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Results for “crystallographic defects”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Correlations of crystallographic defects and anisotropy with magnetotransport properties in Fe x TaS 2 single crystals ( 0.23 ≤ x ≤ 0.35 )

Very large magnetoresistance discovered in single crystals of the ferromagnetic Fe-intercalated transition metal dichalcogenide, Fe 0.28 TaS 2 was attributed to the deviation of the Fe concentration from commensurate values (x = 1/4 or 1/3), which caused magnetic moment misalignments. Here we report a study of Fe x TaS 2 crystals with 0:23 ≤ x ≤ 0:35, demonstrating that crystallographic defects lead to spin disorder, which correlates with magneto-transport properties such as switching magnetic fi eld HS, magnetoresistance MR, and even zero-field resistivity ρ0 and temperature coefficient A in ρ(T) = ρ 0 + AT 2 : The ordering temperature T C and Weiss temperature θ W are maximized at the superstructure composition x = 1/4, while H s , MR, ρ 0 , and A are minimum. Conversely, at a composition intermediate between the superstructure compositions x = 1/4 and 1/3, the corresponding magneto-transport properties reach local maxima.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels

Crystalline materials exhibit long-range ordered lattice unit, within which resides nonperiodic structural features called defects. These crystallographic defects play a vital role in determining the physical and mechanical properties of a wide range of material systems. While computer vision has demonstrated success in recognizing feature patterns in images with well defined contrast, automated identification of nanometer scale crystallographic defects in electron micrographs governed by complex contrast mechanism is still a challenging task. Here, building upon an advanced defect imaging mode that offers high feature clarity, we introduce DefectSegNet - a new convolutional neural network (CNN) architecture that performs semantic segmentation of three common crystallographic defects in structural alloys: dislocation lines, precipitates and voids. Results from supervised training of a small set of high-quality defect images of steels show high pixel-wise accuracy across all three types of defects: 91.60 ± 1.77% on dislocations, 93.39 ± 1.00% on precipitates, and 98.85 ± 0.56% on voids. We discuss the sources of uncertainties in CNN prediction, and the training data in terms of feature density, representation and homogeneity and their effects on deep learning performance. Further defect quantification using DefectSegNet prediction outperforms human expert average, presenting a promising new workflow for fast and statistically meaningful quantification of materials defects.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Charging Reactions Promoted by Geometrically Necessary Dislocations in Battery Materials Revealed by In Situ Single-Particle Synchrotron Measurements

Crystallographic defects exist in many redox active energy materials, e.g., battery and catalyst materials, which significantly alter their chemical properties for energy storage and conversion. However, there is lack of quantitative understanding of the interrelationship between crystallographic defects and redox reactions. Herein, crystallographic defects, such as geometrically necessary dislocations, are reported to influence the redox reactions in battery particles through single-particle, multimodal, and in situ synchrotron measurements. Through Laue X-ray microdiffraction, many crystallographic defects are spatially identified and statistically quantified from a large quantity of diffraction patterns in many layered oxide particles, including geometrically necessary dislocations, tilt boundaries, and mixed defects. The in situ and ex situ measurements, combining microdiffraction and X-ray spectroscopy imaging, reveal that LiCoO 2 particles with a higher concentration of geometrically necessary dislocations provide deeper charging reactions, indicating that dislocations may facilitate redox reactions in layered oxides during initial charging. The present study illustrates that a precise control of crystallographic defects and their distribution can potentially promote and homogenize redox reactions in battery materials.

25 ENERGY STORAGE↗
DOE OSTI2022

X-ray nano-imaging of defects in thin film catalysts via cluster analysis

Functional properties of transition-metal oxides strongly depend on crystallographic defects; crystallographic lattice deviations can affect ionic diffusion and adsorbate binding energies. Scanning x-ray nanodiffraction enables imaging of local structural distortions across an extended spatial region of thin samples. Yet, localized lattice distortions remain challenging to detect and localize using nanodiffraction, due to their weak diffuse scattering. Here, in this study, we apply an unsupervised machine learning clustering algorithm to isolate the low-intensity diffuse scattering in as-grown and alkaline-treated thin epitaxially strained SrIrO 3 films. We pinpoint the defect locations, find additional strain variation in the morphology of electrochemically cycled SrIrO 3 , and interpret the defect type by analyzing the diffraction profile through clustering. Our findings demonstrate the use of a machine learning clustering algorithm for identifying and characterizing hard-to-find crystallographic defects in thin films of electrocatalysts and highlight the potential to study electrochemical reactions at defect sites in operando experiments.

42 ENGINEERING↗
DOE OSTI2023

Atomic-scale identification of defects in alite

Crystallographic defects play a crucial role in cement hydration, with initial dissolution being dominated by the formation of etch pits that rely on the intersection of defects on surfaces. However, the defects present in cement particles have remained a mystery due to the lack of detailed direct observation at the atomic scale. In this study, we used scanning transmission electron microscopy to unravel the defects in alite particles at the single-atom level. Our observations identified different types of defects, including vacancies, doping, dislocations, rough surfaces, and grain boundaries. Atomic ordering in the alite crystal was further examined based on our single-atom recognition method. Our findings indicate that defects in cement particles may serve as reactive sites during the early hydration stage, facilitating the initial dissolution and providing nucleation sites for hydration products. Finally, this work provides insights into cement defect formation at the single-atom level and offers new opportunities in tuning the hydration process through defect engineering of cement particles.

36 MATERIALS SCIENCE↗
DOE OSTI2019

DefectSegNet

DefectSegNet for semantic segmentation of defects in Steels The first and most important step of automating defect analysis is perceptual defect identification. In terms of digital image processing, semantic segmentation best emulates human recognition of defect features – it identifies the crystallographic defects and where they are located in a TEM micrograph. We solved this problem by developing DefectSegNet, a novel hybrid CNN algorithm for robust and automated semantic segmentation of three crystallographic defects, including line dislocations, precipitates and voids, that are commonly observed in structural metals and alloys.

Sainju, Rajat↗
DOE OSTI2024

Dynamic response of additively manufactured Ti–5Al–5V–5Mo–3Cr as a function of heat treatment

Both shock and shockless compression experiments were performed on laser powder bed fusion (LPBF) Ti–5Al–5V–5Mo–3Cr (Ti-5553) to peak compressive stresses near 15 GPa. Experiments were performed on the as-built material, containing a purely β (body centered cubic) microstructure, and two differing heat treatments resulting in a dual phase α (hexagonal close packed) and β microstructure. The Hugoniot, Hugoniot elastic limit (HEL), and spallation strength were measured and compared to wrought Ti-6Al-4V (Ti-64). The results indicate the LPBF Ti-5553 Hugoniot response is similar between heat treatments and to Ti-64. The HEL stress observed in the LPBF Ti-5553 was considerably higher than Ti-64, with the as-built, fully β alloy exhibiting the largest values. The spallation strength of the LPBF Ti-5553 was also similar to Ti-64. Clear evidence of initial porosity serving as initiation sites for spallation damage was observed when comparing computed tomography measurements before and after loading. Post-mortem scanning electron microscopy images of the recovered spallation samples showed no evidence of retained phase changes near the spall plane. The spall plane was found to have kinks aligned with the loading direction near areas with large concentrations of twin-like, crystallographic defects in the as-built condition. For the heat-treated samples, the concentrations of twin-like, crystallographic defects were absent, and no preference for failure at the interface between the α and β phases was observed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Towards bend-contour-free dislocation imaging via diffraction contrast STEM

Dislocation imaging using transmission electron microscopy (TEM) has been an invaluable tool for characterizing crystallographic defects in metals. Compared to conventional TEM imaging, diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) with appropriate setting can provide better defect contrast with almost negligible bend contour artifacts, enabling more effective analysis of dislocation structures. Here, we investigated why STEM can suppresses bend contour, and how dislocation contrast behaves along with different STEM imaging parameters. Using a body-centered cubic HT-9 ferritic/martensitic alloy as an example, a simple procedure and operational theory are described at the beginning to help set up DCI STEM experiments. Comparing with conventional TEM and the STEM strictly complying with the principle of reciprocity, we found that a pair of STEM convergence and collection semi-angles, α S and β S , a few milliradians in size is essential for bend-contour-free defect imaging. It works in concert such that the convergence STEM probe opens up the reciprocal space, and then a comparable collection region evens out the rocking-curve oscillation and alleviates bend contours from the reciprocal space. This fundamental advantage is unique in DCI STEM. Practical guidelines regarding STEM parameters and specimen orientation and thickness are then provided for DCI STEM dislocation imaging. Lastly, we show that coupling DCI STEM with spectrum images of electron energy loss spectroscopy and of energy-dispersive X-ray Spectroscopy offers a comprehensive characterization of crystallographic defects and chemical information of complex microstructures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Native lattice strain induced structural earthquake in sodium layered oxide cathodes

Abstract High-voltage operation is essential for the energy and power densities of battery cathode materials, but its stabilization remains a universal challenge. To date, the degradation origin has been mostly attributed to cycling-initiated structural deformation while the effect of native crystallographic defects induced during the sophisticated synthesis process has been significantly overlooked. Here, using in situ synchrotron X-ray probes and advanced transmission electron microscopy to probe the solid-state synthesis and charge/discharge process of sodium layered oxide cathodes, we reveal that quenching-induced native lattice strain plays an overwhelming role in the catastrophic capacity degradation of sodium layered cathodes, which runs counter to conventional perception—phase transition and cathode interfacial reactions. We observe that the spontaneous relaxation of native lattice strain is responsible for the structural earthquake (e.g., dislocation, stacking faults and fragmentation) of sodium layered cathodes during cycling, which is unexpectedly not regulated by the voltage window but is strongly coupled with charge/discharge temperature and rate. Our findings resolve the controversial understanding on the degradation origin of cathode materials and highlight the importance of eliminating intrinsic crystallographic defects to guarantee superior cycling stability at high voltages.

25 ENERGY STORAGE↗
DOE OSTI2024

X-ray linear dichroic tomography of crystallographic and topological defects

Abstract The functionality of materials is determined by their composition 1–4 and microstructure, that is, the distribution and orientation of crystalline grains, grain boundaries and the defects within them 5,6 . Until now, characterization techniques that map the distribution of grains, their orientation and the presence of defects have been limited to surface investigations, to spatial resolutions of a few hundred nanometres or to systems of thickness around 100 nm, thus requiring destructive sample preparation for measurements and preventing the study of system-representative volumes or the investigation of materials under operational conditions 7–15 . Here we present X-ray linear dichroic orientation tomography (XL-DOT), a quantitative, non-invasive technique that allows for an intragranular and intergranular characterization of extended polycrystalline and non-crystalline 16 materials in three dimensions. We present the detailed characterization of a polycrystalline sample of vanadium pentoxide (V 2 O 5 ), a key catalyst in the production of sulfuric acid 17 . We determine the nanoscale composition, microstructure and crystal orientation throughout the polycrystalline sample with 73 nm spatial resolution. We identify and characterize grains, as well as twist, tilt and twin grain boundaries. We further observe the creation and annihilation of topological defects promoted by the presence of volume crystallographic defects. The non-destructive and spectroscopic nature of our method opens the door to operando combined chemical and microstructural investigations 11,18 of functional materials, including energy, mechanical and quantum materials.

Science & Technology - Other Topics↗
DOE OSTI2017

Densification of the interlayer spacing governs the nanomechanical properties of calcium-silicate-hydrate

Calciuam-silicate-hydrate (C-S-H) is the principal binding phase in modern concrete. Molecular simulations imply that its nanoscale stiffness is 'defect-driven', i.e., dominated by crystallographic defects such as bridging site vacancies in its silicate chains. However, experimental validation of this result is difficult due to the hierarchically porous nature of C-S-H down to nanometers. Here in this paper, we integrate high pressure X-ray diffraction and atomistic simulations to correlate the anisotropic deformation of nanocrystalline C-S-H to its atomic-scale structure, which is changed by varying the Ca-To-Si molar ratio. Contrary to the 'defect-driven' hypothesis, we clearly observe stiffening of C-S-H with increasing Ca/Si in the range 0.8 ≤ Ca/Si ≤ 1.3, despite increasing numbers of vacancies in its silicate chains. The deformation of these chains along the b-Axis occurs mainly through tilting of the Si-O-Si dihedral angle rather than shortening of the Si-O bond, and consequently there is no correlation between the incompressibilities of the a-and b-Axes and the Ca/Si. On the contrary, the intrinsic stiffness of C-S-H solid is inversely correlated with the thickness of its interlayer space. This work provides direct experimental evidence to conduct more realistic modelling of C-S-H-based cementitious material.

36 MATERIALS SCIENCE↗
NASA NTRS1985

High-purity silicon crystal growth investigations

The study of silicon sheet material requirements for high efficiency solar cells is reported. Research continued on obtaining long lifetime single crystal float zone silicon and on understanding and reducing the mechanisms that limit the achievement of long lifetimes. The mechanisms studied are impurities, thermal history, point defects, and surface effect. The lifetime related crystallographic defects are characterized by X-ray topography and electron beam induced current.

Ciszek, T. F.↗
DOE OSTI2023

In situ observation of medium range ordering and crystallization of amorphous TiO 2 ultrathin films grown by atomic layer deposition

The evolution of medium range ordering (MRO) and crystallization behavior of amorphous TiO 2 films grown by atomic layer deposition (ALD) were studied using in situ four-dimensional scanning transmission electron microscopy. The films remain fully amorphous when grown at 120 °C or below, but they start showing crystallization of anatase phases when grown at 140 °C or above. The degree of MRO increases as a function of temperature and maximizes at 140 °C when crystallization starts to occur, which suggests that crystallization prerequires the development of nanoscale MRO that serves as the site of nucleation. In situ annealing of amorphous TiO 2 films grown at 80 °C shows enhancement of MRO but limited number of nucleation, which suggests that post-annealing develops only a small portion of MRO into crystal nuclei. The MRO regions that do not develop into crystals undergo structural relaxation instead, which provides insights into the critical size and degree of ordering and the stability of certain MRO types at different temperatures. In addition, crystallographic defects were observed within crystal phases, which likely negate corrosion resistance of the film. Our result highlights the importance of understanding and controlling MRO for optimizing ALD-grown amorphous films for next-generation functional devices and renewable energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Identifying Defects with Guided Algorithms in Bragg Coherent Diffractive Imaging

In this study, crystallographic defects such as dislocations can significantly alter material properties and functionality. However, imaging these imperfections during operation remains challenging due to the short length scales involved and the reactive environments of interest. Bragg coherent diffractive imaging (BCDI) has emerged as a powerful tool capable of identifying dislocations, twin domains, and other defects in 3D detail with nanometer spatial resolution within nanocrystals and grains in reactive environments. However, BCDI relies on phase retrieval algorithms that can fail to accurately reconstruct the defect network. Here, we use numerical simulations to explore different guided phase retrieval algorithms for imaging defective crystals using BCDI. We explore different defect types, defect densities, Bragg peaks, and guided algorithm fitness metrics as a function of signal-to-noise ratio. Based on these results, we offer a general prescription for phasing of defective crystals with no a prior knowledge.

36 MATERIALS SCIENCE↗