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Results for “Microstructure characterization”

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 OSTI2023

Microstructural characterization of the oxidation of nuclear graphite under chronic and accident conditions via XCT and synchrotron XCT

Graphite is a candidate material to moderate fast neutrons and for structural components in the US next-generation graphite-moderated reactors. A graphite core is conceived as a large formation of interconnected bricks that primarily serves as the moderator of fast neutrons, holds instrumentation, fuel elements, control rods, and is a receptacle for molten salts for Molten Salt Reactors (MSRs) designs. During the operation of a graphite-moderated power plant, graphite components might be subjected to chronic oxidation during normal operating conditions or aggressive oxidation as a result of accidental ingress of air that reacts vigorously with the graphite core. Using synchrotron, x-ray computed tomography (XCT), this research systematically characterized microstructural changes that accompanied these two oxidation scenarios. Chronic oxidation was studied by characterizing IG-110, PCEA, and NBG-18 specimens that were gradually oxidized in air at a low temperature (520°C). The accidental ingress of air into the graphite reactor was simulated by subjecting the grades mentioned above to high-temperature oxidation at approximately 750°C. This research is the first, in situ, systematic characterization of nuclear graphite microstructural evolution that can be associated with the two possible oxidation scenarios and provide insight into related repercussions. The results show that the microstructure and pore connectivity influence the rate of oxidation and evolution of the microstructure under the two oxidation regimes. These results are crucial to understanding which grades are more resilient to each type of oxidation and documenting the damage created in the graphite.

Arregui Mena, Jose'↗
DOE OSTI2017

Quantitative Microstructure Characterization of a NMC Electrode

Performance of lithium-ion batteries (LIBs) is strongly influenced by the porous microstructure of their electrodes. In this work, 3D microstructures of calendared and un-calendared positive electrode LiNi1/3Mn1/3Co1/3O2 (NMC) have been investigated in order to extract relevant properties useful for battery modeling. Transport (volume fraction, connectivity, particle size and tortuosity) and electrochemical (specific surface area) properties have been calculated for the pore and the active material. Special attention has been paid to determine the size of the so-called representative volume element (RVE) required to be statistically representative of the heterogeneous medium. Several parameters have been calculated using a panel of different numerical methods in order to compare their results. Besides, the image level of detail has been evaluated (using original criteria based upon edge detection) to assess the overall data quality available for the study.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Comparing non-destructive 3D X-ray computed tomography with destructive optical microscopy for microstructural characterization of fiber reinforced composites

Due to their lightweight, relatively high stiffness properties, and formability into complex shapes, discontinuous fiber composites are advantageous for producing small and medium size components. Improved characterization techniques and post-processing methodologies are required for more reliable quantification of the microstructure and defect distributions in these materials, in order to employ model-based approaches to assess their structural integrity. This work compares a non-destructive X-ray approach with a destructive optical microscopy approach for characterizing the microstructural attributes, specifically the fiber volume fraction, porosity volume fraction, fiber orientation distribution, and fiber length distribution of discontinuous glass fibers in a polypropylene matrix. Additionally, a method for destructively determining the ambiguous components of the orientation tensor (related to the sign ambiguity of the out-of-plane angle in a destructive cross-sectional cut of a fiber) over a large surface area is included. It was found that fiber volume fraction and average fiber aspect ratio matched well, while fiber orientation and porosity detection had small but notable differences. The differences in the detection capabilities of each technique are quantified and discussed shedding light on the specific advantages and disadvantages of each approach, and enabling engineers to quantify uncertainty in their microstructural characterization measurements especially as they relate to model based structural integrity activities.

Non-destructive testing↗
DOE OSTI2020

Microstructural characterization of dendritic evolution using two-point statistics

Characterizing large four-dimensional materials datasets is difficult due to the presence of complex mi- crostructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evo- lution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into compet- itive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap.

Aluminum alloys↗
DOE OSTI2016

Three dimensional microstructural characterization of nanoscale precipitates in AA7075-T651 by focused ion beam (FIB) tomography

The size and distribution of precipitates in Al 7075 alloys affects both the mechanical and corrosion behavior (including stress corrosion cracking and fatigue corrosion) of the alloy. Three dimensional (3D) quantitative microstructural analysis of Al 7075 in the peak aged condition (T651) allows for a better understanding of these behaviors. In this study, Focused ion beam (FIB) tomography was used to characterize the microstructure in three dimensions. Analysis of grains and precipitates was performed in terms of volume, size, and morphology. It was found that the precipitates at the grain boundaries are larger in size, higher in aspect ratios and maximum Feret diameter compared to the precipitates inside the grains, due to earlier nucleation of the precipitates at the grain boundaries. Our data on the precipitates at the interface between grains and Mg{sub 2}Si inclusion show that the surfaces of inclusion (impurity) particles can serve as a location for heterogeneous nucleation of precipitates. - Highlights: •Focused ion beam (FIB) tomography was used to characterize the microstructure of Al 7075 in three dimensions. •Analysis of grains and precipitates was performed in terms of volume, size, and morphology. •Precipitates at the grain boundaries have larger size and aspect ratio compared to the precipitates inside the grains.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantitative Microstructural Characterization of Plutonium Oxalate Auto-Degradation and Evidence for PuO2 Nanocrystal Formation

It has been known since the 1950s that plutonium oxalate powders change color and lose mass over time when stored at room temperature in air. Despite several studies monitoring these changes, there are still discrepancies in the literature regarding the speciation of intermediate and final products that result from this decomposition. Presented here for the first time is a comprehensive series of time-resolved powder X-ray diffraction experiments coupled with solid-state optical spectroscopy and electron microscopy of aged plutonium (III) and (IV) oxalate powders. These data provide fresh insight into the chemical and structural changes that occur in these solids over time at room temperature and represent new evidence suggesting both plutonium (III) and plutonium (IV) oxalates decompose to form nanocrystalline plutonium oxide in the solid state.

Corbey, Jordan F.↗
DOE OSTI2020

Microstructural characterization of cold-worked 316 stainless steel flux thimble tubes irradiated up to 100 dpa in a commercial Pressurized Water Reactor

Two flux thimble tubes (FTT) made of 15% cold-worked 316 stainless steel (SS) were harvested from Ringhals Pressurized Water Reactor (PWR) Unit 2, with peak damages of 76 and 100 displacements per atom (dpa) after 29 and 34 years’ service, respectively. Specimens sectioned from parent tubes were comprehensively characterized with nominal damage levels of ~0, ~41, ~74, 76, and 100 dpa at a nominal temperature range of 285-323 °C. Both FTTs contained helium and hydrogen gases as transmutation products. The helium follows a production rate of ~9.8 appm/dpa, while environmental factors complicate hydrogen production obscuring an exact H/dpa ratio. Irradiation-induced dislocation loops, nano-cavities, solute clusters, and microsegregation were all observed. The dislocation loops and nano-cavities indicated saturation at 41 dpa. The solute clusters continued to evolve with Ni-Si clusters formed at 41 dpa, and Ni-Si-Mn-P clusters formed at 74 and 100 dpa, but neither clusters exhibited distinct diffraction patterns at any damage levels. Solute clusters were observed to frequently be co-located with dislocation loops, but fully decorated loops were rarely detected. Significant radiation-induced segregation (RIS) was observed around grain boundaries at all damage levels. The modified inverse Kirkendall (MIK) model captured the RIS behavior of major elements. Large cavities within or around an Mn-S rich region were observed for the first time. Through all the damage levels, void swelling is always below 0.05%, making significant dimensional change unlikely in core internals when used at similar conditions. Meanwhile, the role of overwhelming nanocavities, presumably helium bubbles, should be considered in other potential degradation mechanisms, including irradiation-assisted stress corrosion cracking, embrittlement, and loss of fracture toughness, which remain the concerns for extended operation of nuclear power plants.

Post Irradiation Examination, Isotope Dilution Mas↗
DOE OSTI2020

Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives

Microstructural characterization of composite high explosives (HEs) has become increasingly important over the last several decades in association with the development of high fidelity mesoscale modeling and an improved understanding of ignition and detonation processes. HE microstructure influences not only typical material properties (e.g., thermal, mechanical) but also reactive behavior (e.g., shock sensitivity, detonation wave shape). A detailed nondestructive 3D examination of the microstructure has generally been limited to custom-engineered samples or surrogates due to poor contrast between the composite constituents. Highly loaded (>90 wt%) HE composites such as plastic-bonded explosives (PBX) are especially difficult. Here, we present efforts to improve measurement quality by using single and dual-energy microcomputed X-ray tomography and state-of-the-art image processing techniques to study a broad set of HE materials. Some materials, such as PBX 9502, exhibit suitable contrast and resolution for an automatic segmentation of the HE from the polymer binder and the voids. Other composite HEs had varying levels of success in segmentation. Post-processing techniques that used commercially available algorithms to improve the segmentation quality of PBX 9501 as well as zero-density defects such as cracks and voids could be easily segmented for all samples. Aspects of the materials that lend themselves well to this type of measurement are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Microstructure characterization based on the type of deformed grains in cold-rolled, Cu-added, bake-hardenable steel

The electron backscatter diffraction technique has been used to characterize the microstructure of deformed grains in cold-rolled, Cu-added, bake-hardenable steel. A new scheme based on the kind and number of average orientations, as determined from a unique grain map of the deformed grains, was developed in order to classify deformed grains by type. The α-fiber components, γ-fiber components and random orientations, those which could not be assigned to either γ-fiber or α-fiber components, were used to define the average orientation of unique grains within individual deformed grains. The microstructures of deformed grains in as-rolled specimens were analyzed based on the Taylor factor, stored energy, and misorientation. The relative levels and distributions of the Taylor factor, the stored energy and the misorientation were examined in terms of the types of deformed grains. - Highlights: • We characterized the microstructure of Cu-added BH steel using EBSD. • A new scheme was developed in order to classify deformed grains by type. • Stored energy and misorientation are strongly dependent on the type of deformed grains. • Microstructure was examined in terms of the types of deformed grains.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗
DOE OSTI2023

A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation

Understanding the microstructure–property relationships of porous media is of great practical significance, based on which macroscopic physical properties can be directly derived from measurable microstructural informatics. However, establishing reliable microstructure–property mappings in an explicit manner is difficult, due to the intricacy, stochasticity, and heterogeneity of porous microstructures. In this paper, a data-driven computational framework is presented to investigate the inherent microstructure–permeability linkage for natural porous rocks, where multiple techniques are integrated together, including microscopy imaging, stochastic reconstruction, microstructural characterization, pore-scale simulation, feature selection, and data-driven modeling. A large number of 3D digital rocks with a wide porosity range are acquired from microscopy imaging and stochastic reconstruction techniques. A broad variety of morphological descriptors are used to quantitatively characterize pore microstructures from different perspectives, and they compose the raw feature pool for feature selection. Here high-fidelity lattice Boltzmann simulations are conducted to resolve fluid flow passing through porous media, from which reliable permeability references are obtained. The optimal feature set that best represents permeability is identified through a performance-oriented feature selection process, upon which a cost-effective surrogate model is rapidly fitted to approximate the microstructure-permeability mapping via data-driven modeling. This surrogate model exhibits great advantages over empirical/analytical formulas in terms of prediction accuracy and generalization capacity, which can predict reliable permeability values spanning four orders of magnitude. Besides, feature selection also greatly enhances the interpretability of the data-driven prediction model, from which new insights into the mechanism of how microstructural characteristics determine intrinsic permeability are obtained.

58 GEOSCIENCES↗
DOE OSTI2017

Current Status of the Irradiated Materials Characterization Laboratory at INL with Limited PIE Microstructural Characterization

The Irradiated Materials Characterization Laboratory at Idaho National Laboratory is a post-irradiation examination (PIE) facility focused on high end microscopy enclosed in shielded enclosures. Planned PIE activities include: sample preparation, microscopy (FIB, EPMA, and TEM), and thermal property measurements. An overview of the facility, its operational status, and its future growth will be presented. A detailed discussion of the shielding/confinement surrounding the PIE equipment will be provided. The shielded sample preparation area, SSPA, will be discussed, focusing on instruments being incorporated to achieve high quality sample finishes for microscopy and thermal property measurements. With various instruments of IMCL operational, PIE results of irradiated fuels using the EPMA, FIB, and TEM will be provided. A detailed explanation of the capabilities of the PIE equipment will be presented and how these instruments are being incorporated in preforming high quality microstructural characterization on highly irradiated materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Vibro-acoustic Testing for Microstructure Characterization and Metrology: Technology Commercialization Fund—Fiscal Year 2017

There is a need in nuclear reactors to inspect irradiated materials and structures. A portable scanning infrastructure for a material characterization technique called vibro acoustography (VA) is being developed by the Idaho National laboratory for nuclear applications to characterize fuel, cladding materials, and structures. The proposed VA technology is based on ultrasound and acoustic waves; however, it provides information beyond what is available from the traditional ultrasound techniques and can expand the knowledge on nuclear material characterization and microstructure evolution. VA technique has several advantages over traditional characterization techniques. VA is a non-contact submersion technique that is inherently wireless transmission and reception (from the ultrasonic transmitter to the acoustic receiver). The transmission medium can be most liquids used for reactor cooling such as water and sodium. For nuclear in-pile applications, the Ultrasonic Transducer (UT) will need to have a line of sight location that is within lower radiation flux zones. Multiple UT sources can be frequency multiplexed to allow a single hydrophone receiver to monitor several locations. The reactor structure can also be an integral part of the transmission system acting as waveguides to deliver the acoustic signal to an acoustic receiver. Because of the long wavelength of the acoustic signal, the acoustic receiver does not have to be line of sight with respect to the component under test. The focusing and generation of the acoustic beat frequency from two ultrasonic waves allows for the potential to ultrasonically image complex shapes. These features will significantly reduce experiment complexity, installation times and cost while being safe and easy to use.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗