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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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101 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Imaging, understanding, and control of nanoscale materials transformations

The development of liquid cells for transmission electron microscopy has enabled breakthroughs in our ability to follow nanoscale structural, morphological, or chemical changes during materials growth and applications. Time-resolved high-resolution imaging and chemical analysis through liquids opened the opportunity to capture nanoscale dynamic processes of materials, including reaction intermediates and the transformation pathways. In this article, a series of work is highlighted with topics ranging from liquid cell developments to in situ studies of nanocrystal growth and transformations, dendrite formation, and suppression of lithium dendrites through in situ characterization of the solid–electrolyte interphase chemistry. The understanding garnered is expected to accelerate the discovery of novel materials for applications in energy storage, catalysis, sensors, and other functional devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Characterization of radiation damage in 3D printed SiC

The SiC fuel matrix for advanced gas-cooled high temperature reactors as part of the Transformational Challenge Reactor program serves as the fuel particle container structure, a barrier to fission gas release, and a heat transfer medium. Its performance is particularly important because the fuel matrix must demonstrate good structural stability and thermal behaviors. An additive manufacturing methodology combining a binder jet 3D printing process with chemical vapor infiltration (CVI) for the production of SiC was recently developed. In this study, post irradiation examination by transmission electron microscopy shows that defect accumulation within the printed particles is very similar to other forms of high-purity SiC. However, damage accumulation was not directly observed in the CVI matrix because black spot damage and dislocation loops are difficult to image within the nanoscale highly faulted CVI matrix and because interstitial defects may rapidly annihilate at the stacking faults. Therefore, electron energy loss spectroscopy (EELS) analysis was used to analyze defect swelling in both the printed particles and the CVI matrix. The EELS analysis helped reveal that the radiation-induced swelling in the CVI matrix is similar to that of the printed SiC particles. This work shows that 3D printed SiC has behavior that is comparable to SiC processed by other means and that 3D printing could serve as a suitable processing technique for high-purity SiC for nuclear applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Antiphase-Boundary-Engineered Domain Switching in a (110)-Oriented BiFeO 3 Film

A ferroelectric domain wall memory device exploits the presence (or absence) of domain walls as the basis for information storage. Although structural defects strongly influence ferroelectric domain wall nucleation and growth, this correlation is far from being fully understood. For example, a single defect can play opposing roles: it can act as a nucleation site to initiate domain switching or, conversely, serve as a pinning center inhibiting domain wall motion. This is particularly the case for antiphase boundaries (APBs), whose influence on switching remains relatively unexplored despite being ubiquitous in oxide perovskite ferroelectrics. Here, we use aberration-corrected scanning transmission microscopy and in situ transmission electron microscopy under an applied bias to extensively characterize the influence of an APB on the switching behavior in a (110)-oriented BiFeO 3 thin film. We demonstrate that deterministic nucleation occurs in the proximity of a vertically oriented APB, following which domain growth occurs laterally in a symmetric fashion. Atomic-scale structural analysis reveals that the shear operation vector for the APB is 1/2[110]; this half-unit-cell shift extends over a few nanometers, implying that the APB plane is inclined toward the imaging direction. The symmetric switching observation is attributed to local inhomogeneous lattice strain and a reduction of polarization caused by the APB. These results demonstrate that an extended structural defect can be used as an active switching element rather than a stumbling block in reprogrammable domain-wall-based devices. Ultimately, this will expand the capabilities of ferroelectric thin films for future electronic devices based on ferroelectric domain walls.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Soot-particle core-shell and fractal structures from small-angle X-ray scattering measurements in a flame

We have characterized soot particles measured in situ in a laminar co-flow ethylene-air diffusion flame using small-angle X-ray scattering (SAXS). The analysis includes temperature measurements made with coherent anti-Stokes Raman spectroscopy (CARS) and complements soot volume-fraction and maturity measurements made with laser-induced incandescence (LII). We compared the results of fits to the SAXS measurements using a unified model and a fractal core-shell model. Power-law parameters yielded by the unified model indicate that aggregates of primary particles are in the mass-fractal regime, whereas the primary particles are in the surface-fractal regime in the middle of the flame. Higher and lower in the flame, the primary-particle power-law parameter approaches 4, suggesting smooth primary particles. Furthermore, these trends are consistent with fits using the fractal core-shell model, which indicate that particles have an established core-shell structure in the middle of the flame and are internally homogeneous at higher and lower heights in the flame. Primary-particle size distributions derived using the fractal core-shell model demonstrate excellent agreement with distributions inferred from transmission electron microscopy (TEM) images in the middle of the flame. Higher in the flame, a second small mode appears in the size distributions, suggesting particle fragmentation during oxidation. Surface oxidation would explain (1) aggregate fragmentation and (2) loss of core-shell structure leading to smoother primary-particle surfaces by removal of carbon overlayers. SAXS measurements are much more sensitive to incipient and young soot particles than LII and demonstrate significant volume fraction from particles low in the flame where the LII signal is negligible.

42 ENGINEERING↗
DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

In Situ High-Temperature TEM Observation of Inconel Corrosion by Molten Chloride Salts with N 2 , O 2 , or H 2 O

Here, in situ transmission electron microscopy (TEM) diffraction and imaging techniques are used to monitor and quantify corrosion of Inconel-625 by pure molten chloride salts (MgCl 2 – NaCl – KCl) at 500 °C–800 °C in 1.0 atm inert N 2 or pure O2, or by salts which are controllably hydrated in a high vacuum chamber. The isothermal corrosion rate R in inert N 2 increases from 203 ± 30 μ m year –1 at 700 °C to 463 ± 30 μ m year –1 at 800 °C. An oxygen ambient causes a six-fold increase to R = 1261 ± 170 μ m year –1 at 700 °C. Salt hydration dramatically accelerates corrosion to R > 3 × 10 5 μ m year –1 at 700 °C while it leads to a more moderate R = 95 ± 20 and 486 ± 30 μ m year –1 at 500 °C and 600 °C, respectively. These isothermal corrosion rates indicate that the molten chloride corrosion is significantly accelerated by salt hydration at temperatures above 600 °C, where corrosion is aggravated by increased generation and solubility of corrosive HCl gases. Hence, to reduce rate of corrosion it is important to both avoid incorporation of H 2 O into the system at each stage and ensure proper flushing of the system before increasing the temperature beyond 600 °C. Compositional analysis of the corroded cells indicate that corrosion in O 2 ambient is dominated by oxidation of metals by O 2 gas dissolved in the chloride melt, but corrosion in H 2 O ambients is caused by chlorination of metals by dissolved HCl gas and MgOH + ions. So, to reduce rate of corrosion, steps should be taken to tailor chloride melt compositions that has low solubility for HCl and O 2 . All of our corroded samples exhibit passive-protective oxide layers of Cr, Mg, and Ni. In addition, distinct volatile compounds of Ni, Mo and Cr involving NiCl 2 , (Na,K) 2 MoO 4 and CrO 2 (OH) 2 are detected in N 2 , H 2 O, and O 2 ambients, respectively. We believe that corrosion acceleration can be minimized by minimizing formation of volatile by-products or promoting reactions that could convert these volatile compounds to solid phases, as these volatile compounds led to destruction of protective oxide layers.

14 SOLAR ENERGY↗
DOE OSTI2024

Thermal Transport and Mechanical Stress Mapping of a Compression Bonded GaN/Diamond Interface for Vertical Power Devices

Bonding diamond to the back side of gallium nitride (GaN) electronics has been shown to improve thermal management in lateral devices; however, engineering challenges remain with the bonding process and characterizing the bond quality for vertical device architectures. Here, in this study, integration of these two materials is achieved by room-temperature compression bonding centimeter-scale GaN and a diamond die via an intermetallic bonding layer of Ti/Au. Recent attempts at GaN/diamond bonding have utilized a modified surface activation bonding (SAB) method, which requires Ar fast atom bombardment immediately followed by bonding within the same tool under ultrahigh vacuum (UHV) conditions. The method presented here does not require a dedicated SAB tool yet still achieves bonding via a room-temperature metal–metal compression process. Imaging of the buried interface and the total bonding area is achieved via transmission electron microscopy (TEM) and confocal acoustic scanning microscopy (C-SAM), respectively. The thermal transport quality of the bond is extracted from spatially resolved frequency-domain thermoreflectance (FDTR) with the bonded areas boasting a thermal boundary conductance of >100 MW/m 2 ·K. Additionally, Raman maps of GaN near the GaN–diamond interface reveal a low level of compressive stress, <80 MPa, in well-bonded regions. FDTR and Raman were coutilized to map these buried interfaces and revealed some poor thermally bonded areas bordered by high-stress regions, highlighting the importance of spatial sampling for a complete picture of bond quality. Overall, this work demonstrates a novel method for thermal management in vertical GaN devices that maintains low intrinsic stresses while boasting high thermal boundary conductances.

Raman↗
DOE OSTI2021

Visualizing Intrinsic 3D-Strain Distribution in Gold Coated ZnO Microstructures by Bragg Coherent X-Ray Diffraction Imaging and Transmission Electron Microscopy with Respect to Piezotronic Applications

Novel devices ranging from bio magnetic field sensors to energy harvesting nano machines utilize the piezotronic effect. For optimal function, understanding the interaction of electrical and strain phenomena within the semiconductor crystal is necessary. Here, studies of a model piezotronic system are presented, consisting of a ZnO microrod coated by a thin layer of gold, which forms a Schottky contact with the piezoelectric ZnO material. Coherent X-ray diffraction imaging (CXDI) and transmission electron microscopy (TEM) are used to visualize the structure and strain distribution, showing that the ZnO microrod exhibits strains of multiple origins in the bulk and at the interface. Strain values of -6 × 10 -4 have been measured by CXDI at the ZnO/Au interface. The origin is shown to be a combination of an interface strain, possibly caused by the Schottky contact formation, and distinct, localized electrical fields inside the crystal which are assigned to electron depletion and screening in a bent ZnO/Au piezotronic rod. These findings will contribute to sensor development and to a better understanding of piezotronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network

Over the past half century, the transmission electron microscope enabled insight into the fundamental arrangements and structures of materials. State-of-the-art electron microscopes can acquire large image datasets across multiple imaging modalities. However, the manual annotation process for feature or defect quantification may not be feasible with the modern microscope. Convolutional neural networks emerged to characterize individual microstructural features from an image in a cost-effective, consistent manner. However, many of these neural network approaches rely on thousands to hundreds of thousands of manual annotations of each feature type across hundreds of images to train the network for adequate performance. This work focused on the development and application of a pixel-wise defect detection machine-learning dynamic segmentation convolutional neural network with associated automated acquisition and postprocessing to identify microstructural features rapidly and quantitatively from a small initial dataset incorporating multiple imaging modes. The approach was demonstrated for characterization of superalloy 718 from both single image acquisition on multiple detectors to in-situ evolution captured with a single detector on a standard desktop computer to demonstrate the low barrier to entry required for widespread adoption. Pixel-by-pixel class identification was excellent with strong identification of chemically distinct phases, structurally distinct phases, and defect structures, thus demonstrating the new paradigm of machine learning-assisted characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Measurement of G-phase volume fraction and number density in duplex stainless steels using transmission electron microscopy

Duplex stainless steels (DSS) have a high toughness and strength due the presence of both austenitic and ferritic phases. These alloys have had limited use in power production applications due to thermal embrittlement caused by spinodal decomposition and development of G-phase precipitates in the ferrite. Lean grade DSS alloys (e.g., 2101, 2003) may offer improved thermal stability due to the reduction of Cr- and Ni-equivalent elements when compared to standard grade compositions (e.g., 2205, 2209). The abundance of the G-phase was measured in five duplex stainless steels, three wrought alloys (2101, 2003, 2205) and their matching filler metals (2101-w, 2209-w), after aging at 427 °C for 1000 h and 10,000 h. The G-phase volume fraction, number density, size, and precipitate spacing were found using quantitative analysis of transmission electron microscopy dark field images and the composition of G-phase precipitates on other clusters were characterized with atom probe tomography (APT). In the welded alloys, the G-phase was found to develop rapidly, relative to the wrought material. A positive correlation was found between the nickel equivalent composition of the alloy and the G-phase volume fraction. The alloys 2205, 2209, and 2101-w, which are higher in Cr and Ni, all showed significant G-phase precipitation, further strengthening the hypothesis that lean grade DSS alloys are more thermally stable against precipitation in the ferrite. Electron diffraction showed a secondary phase present in the 2101 wrought alloy at 10,000 h, but it was not crystallographically consistent with the G-phase; APT showed the presence of nanoclusters rich in both nickel and copper for this alloy. In conclusion, no secondary phases or clusters were found in 2003 after 10,000 h of aging, so it may be a candidate alloy for applications that require long-life times at high operating temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Statistical analysis of HAADF-STEM images to determine the surface coverage and distribution of immobilized molecular complexes

The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to design improved catalytic systems. Here, in this work, we demonstrate that the combination of scanning transmission electron microscopy (STEM) and image analysis of the individual positions of heavy atoms in transition metal complexes via a convolutional neural network (CNN) allows statistically robust determination of the surface coverage and distribution of immobilized molecular catalysts. These observations provide information about how changes in the functionalization conditions, attachment group, and structure of the molecular catalyst affect the surface coverage and distribution, providing insight into the chemical mechanism of surface immobilization. The method could be generally valuable for correlating the surface coverage and distribution to the activity, selectivity, and stability of a catalytic system.

HAADF-STEM↗