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At least 37 records · Page 2

The effects of radiation-induced grain subdivision and dislocations on the fracture properties of uranium dioxide

Microcantilever bending tests were applied on uranium dioxide samples irradiated by 84 MeV Xe ions. Depending on the initial grain sizes, different levels of grain subdivision and dislocation development were observed near the irradiated surface. These radiation damage features were shown to degrade the fracture properties of both samples. The fundamental aspects of the radiation-microstructure-property relationships were discussed in this paper, taking a holistic consideration of the microcantilever bending data, fractography and microstructures. The separate effects of the irradiation-induced grain subdivision and dislocations on the fracture initiation and propagation of uranium dioxide were discussed. In conclusion, it was observed that radiation-induced dislocations and grain subdivision, without the presence of Xe bubbles co-located with the defects, cause reductions in the Young's modulus, fracture strain, and fracture stress, and a transition to intergranular fracture.

36 MATERIALS SCIENCE↗

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↗

Additive manufacturing of metal matrix composites

Although Metal matrix composites (MMCs) are superior to most sought-after metallic alloys, their challenging fabricability has limited their widespread use in bulk-form applications. Among the many advanced fabrication techniques, Additive Manufacturing (AM), owing to its unique capabilities to produce near-net shapes, has drawn significant traction in the past two decades, especially for materials that are difficult to process using traditional methods. However, unlike pure metal/alloy systems, MMCs are highly sensitive to the processing conditions prevailing in AM techniques due to factors such as the high melting point of reinforcement particles and the potential for in-situ reactions. Therefore, it may be a while before metal matrix composites are commercially produced via AM. This review will discuss the current state-of-the-art design, fabricability, and performance of various additively manufactured MMCs. A particular focus will be on microstructural evolution and microstructure-property relationships. The most employed AM techniques, such as directed energy deposition, powder bed fusion, binder jetting, sheet lamination, and solid-state friction stir processing, are fundamentally different in terms of thermo-kinetics, forming the perspective for this review. A detailed comparison of microstructural evolution and process parameter optimization, including feedstock preparation methods and the role of machine learning and modeling among the different AM processes, is also presented. Finally, a critical evaluation of emerging AM technologies for MMCs is also provided, highlighting their potential advantages and challenges.

36 - MATERIALS SCIENCE↗

Location-Dependent Mechanical Property Evaluation on Additively Manufacture Materials

This report summarizes research activities conducted at Argonne National Laboratory in support of the development, qualification and certification of additively manufactured (AM) metallic components to allow for innovative reactor design and licensing for the Transformational Challenge Reactor (TCR). Focus is on the evaluation of high temperature mechanical properties including creep and fatigue of 316L stainless steel manufactured by the laser powder bed fusion process. Creep behavior of AM 316L stainless steel was evaluated for rods printed by either or a combination of both lasers of the dual-laser system of a Concept Laser-M2 printer to examine the consistency across the build plate. Creep tests were conducted at temperatures of 550, 575, 600, and 650°C and stresses between 175 and 300 MPa using ASTM standard-sized specimens. The effect of heat treatments at different temperatures on creep properties of AM 316L SS was examined to understand the processing-microstructure-property relationship. Fatigue properties of AM 316L SS were investigated for two print geometries (rod and plate) and in two build orientations of printed plates. Locations of specimens in the build were carefully tracked such that the testing data can be directly related to location-specific in situ data to establish links between printing process, post-printing treatment, microstructure and mechanical properties. The work is to support the development of a digital platform informed approach to AM component qualification and certification for nuclear applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Baseplate Temperature–Dependent Vertical Composition Gradient in Pseudo–Bilayer Films for Printing Non–Fullerene Organic Solar Cells

Numerous previous reports on the sequential deposition (SD) technique have demonstrated that this approach can achieve a p–i–n active layer architecture with an ideal vertical composition gradient, which is one of the critical factors that can influence the physical processes that determine the photovoltaic performance of organic solar cells. Herein, a commonly used photovoltaic system comprised of PM6 as a donor and Y6 as an acceptor is investigated with respect to sequential blade–processing deposition to comprehensively explore the morphology characteristics as a function of baseplate temperature. A systematic study of the temperature–dependent blend morphology elucidates the SD–processed configuration merits and device physics behind temperature–controlled degree of vertical composition gradient, and constructs the temperature–microstructure–property relationship for the corresponding photovoltaic parameters. The result shows, as the temperature increases, the morphology of the active layer has undergone a distinct evolution from the pseudo–bulk heterojunction to a pseudo–planar heterojunction and then to a pseudo–planar bilayer, leading to a non–monotonic correlation between baseplate temperature and device performance. Further, this investigation not only reveals the importance of precisely controlling baseplate temperature for gaining vertical morphology control, but also provides a path toward rational optimization of device performance in the lab–to–fab transition.

14 SOLAR ENERGY↗

Heterogeneous microstructure of yttrium hydride and its relation to mechanical properties

Here, the goal of this study is to investigate the properties of yttrium hydride materials in relation to the microstructure, especially its homogeneity. High-throughput nanoindentation mapping was used to evaluate hardness distribution. Raman spectral imaging demonstrated its sensitivity to the presence of YH2 and impurities. Raman peak position maps were correlated with residual stress in the specimens. Electron backscatter diffraction mapping provided phase distributions with correlation to high-energy X-ray diffraction analysis. The experimental mapping data were combined and analyzed using unsupervised machine learning cluster procedures. The machine learning analysis revealed that yttrium hydride specimens contained a major δ-YH2 – x phase component and minor α-Y and δ-YH2 – x components with significant residual stress. The minor phase fraction decreased with increasing nominal H/Y ratio, which affected the nanoindentation and Vickers hardness. The multimodal mapping procedures described herein affect developing important microstructure–property relationships, as well as correlations in heterogeneity and mechanical properties.

36 MATERIALS SCIENCE↗

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗

Applications of analytical electron microscopy to guide the design of boron carbide

Compositional analysis of boron carbide on nanometer length scales to examine or interpret atomic mechanisms, for example, solid-state amorphization or grain-boundary segregation, is challenging. This work reviews advancements in high-resolution microanalysis to characterize multiple generations of boron carbide. First, ζ-factor microanalysis will be introduced as a powerful (scanning) transmission electron microscopy ((S)TEM) analytical framework to accurately characterize boron carbide. Three case studies involving the application of ζ-factor microanalysis will then be presented: (1) accurate stoichiometry determination of B-doped boron carbide using ζ-factor microanalysis and electron energy loss spectroscopy, (2) normalized quantification of silicon grain-boundary segregation in Si-doped boron carbide, and (3) calibration of a scanning electron microscope X-ray energy-dispersive spectroscopy (XEDS) system to measure compositional homogeneity differences of B/Si-doped arc-melted boron carbides in the as-melted and annealed conditions. Overall, the improvement and application of advanced analytical tools have helped better understand processing–microstructure–property relationships and successfully manufacture high-performance ceramics.

36 MATERIALS SCIENCE↗

Development of creep resistant ferritic-martensitic steels for operation at 650°C

Creep resistant ferritic-martensitic steels capable of operating at 650°C have long been under development for electricity generation. This presentation will showcase the design and development of alloys CPJ-7 and JMP with approximately 420,000 h of in-house creep testing, the equivalent of ~50 years of cumulative creep tests. Approximately fifty different alloy compositions were manufactured as part of an ICME approach. CPJ-7 present superior creep properties compared to COST alloys for steam turbine and P91/92 for boiler applications. The prolonged creep life was attributed to slowing down the destabilization of fine precipitates at 650°C. The JMP steels were designed with higher Co for solid solution strengthening and increased W for matrix strength and stability. The creep life compared to CPJ-7 increased between 118 and 150% at 650°C depending on the stress. On a Larson-Miller plot, the performance of the JMP steels surpasses that of MARBN steel. Composition-microstructure-properties relationships will be discussed.

Detrois, Martin↗

Critical statistical assessment of data in metal additive manufacturing

Obtaining high quality data reflecting the relationships between the additive manufacturing (AM) process parameters, material microstructure and mechanical properties is crucial for the use of machine learning in AM. A database of over 4,000 data entries of metal AM was created thanks to a large number of literature studies on key process parameters and indicators of build quality. Meta-analysis reveals critical biases in the literature. Firstly, majority of studies report only high quality builds, these imbalances in reporting result in weak correlation between process parameters, properties and consolidation, limiting the ability of machine learning models to generalize beyond optimized conditions. Nevertheless, the trained models accurately predict yield strength ($R^2 = 0.85$), suggesting that certain process–property relationships are effectively captured within these models. Secondly, quantitative microstructural data are largely absent, limiting the learning of the microstructure-mechanical properties relationships. Finally, current process window identification is based largely on the consolidation, despite significant uncertainty in its measurement. It is important to identify the process map on the basis of not only the consolidation, but also mechanical behaviour under loading. Such a identification shows that 316 L and Inconel have much larger process map (i.e. highly printable) in comparison to the AlSi10Mg and Ti6Al4V.

Additive manufacturing↗

Multi-scale characterization of supersolidus liquid phase sintered H13 tool steel manufactured via binder jet additive manufacturing

Additive manufacturing (AM) of H13 tool steel by binder jet 3D printing (BJ3DP) followed by pressureless supersolidus liquid phase sintering (SLPS) provides a low-cost alternative manufacturing method for components with intricate geometric features. However, the microstructure-mechanical property relationships for BJ3DP-SLPS produced H13 tool steel are not well understood, which makes it challenging to develop printing and post-processing methods that maximize part performance. In this work, we leverage atom probe tomography and transmission electron microscopy along with thermodynamic calculations to rationalize the microstructure-mechanical property relationships in as-sintered BJ3DP H13 tool steel. Here, we report for the first time, the presence of a continuous eutectic film-like carbide in H13 along with the more commonly observed cuboidal MX carbides in the prior liquid channels of the microstructure. Further, atom probe tomography revealed the interconnected nature of the MX carbides that appear to be discrete in two-dimensional micrographs. These continuous eutectic carbides and interconnected MX carbides result in brittle failure of the material. Characterization of these microstructural features will be critical in developing appropriate post-processing heat treatments for the improved mechanical performance of BJ3DP H13.

36 MATERIALS SCIENCE↗

Microstructure, Thermal, and Mechanical Properties Relationships in U and UZr Alloys (Final Report)

Uranium-zirconium (U-Zr) alloys are candidate fuel systems for transmutation based reactors that can be used to burn long-lived minor actinides and fission products in fast spectrum reactors. Metallic fuels have also been gaining more recent attention for applications as accident tolerant fuels, as well as for use in small modular reactors. This research focused on a “science-based” approach to capture the connections between U and U-Zr alloys’ three-dimensional (3-D) microstructure, thermal properties, and mechanical properties through closely coordinated experiments and modeling efforts from the unirradiated to the irradiated fuels. Advanced characterization and modeling techniques were used to understand irradiation-induced microstructural evolution and its direct impact on the thermal and mechanical properties of U and U-Zr fuel. Closely coordinated experiments and modeling were performed to provide crucial data that does not currently exist. Overall, this research spanned multiple length and time scales within the models and experiments. The scope of the research encompassed the understanding of the irradiation effects in U and various U-Zr alloys with particular attention paid to three task areas: (1) microstructural evolution, (2) in-situ/ex-situ thermal and mechanical properties, and (3) multiscale modeling connections to microstructure, thermal, and mechanical properties. This research resulted in (1) the 3-D characterization of neutron irradiated U-Zr fuel in multiple phase regions to better understand fission gas swelling and constituent redistribution, (2) development of a microstructural model linking thermal and mechanical properties via in situ Raman and nanoindentation, (3) and mesoscale phase field modeling was coupled with the AEH method in the MOOSE framework was used to calculate the effective thermal conductivities of U-Zr fuels consisting of α-U and δ-UZr 2 heterogeneous microstructures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Structure–property relationships of reduced graphene oxide membranes intercalated with polycyclic aromatics

Graphene oxide (GO) membranes intercalated with various organic moieties have shown excellent potential for a range of water processing applications. However, microstructure–functional property relationships in these structurally disordered membranes are not well understood. We demonstrate a practical methodology for developing such relationships for GO membranes intercalated with molecular species, with polycyclic aromatic toluidine blue O (TBO) as an example functional intercalant. We use solid-state UV–vis absorbance and fluorescence measurements to quantitatively track the arrangements of TBO in a series of TBO-loaded reduced GO (rGO) membranes. This study reveals the evolution of diverse arrangements including TBO monomers, lateral and stacked dimers, and other aggregates, as a function of overall TBO loading. These microstructures are then correlated to changes in overall properties such as interlayer d-spacings, permeate fluxes, and solute rejections. The characterization of these different intercalant microstructures explains non-intuitive flux and rejection trends, which can circumvent flux and solute rejection trade-offs.

02 PETROLEUM↗

Relationship between microstructure evolution and properties enhancement of carbon nanotubes‐filled polybutylene terephthalate/polypropylene blends induced by thermal annealing

Abstract Thermal annealing induced microstructure evolution and properties enhancement of polybutylene terephthalate/polypropylene/carbon nanotubes (PBT/PP/CNTs) nanocomposites was methodically investigated. The electrical conductive PBT/PP/CNTs nanocomposites with a low percolation threshold were obtained by simple melt blending due to the selective location of the CNTs in PBT phase and the formation of the double percolation structure. Thermal annealing further remarkably decreased the volume resistivity of the nanocomposites, with the maximum reduction of seven orders of magnitude. Scanning electron microscope observation and rheology tests demonstrated that the relatively large CNTs agglomerates were redistributed to build more homogeneous CNTs networks after annealing. The phase coalescence during annealing promoted the formation of the more perfect co‐continuous structure. These phenomena helped to enhance the electrical conductivity of the nanocomposites. Flexural properties of the nanocomposites were also enhanced after annealing, which might be due to the more effective stress transfer between the polymer and CNTs induced by the reconstructed CNTs networks. The nanocomposites obtained in this study possess excellent electrical and mechanical properties, which can be applied to the fields of sensors, electromagnetic interference shielding, anti‐static materials, and so forth.

Shang, Mengyao↗

Physically Based Modeling of PEMFC Cathode Catalyst Layers: Effective Microstructure and Ionomer Structure–Property Relationship Impacts

Abstract This work presents a pseudo-two-dimensional proton exchange membrane fuel cell (PEMFC) model incorporating Nafion ionomer structure–property relationships in the cathode catalyst layer (CL) to capture and explain losses at low Pt loading. Structural data from neutron reflectometry and thin film Nafion conductivity measurements predict variations in the oxygen diffusion coefficient and ionic conductivity with changing CL ionomer thickness and Pt loading. By including these structure–property relationships, predicted polarization curves agree closely with previously published experimental data from cells with Pt loadings between 0.025 and 0.2 mg/cm2. Results demonstrate that structure–property relationships based on physically measurable ionomer and CL properties provide a feasible interpretation of PEMFC CL phenomena for a range of Pt loadings and help explain previously unaccounted-for losses at low Pt. Results also show that simulations must account for surface species coverage variations in order to properly capture the kinetic losses. Finally, results suggest that an increase in ionomer thickness surrounding the C/Pt surfaces may lead to improved cell performance due to improved ionic conductivity.

Electrochemistry↗

Microstructure Evolution of a Multimodal Gamma-Prime Ni-Based Superalloy Characterized by In Situ Diffraction

The relationship between the evolution of microstructure, deformation micromechanisms and mechanical properties is difficult to establish in multimodal size distribution $_γ$$'$ superalloys, as the microstructure evolves with both temperature and time, and multiple strengthening mechanisms across each size distribution contribute to mechanical performance. In situ X-ray scattering can offer unparalleled insight regarding microstructure evolution at the temperatures and stresses of importance to gas-turbine applications; however, in situ X-ray diffraction has not been applied to the study of multimodal $_γ$$'$ distribution superalloys. Herein, lattice parameter evolution of secondary and tertiary $_γ$$'$ precipitates in a representative superalloy, Nimonic 115, is determined between 750 °C and 950 °C and correlated to room-temperature SEM and microhardness values. A large positive lattice parameter misfit of secondary $_γ$$'$ induces precipitate splitting, and the tertiary $_γ$$'$ goes into dissolution at ~ 800 °C, but with little apparent change in hardness values. The volume fraction of $_γ$$'$ decreases above 900 °C and precipitate-matrix coherency is lost, and there is a corresponding decrease in microhardness values. Importantly, the diffraction analysis demonstrates the capability to determine critical microstructural parameters of both precipitate size distributions in situ, representing an additional tool for determining microstructure-mechanical property relationships of multimodal superalloys.

36 MATERIALS SCIENCE↗

Insights into the Effect of Heat Treatment and Carbon Coating on the Electrochemical Behaviors of SiO Anodes for Li-Ion Batteries

The use of SiO as an anode material has attracted significant interest due to its high capacity and long cycling life. Many promising approaches, including structural design and carbon coating at high temperatures, effectively improve its intrinsic low electrical conductivity and poor Coulombic efficiency. However, the “heat treatment process-composition and microstructure-electrochemical properties” relationship of the SiO anode is not fundamentally understood. Here the structure and composition evolution in amorphous SiO and graphene-coated SiO is investigated using different heat-treatment conditions. X-ray absorption near-edge structure techniques are also employed to analyze the surface and bulk composition change during the initial lithiation process, supplemented by physical or chemical characterization and electrochemical testing. Here results reveal the structural transition of SiO during heat treatment, from amorphous to disproportionated hierarchical structure, where the as-formed dielectric exterior SiO 2 shell and interior SiO 2 matrix severely polarizes electrodes, hindering the lithiation process. Carbon coating on SiO effectively restricts the growth of the SiO 2 shell and facilitates charge transfer, leading to improved electrochemical performance. A schematic model is proposed to reveal the relationship between the treatments, the resultant structural evolutions, and corresponding electrochemical behaviors.

36 MATERIALS SCIENCE↗

Additive manufacturing of AISI M2 tool steel by binder jetting (BJ): Investigation of microstructural and mechanical properties

The presented research demonstrates for the first time the successful processing of AISI M2 tool steel by binder jetting, a promising additive manufacturing technique capable of producing complex shapes with minimal residual stresses and isotropic properties. The optimal printing parameters were explored by varying processing parameters such as the binder saturation (45 %–105 %), binder set time (0 to 10 s), targeted bed temperature (50–60 °C), oscillator (2600–2750 rpm), recoater (20–28 mm/s), and roller speeds (200–300 rpm). Microstructural characterization and evaluation of mechanical properties of binder jetted parts were performed using x-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS) to study their chemical composition, powder morphology, microstructure, carbide morphologies, relative density, hardness, compressive strength, and ductility. Two powder sizes (5 and 10 μm) were used, and sintering was performed at varying temperatures (1270, 1280, and 1300 °C) and durations (60 and 120 min), followed by a furnace, air, and water cooling. An optimum hardness of ~970 HV was obtained when parts were sintered at 1270 °C for 60 min, followed by water quenching. Impressive compressive strength of ~ 3580 MPa was observed in the sample sintered at 1280 °C for 60 min duration, followed by air cooling. Furnace-cooled parts showed the highest density of ~95 %, whereas the relative density of air- and water-cooled parts varied between ~91 to 93.50 %, respectively. The microstructure of sintered samples revealed the formation of M 6 C stable carbide, M 2 C metastable carbide, MC as a secondary carbide, and a-Fe matrix, which contributed to the observed increase in mechanical properties.

36 MATERIALS SCIENCE↗