelity infrared (IR) process monitoring through a common optic. In-situ microscopy at 50 μm spatial resolution and at mid-wave IR wavelengths is proven readily achievable with the first purpose-built optic of this type. Next, a bespoke imaging spectrometer, along with a temperature-emissivity separation technique, is used to retrieve accurate process temperatures over a 1000 K range. Data from these instruments are correlated to porosity as fine as 4.3 μm in two LPBF test artifacts, as verified using computed tomography (CT), establishing the viability of robust optically-based component qualification.

Penny, Ryan↗
DOE OSTI2025

Experimental study of energy-dependent angular broadening of MeV electron beams for high-resolution imaging in thick samples

In scanning transmission electron microscopy (STEM), spatial resolution is primarily influenced by the projected size of the electron probe within the specimen. In thin samples, a large semi-convergence angle enables a tightly focused beam and sub-nanometer resolution. However, in thick specimens, resolution is fundamentally limited by transverse beam broadening from multiple large-angle scattering events—for example, a probe with 10 mrad angular divergence can broaden by ∼100 nm over a 10 μm path. Since this broadening scales inversely with beam energy, MeV-STEM offers a promising route for high-resolution imaging in thick materials. To quantitatively assess this effect, we performed high-precision measurements at UCLA’s PEGASUS beamline, characterizing beam divergence and intensity profiles for 3–8 MeV electrons transmitted through a wedged-silicon sample of varying thickness. Our results reconcile discrepancies among analytical models and validate Monte Carlo simulations. Here, we find that increasing beam energy from 3.0 to 5.8 MeV reduces angular broadening by a factor of 2.6, with diminishing returns observed at 7.6 MeV. These findings provide a quantitative framework for optimizing MeV-STEM parameters in high-resolution imaging of thick biological and microelectronic specimens, and for guiding beam energy selection in other advanced imaging modes beyond STEM.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Versatile compact heater design for in situ nano-tomography by transmission X-ray microscopy

A versatile, compact heater designed at National Synchrotron Light Source-II for in situ X-ray nano-imaging in a full-field transmission X-ray microscope is presented. Heater design for nano-imaging is challenging, combining tight spatial constraints with stringent design requirements for the temperature range and stability. Finite-element modeling and analytical calculations were used to determine the heater design parameters. Performance tests demonstrated reliable and stable performance, including maintaining the exterior casing close to room temperature while the heater is operating at above 1100°C, a homogenous heating zone and small temperature fluctuations. Two scientific experiments are presented to demonstrate the heater capabilities: (i) in situ 3D nano-tomography including a study of metal dealloying in a liquid molten salt extreme environment, and (ii) a study of pore formation in icosahedral quasicrystals. The progression of structural changes in both studies were clearly resolved in 3D, showing that the new heater enables powerful capabilities to directly visualize and quantify 3D morphological evolution of materials under real conditions by X-ray nano-imaging at elevated temperature during synthesis, fabrication and operation processes. This heater design concept can be applied to other applications where a precise, compact heater design is required.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Measurement of Thomson-scattering spectra with continuous angular resolution (invited)

Here, a novel Thomson-scattering diagnostic with continuous angular resolution over a span of 120° was developed for the characterization of plasmas produced at the Omega Laser Facility. Spectrally resolving light scattered from electron plasma wave features as a function of emission angle provides a means to efficiently probe a large range of plasma frequencies and k vectors. Together, these spectra contain critical constraints on the plasma-physics models used to interpret the data and enable experimental measurements of the electron-velocity distribution function over several orders of magnitude without assumptions about its mathematical form. Major components of the instrument include (1) a reflective collection objective that gathers light over a range of 120° × 12°; (2) a spatial-filter image relay for measurement localization; (3) cylindrical optics for producing a line image of the collection aperture; (4) a transmission grating spectrometer; and (5) a time-gated, image-intensified camera. Thomson-scattered light collected from an ~(50 – μM) 3 volume of plasma is recorded with 0.8-nm spectral and 1° angular resolution. Initial experiments examined the properties of the electron-velocity distribution in gas-jet-produced plasmas in the presence of heating via inverse bremsstrahlung absorption.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Semi-Automated, Object-Based Tomography of Dislocation Structures

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.

47 OTHER INSTRUMENTATION↗