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At least 1,675 records · Page 93

The Convolutional Multiple Whole Profile (CMWP) Fitting Method, a Global Optimization Procedure for Microstructure Determination

The analysis of line broadening in X-ray and neutron diffraction patterns using profile functions constructed on the basis of well-established physical principles and TEM observations of lattice defects has proven to be a powerful tool for characterizing microstructures in crystalline materials. These principles are applied in the convolutional multiple-whole-profile (CMWP) procedure to determine dislocation densities, crystallite size, stacking fault and twin boundary densities, and intergranular strains. The different lattice defect contributions to line broadening are separated by considering the hkl dependence of strain anisotropy, planar defect broadening and peak shifts, and the defect dependent profile shapes. The Levenberg–Marquardt (LM) peak fitting procedure can be used successfully to determine crystal defect types and densities as long as the diffraction patterns are relatively simple. However, in more complicated cases like hexagonal materials or multiple-phase patterns, using the LM procedure alone may cause uncertainties. Here, we extended the CMWP procedure by including a Monte Carlo statistical method where the LM and a Monte Carlo algorithm were combined in an alternating manner. The updated CMWP procedure eliminated uncertainties and provided global optimized parameters of the microstructure in good correlation with electron microscopy methods.

36 MATERIALS SCIENCE↗

Development and Optical Testing of the Camera, Hand Lens, and Microscope Probe with Scannable Laser Spectroscopy (CHAMP-SLS)

Conducting high resolution field microscopy with coupled laser spectroscopy that can be used to selectively analyze the surface chemistry of individual pixels in a scene is an enabling capability for next generation robotic and manned spaceflight missions, civil, and military applications. In the laboratory, we use a range of imaging and surface preparation tools that provide us with in-focus images, context imaging for identifying features that we want to investigate at high magnification, and surface-optical coupling that allows us to apply optical spectroscopic analysis techniques for analyzing surface chemistry particularly at high magnifications. The camera, hand lens, and microscope probe with scannable laser spectroscopy (CHAMP-SLS) is an imaging/spectroscopy instrument capable of imaging continuously from infinity down to high resolution microscopy (resolution of approx. 1 micron/pixel in a final camera format), the closer CHAMP-SLS is placed to a feature, the higher the resultant magnification. At hand lens to microscopic magnifications, the imaged scene can be selectively interrogated with point spectroscopic techniques such as Raman spectroscopy, microscopic Laser Induced Breakdown Spectroscopy (micro-LIBS), laser ablation mass-spectrometry, Fluorescence spectroscopy, and/or Reflectance spectroscopy. This paper summarizes the optical design, development, and testing of the CHAMP-SLS optics.

Fluorescence↗

A complete grain-level assessment of the stress-strain evolution and associated deformation response in polycrystalline alloys

Polycrystalline alloys are used pervasively across structural applications contingent upon extensive experimental testing. A statistically representative number of tests are required to expose the variability in the material's performance, as a result of non-uniform microstructures and associated micromechanical fields. In a more direct means of capturing this pertinent information, multi-modal experimental techniques are presented to measure and track the complete micromechanical state, evolving during loading, of each and every grain within the regions of interest. Specifically, a combination of high-energy X-ray diffraction microscopy and digital image correlation coupled with electron backscatter diffraction are conducted on a specimen for each of the alloys, Haynes 282 and Ti7Al. The results of the multi-modal analysis definitively demonstrate that the degree of heterogeneity increases with deformation level and is used to assess the number of grains necessary for a representative volume element description of the stress state for each of these materials. Moreover, higher resolution imaging is used for identification of the slip system activity and subsequently used to study slip transmission events. An accurate knowledge of the resolved shear stress in adjacent grains (grain interactions) is demonstrated to be a key descriptor of the slip transmission events.

36 MATERIALS SCIENCE↗

Optical and Structural Properties of High-Efficiency Epitaxial Cu(In,Ga)Se 2 Grown on GaAs

Photovoltaic devices based on Cu(In,Ga)Se 2 (CIGS) usually employ polycrystalline thin films as the absorber layer. This is because, to date, the highest conversion efficiencies have been attained with polycrystalline CIGS films. Recently, Nishinaga et al. presented an epitaxial CIGS thin-film solar cell grown on a GaAs (100) substrate with a conversion efficiency of 20.0%. In this contribution, we study the optical and structural properties of this high-efficiency epitaxial film, along with others with different compositions using cathodoluminescence spectrum imaging and transmission electron microscopy. A comparison of the high-efficiency epitaxial film and a traditional polycrystalline film with a similar global composition reveals significant differences in microstructure and uniformity of emission properties despite similar performance. The analysis of epitaxial films with a higher gallium concentration indicates that the emission characteristics and nature of extended defects in epitaxial CIGS films are strongly dependent on the gallium content. The results presented here provide evidence that, with further optimization, photovoltaic conversion efficiencies of epitaxial CIGS films could exceed those of polycrystalline CIGS.

14 SOLAR ENERGY↗

Data Mining – Image Analysis of Radiography for Zr Redistribution

The research effort described in this report represents a first attempt to investigate the radial redistribution of Zr in ternary fuel alloys U-xPu-10Zr (x = 0, 8, 19) irradiated in the in-reactor fuel experiments during the operation of the U.S. Department of Energy’s (DOE’s) Experimental Breeder Reactor II (EBR-II) at Idaho National Laboratory (INL) using methods of image processing on post-irradiation neutron radiographs. Approximately 130,000 metal fuel pins were irradiated in EBR-II during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed historically now allowing application of modern image analysis techniques to characterize fuel behavior, such as fuel swelling, fluff formation, and now, fuel alloy constituent redistribution. The redistribution of fuel components depends on the temperature field, radially, within the fuel. Specifically, Zr is expected to redistribute radially towards the center of the pin, as well as towards the outer zones. Currently, direct imaging of a pin cross-section through optical methods or scanning electron microscopy (SEM) is used to study the constituents’ redistribution, which is very time-consuming and can only be applied to a limited number of pins. An automated image processing technique allowing for the investigation of fuel radial redistribution zones would significantly accelerate data analysis. In general, if the fuel temperature is hot enough, three redistribution zones are expected, corresponding to the main fuel components (e.g., U, Pu, Zr). While more assessment will be performed in fiscal year (FY)-2023, it seems possible to differentiate the pins according to their fuel composition using image analysis techniques on neutron radiographs of metallic fuel pins based on the analysis to date.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

TEM Analysis of Interfaces in Diffusion-Bonded Silicon Carbide Ceramics Joined Using Metallic Interlayers

Silicon Carbide (SiC) is a promising material for thermo-structural applications due to its excellent high-temperature mechanical properties, oxidation resistance, and thermal stability. However, joining and integration technologies are indispensable for this material in order to fabricate large size and complex shape components with desired functionalities. Although diffusion bonding techniques using metallic interlayers have been commonly utilized to bond various SiC ceramics, detailed microstructural observation by Transmission Electron Microscopy (TEM) of the bonded area has not been carried out due to difficulty in preparing TEM samples. In this study, we tried to prepare TEM samples from joints of diffusion bonded SiC ceramics by Focused Ion Beam (FIB) system and carefully investigated the interfacial microstructure by TEM analysis. The samples used in this study were SiC fiber bonded ceramics (SA-Tyrannohex: SA-THX) diffusion bonded with metallic interlayers such as Ti, TiMo, and Mo-B. In this presentation, the result of microstructural analysis obtained by TEM observations and the influence of metallic interlayers and fiber orientation of SA-THX on the joint microstructure will be discussed.

Silicon Carbide↗

Experiment 1: Orbital Processing of High-Quality Zn-Alloyed CdTe Compound Semiconductors

Zinc-alloyed cadmium telluride (Zn:CdTe) crystals were grown in unit gravity and in microgravity for comparative analysis. Two crystals were grown on USML-1/STS-50 in 1992, and two additional crystals were grown on USML-2/STS-73 in 1995. The Crystal Growth Furnace (CGF) in the seeded Bridgman-Stockbarger crystal growth geometry was utilized on both missions. Crystals grown on USML-1/STS-50 were found to have solidified with partial wall contact due to the near-absence of the hydrostatic pressure in microgravity, a residual g-vector that was not axial, and the nonwetting sample/ampoule wetting conditions. Crystals grown on USML-2/STS-73 included: a sample/ampoule identical to the USML-1/STS-73 sample/ampoule, with the addition of a restraining spring to simulate hydrostatic pressure internally, and a tapered ampoule which accomplished 2.2 cm of crystal growth without wall contact. Infrared transmission of all ground and flight samples was found to be 63-66 percent, very close to the theoretical 66 percent, suggesting good stoichiometric control. Infrared microscopy confirmed that the primary precipitates were Te and their size (1-10 microns) and density suggested that the flight- and ground-base samples experienced similar thermal histories. Longitudinal macrosegregation, calculated using scaling analysis, was predicted to be low. Nearly diffusion controlled growth was achieved even in unit gravity and macrosegregation data could be fit with a diffusion controlled model. Radial segregation was monitored and was found to vary with fraction solidified, particularly through the shoulder region, where the sample cross section was varying significantly. It was also disturbed in the flight samples in regions where asymmetric wall contact was noted. In regions where a steady state was established, the radial segregation was invariant within our experimental measurement error. Flight samples were found to be much higher in structural perfection than samples processed in unit gravity under identical growth conditions. In regions where solidification had occurred without wall contact, the free surfaces evidenced virtually no twinning, although twins appeared in the flight samples in regions of wall contact and were pervasive in the ground samples. These results were confirmed using optical microscopy and synchrotron x-ray white beam topography. Full-width half-maximum rocking curve widths (FWHM), recorded in arc-seconds, were significantly reduced from 20 a-s (1 g) to 9 a-s (micro-g) for the best regions of the crystals. The 9 a-s (FWHM) rocking curve value in the unconfined flight samples equals the best value reported terrestrially for this material. The ground samples exhibited a fully developed (111)[110] dislocation mosaic structure, whereas dislocations within the flight samples were discrete and no mosaic structure was evident. The defect density was quantitatively reduced from 75,000 (1 g) to 800 (micro-g) +/-50 percent. Dislocation etch pit density results were confirmed using transmission synchrotron white beam and monochromated beam topography. The low defect density is thought to have resulted from the near absence of hydrostatic pressure, which allowed the molten boule to solidify with little or no wall contact. This minimized the transfer of hoop stresses during solidification and post-solidification processing.

Larson, D. J., Jr.↗

Microchemical Analysis Of Space Operation Debris

Report discusses techniques used in analyzing debris relative to space shuttle operations. Debris collected from space shuttle, expendable launch vehicles, payloads carried by space shuttle, and payloads carried by expendable launch vehicles. Optical microscopy, scanning electron microscopy with energy-dispersive spectrometry, analytical electron microscopy with wavelength-dispersive spectrometry, and X-ray diffraction chosen as techniques used in examining samples of debris.

Cummings, Virginia J.↗

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Trifan, Anda↗

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗

La 2 ⁢O 3 ⁢Mn 2 ⁢Se 2 : A correlated insulating layered d-wave altermagnet

Altermagnets represent a new class of magnetic phases without net magnetization, invariant under a combination of rotation and time reversal. Unlike conventional collinear antiferromagnets (AFM), altermagnets could lead to new correlated states and important material properties deriving from their nonrelativistic spin-split band structure. Indeed, they serve as the magnetic analogue of unconventional superconductors and can yield spin-polarized electrical currents in the absence of external magnetic fields, making them promising candidates for next-generation spintronics. Here, we report altermagnetism in the correlated insulator, magnetically ordered tetragonal oxychalcogenide, L⁢a 2 ⁢O 3⁢ M⁢n 2 ⁢S⁢e 2 . Symmetry analysis reveals a 𝑑 𝑥 2 −𝑦 2 -wave-like spin-momentum locking arising from the M⁢n 2 ⁢O Lieb lattice, supported by density functional theory (DFT) calculations. Magnetic measurements confirm the AFM transition below ∼166K while neutron pair distribution function analysis reveals a 2D short-range magnetic order that persists above the Néel temperature. Single crystals are grown and characterized using x-ray diffraction, optical and electron microscopy, and micro-Raman spectroscopy to confirm the crystal structure, stoichiometry, and uniformity. Furthermore, our findings establish L⁢a 2⁢ O 3 ⁢M⁢n 2⁢ S⁢e 2 as a model altermagnetic system realized on a Lieb lattice.

36 MATERIALS SCIENCE↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗

Grain Boundary Plane Measurement Using Transmission Electron Microscopy Automated Crystallographic Orientation Mapping for Atom Probe Tomography Specimens

Abstract Grain boundaries are critical in determining the properties of materials, including mechanical stability, conductivity, and corrosion resistance. The specific properties of materials depend not only on the misorientation of the crystals, the three most commonly characterized parameters, but also on the angle of the grain boundary plane between the two crystals, the final two parameters in the five-parameter macroscopic description of the grain boundary. The method presented here allows for the direct measurement of all five parameters of the grain boundary in a transmission electron microscopy specimen of various morphologies. This is especially applicable to atom probe specimens, where only a single-tilt axis is generally available, allowing the crystallographic description to be matched to the detailed chemical data available in the atom probe tomography. This method provides a platform for efficient grain boundary analysis in unique samples, saving operator time and allowing for ease of acquisition and interpretation in comparison with traditional electron diffraction methods.

Materials Science↗

Toward a high-voltage fast-charging pouch cell with TiO 2 cathode coating and enhanced battery safety

Nickel-rich layered lithium transition metal oxides, LiNi x Co y Mn 1-x-y O 2 , are key cathode materials for high-energy lithium-ion batteries owing to their high specific capacity. However, the commercial deployment of nickel-rich oxides has been hampered by their poor thermostability and insufficient cycle life. In this work full batteries with uncoated and TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathodes and graphite anodes are compared in terms of electrochemical performance and safety behavior. The battery using a TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode exhibited better cyclic performance at high cutoff voltage. Electrochemical impedance spectroscopy analysis indicated that the TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode gave the battery a more stable charge transfer resistance. Transmission electron microscopy demonstrated that TiO 2 coating reduced accumulation of the cathode electrolyte interface layer on the particle surface. Time-of-flight secondary ion mass spectrometry demonstrated that TiO 2 coating markedly enhanced the interface stability of the cathode particle and protected the particle from serious etching by the electrolyte. Accelerating rate calorimetry revealed that the trigger temperature of thermal runaway for the battery using TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 as cathode material was 257 °C, which was higher than that of the battery with the uncoated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode (251 °C). In situ X-ray diffraction during heating demonstrated that this enhanced safety can be attributed to the suppressed phase evolution of the coated cathode material.

25 ENERGY STORAGE↗

A study of real-world micrograph data quality and machine learning model robustness

Abstract Machine-learning (ML) techniques hold the potential of enabling efficient quantitative micrograph analysis, but the robustness of ML models with respect to real-world micrograph quality variations has not been carefully evaluated. We collected thousands of scanning electron microscopy (SEM) micrographs for molecular solid materials, in which image pixel intensities vary due to both the microstructure content and microscope instrument conditions. We then built ML models to predict the ultimate compressive strength (UCS) of consolidated molecular solids, by encoding micrographs with different image feature descriptors and training a random forest regressor, and by training an end-to-end deep-learning (DL) model. Results show that instrument-induced pixel intensity signals can affect ML model predictions in a consistently negative way. As a remedy, we explored intensity normalization techniques. It is seen that intensity normalization helps to improve micrograph data quality and ML model robustness, but microscope-induced intensity variations can be difficult to eliminate.

36 MATERIALS SCIENCE↗

Exploring the phase space of Zn 2 SbN 3 , a novel semiconducting nitride

The novel semiconductor Zn 2 SbN 3 is one of a growing list of ternary nitrides with promise for optoelectronic and energy applications. Previous work by Arca et al. [Materials Horizons, 2019, 6, 1669–1974] first reported synthesis of this material, but did not explore the effects of growth conditions on material formation. In this work, we present a semi-automated study of the relationship between growth conditions and crystallinity via high-throughput RF sputtering and a custom X-ray diffraction analysis routine. Zn 2 SbN 3 is found to crystallize in a wide range of growth conditions, and the formation of several contaminant phases is examined. Electron microscopy of these secondary phases, caused both by off-stoichiometry and by growth conditions, provides insight into the growth mechanisms of Zn 2 SbN 3 . Furthermore, computational work relates this material to other Zn-based ternary nitrides and offers an explanation for the difficulty of growing cation-ordered material despite the wide range of growth conditions explored.

36 MATERIALS SCIENCE↗

Chemical imaging of individual stratospheric particles sampled over North America

The increasing size, severity, and frequency of wildfires have led to dramatic increases in particulate matter concentrations in the troposphere. Severe wildfires can generate intense convective systems capable of transporting large quantities of biomass burning organic aerosols (BBOA) to the upper troposphere and lower stratosphere (UTLS). Chemically complex organic matter and light-absorbing carbonaceous material is introduced into stratospheric regions that were historically isolated from direct surface emissions. In this study, stratospheric particles were sampled over North America during the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) campaign, an aircraft-based research project designed to characterize convective perturbation in the UTLS. Particle samples collected from six research flights during summer 2022 were analyzed using Computer-Controlled Scanning Electron Microscopy and Scanning Transmission X-ray Microscopy to investigate particle size distributions, morphology, chemical composition, and mixing state of stratospheric particles along transects across the continental United States and adjacent Pacific Ocean airspace. Analysis revealed that all sampled particles contained detectable levels of carbon, with most exhibiting organic volume fractions of 0.37 ± 0.20. Notably, about 5% of the particles also contained soot inclusions, which indicates the presence of refractory black carbon transported to stratospheric altitudes and provides direct evidence of wildfire-derived black carbon reaching the UTLS. Typical particle morphology exhibits organic shells over soot and inorganic cores and suggests secondary processing and aging of BBOA during transport to and within the UTLS. These findings provide compelling evidence that wildfire emissions play a critical role in affecting the long-term composition and radiative properties of stratospheric particles.

Sharpe, Steven [Purdue Univ., West Lafayette, IN (↗

Terahertz near-field imaging of sidewall-induced losses in superconducting qubits

Correlating superconducting qubit performance with advanced materials analysis is a key strategy for improving coherence. Existing diagnostics for key properties, such as dielectric loss, structural discontinuity, and interface heterogeneity, often rely on destructive electron microscopy or low-throughput millikelvin measurements. Here, in this study, we demonstrate noninvasive terahertz (THz) nano-imaging/spectroscopy of encapsulated niobium transmon qubits as a high-throughput proxy for performance evaluation. We identify large variations in sidewall near-field signals, implicating sidewall loss and discontinuity as major coherence limiters, and also use THz hyperspectral line scans to probe dielectric responses and field participation at Al junction interfaces.

Kim, Richard H. J. [Ames Laboratory (AMES), Ames, ↗