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At least 199 records · Page 11

Nondestructive ultrasonic characterization of a triple-weld-bead wire arc additively manufactured ER70S-6 S-curved wall

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

36 MATERIALS SCIENCE↗

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process–structure–property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process–structure–property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

36 MATERIALS SCIENCE↗

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗

Deuterium trapping mechanisms in reduced activation ferritic martensitic steels and their correlation with mechanical strengthening

Development of high-strength materials often involves introduction of additional strengthening microstructures that also serve as tritium trapping sites. Such additions in fusion material development could degrade the fuel efficiency in fusion reactors and raise radiological concerns. The contribution of individual microstructure features in hydrogen trapping must be evaluated to ensure fuel efficiency and radiological safety. This study explores the mechanistic origins of deuterium trapping in reduced-activation ferritic–martensitic steels and its correlation to mechanical strengthening. A series of model alloys and engineering steels were fabricated and subjected to different heat treatments to control deuterium trapping site density. Deuterium retention was evaluated using D 2 gas charging and thermal desorption spectroscopy, focusing on the role of grain boundary, dislocation, M 23 C 6 precipitates, and TiC precipitates. Multiscale microstructure characterization and synchrotron X-ray diffraction were performed to characterize microstructure, which was correlated to the deuterium retention property. Results show that TiC precipitates exhibit the highest deuterium trapping capacity, followed by M 23 C 6 precipitates. Dislocation and grain boundary demonstrate the lowest and similar efficiencies. Furthermore, the relationship of trapping quantity and mechanical strengthening of these microstructure features was quantified, demonstrating that TiC precipitates offer highest deuterium trapping per unit of mechanical strengthening.

Retention↗

Report on initial development of a database of nuclear graphite characteristics based on microstructural characterization

This report outlines the current and future efforts to produce a comprehensive library of microstructures of nuclear graphite and carbon-based materials that are candidate materials for nuclear applications in the United States. This library must contain extensive characterizations of unirradiated graphite materials, a guide to some of the techniques used to characterize graphite, a compendium of characterization data of neutron-irradiated or oxidized material, and a compendium of microstructural information of carbon-based materials. These characterization efforts are being conducted at various length scales to understand these complex materials’ local structure and property relationships. Achieving this goal requires further developing or adapting advanced characterization techniques that capture graphite’s most relevant characteristics. Some of the general objectives of this project are to aid with the material selection, licensing, management, and core assessments of a graphite core by documenting the unirradiated microstructure of relevant grades or by characterizing the evolution of the microstructure under the reactor environment. Moreover, this project aims to provide additional information, guidelines for characterizing graphite, and a protocol to assess a nuclear graphite grade. This report also summarizes some of the initial results and some of the techniques commonly used to characterize nuclear graphite.

36 MATERIALS SCIENCE↗

Influence of Microstructural Features on Austenite-Martensite Interfaces in NiTi Shape Memory Alloys

Shape memory alloys (SMAs) exhibit several unique thermomechanical properties due to a reversible martensitic phase transformation. A key aspect of this transformation is the austenite-martensite interface. Here we present a molecular dynamics (MD) simulation methodology to study the atomic-scale features of austenite-martensite interface migration under near-equilibrium conditions. In single crystals, the interfaces migrate rapidly with only a small thermodynamic driving force. In polycrystals, however, interface migration is significantly impeded due to the change in orientation relationship at grain boundaries and the stored elastic energy resulting from microstructural constraints. This behavior can be linked to several mechanisms associated with transformation width and hysteresis in SMAs, properties of great importance for applications involving actuation. Additionally, we will present preliminary MD simulation results on the influence of precipitates on the formation and migration of austenite-martensite interfaces.

Gabriel Plummer↗

Influence of Microstructural Features on Austenite-Martensite Interfaces in NiTi Shape Memory Alloys

Shape memory alloys (SMAs) exhibit several unique thermomechanical properties due to a reversible martensitic phase transformation. A key aspect of this transformation is the austenite-martensite interface. Here we present a molecular dynamics (MD) simulation methodology to study the atomic-scale features of austenite-martensite interface migration under near-equilibrium conditions. In single crystals, the interfaces migrate rapidly with only a small thermodynamic driving force. In polycrystals, however, interface migration is significantly impeded due to the change in orientation relationship at grain boundaries and the stored elastic energy resulting from microstructural constraints. This behavior can be linked to several mechanisms associated with transformation width and hysteresis in SMAs, properties of great importance for applications involving actuation. Additionally, we will present preliminary MD simulation results on the influence of precipitates on the formation and migration of austenite-martensite interfaces.

Gabriel Plummer↗

Process-microstructure relationship of laser processed thermoelectric material Bi2Te3

Additive manufacturing allows fabrication of custom-shaped thermoelectric materials while minimizing waste, reducing processing steps, and maximizing integration compared to conventional methods. Establishing the process-structure-property relationship of laser additive manufactured thermoelectric materials facilitates enhanced process control and thermoelectric performance. This research focuses on laser processing of bismuth telluride (Bi 2 Te 3 ), a well-established thermoelectric material for low temperature applications. Single melt tracks under various parameters (laser power, scan speed and number of scans) were processed on Bi 2 Te 3 powder compacts. A detailed analysis of the transition in the melting mode, grain growth, balling formation, and elemental composition is provided. Rapid melting and solidification of Bi 2 Te 3 resulted in fine-grained microstructure with preferential grain growth along the direction of the temperature gradient. Experimental results were corroborated with simulations for melt pool dimensions as well as grain morphology transitions resulting from the relationship between temperature gradient and solidification rate. Samples processed at 25 W, 350 mm/s with 5 scans resulted in minimized balling and porosity, along with columnar grains having a high density of dislocations.

Oztan, Cagri↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Microstructure/mechanical property relationships for various thermal treatments of Al-Cu-Mg-X PM aluminum alloys

The thermal response and aging behavior of three 2XXX-series powder metallurgy aluminum alloys have been investigated, using Rockwell B hardness measurements, optical and electron microscopy, and energy-dispersive chemical analysis, in order to correlate microstructure with measured mechanical properties. Results of the thermal response study indicated that an increased solution heat treatment temperature was effective in resolutionizing large primary constituents in the alloy bearing more copper but had no apparent effect on the microconstituents of the other two. Aging studies conducted at room temperature and at 120, 150, and 180 C for times ranging up to 60 days indicated that classic aging response curves, as determined by hardness measurements, occurred at lower aging temperatures than were previously studied for these alloys, as well as at lower aging temperatures than are commonly used for ingot metallurgy alloys of similar compositions. Microstructural examination and fracture surface analysis of peak-aged tension specimens indicated that the highest tensile strengths are associated with extremely fine and homogeneous distributions of theta-prime or S-prime phases combined with low levels of both large constituent particles and dispersoids. Examination of the results suggest that refined solution heat treatments and lower aging temperatures may be necessary to achieve optimum mechanical properties for these 2XXX series alloys.

Blackburn, L. B.↗

Structure-property relationships in eutectic composites

The preparation of a composite material of eutectic composition directly from the molten state is investigated. The manufacture of eutectic composites by unidirectional solidification is reviewed, and it is shown how two-phase composite structures of given relative volume fraction can be produced with a range of particle sizes. Crystallographic relationships and the thermal stability of interfaces in controlled eutectic structures are examined, the mechanical behavior of aligned eutectic microstructures is discussed, and characteristics of eutectic composites having mechanical properties of engineering significance are evaluated. Specific properties of the Ni-Nb eutectic alloy are reviewed to demonstrate the effect of structure control (through directional solidification) on the mechanical response of a eutectic composite. It is noted that unidirectionally solidified eutectic composites possess highly aligned and thermally stable microstructures and also exhibit excellent combinations of strength and ductility to very high temperature levels.

Hertzberg, R. W.↗

THE ROLE OF FRACTURE PROPERTIES ON LAP JOINT STRENGTH OF FRICTION STIR WELDED AA7055-T6 SHEETS

Friction stir lap welded (FSLW) joints have weight-saving potential in aluminum-intensive automotive assembly. However, FSLW also modifies the material microstructure close to the joint. Optimizing the FSLW process requires understanding the relationship between the strength and the joint's microstructure. In previous studies, efforts have been dedicated to determining the effects of local softening, the shape of the oxide line, and porosity. However, the impact of changes to the fracture properties on the joint's strength has not been studied. In this work, strength testing, and simulations, aided by material characterization, were used to determine the role of fracture properties on the shear strength of a 3-sheet (aluminum alloys 7055-7055-6022) lap joint. Characterization involved testing for fracture properties in the weld region. This data was then implemented into finite element simulations. As a result, the joint strength was predicted with a deviation of less than 6% from the experimental value. Comparison with strength prediction using only the base metal properties indicates that fracture property in the nugget region determines the strength of AA7055 FSLW.

Finite element analysis, Friction stir welding, ma↗

Process-structure-property relationships for droplet-on-demand liquid-metal-jetted parts

Liquid metal jetting droplet-on-demand additive manufacturing is an attractive alternative to industry-standard, laser-based metal additive manufacturing techniques that use powder feedstocks and produce large heat affected zones. Liquid metal jetting provides a low feedstock footprint, minimal materials waste, less contamination and inclusions from feedstock, and is compatible with a large range of materials. However, little has been reported on the liquid metal jetting process-structure-property relationships that are crucial to understanding how to consistently print high quality metal parts. We investigate the effects of build plate temperature, infill pattern, and track raster rate on the macro- and microstructure, density, hardness, and tensile strength of metal parts created with our custom droplet-on-demand setup using pure tin feedstock as a surrogate for more relevant structural materials. We found that although the build plate temperature had the largest influence on the structure and properties, the infill pattern is an important factor for optimal structural integrity. It was observed that the track raster rate influenced track-to-track porosity and should be considered in toolpath development. Despite printing in ambient air, we could not identify oxide on the surface or in the bulk of the parts and saw no adverse effects on microstructure or tensile performance. The results and methods of this study will help guide future work in optimizing the liquid metal jetting process to reliably print parts using any liquid metal jetting system for a wide variety of metal feedstocks.

36 MATERIALS SCIENCE↗

Microstructural characterization of phase-separated co-deposited Cu–Ta immiscible alloy thin films

Elevated temperature co-sputtering of immiscible elements ends in a variety of self-organized morphologies due to phase separation. Cu–Ta is used as a model system to understand the evolution of phase-separated microstructural morphologies by co-sputtering thin films with nominal 50–50 at.% composition at four temperatures: 25, 400, 600, and 800 °C. Scanning/transmission electron microscopy of the film cross sections showed the microstructure morphology varied from nanocrystalline Cu–Ta at 25 °C to a wavy ribbon-like structure at 400 °C, to Cu-rich agglomerates surrounded by Ta-rich veins at 600 and 800 °C. In the agglomerate-vein morphology, microstructural features were present on two length scales, from a few nanometers to a few tens of nanometers, thus making the structures hierarchical. On the nanoscale, the Cu-rich agglomerates contained Ta precipitates, whereas the Ta-rich veins had embedded Cu nanocrystals. The various microstructures can be attributed to the highly disparate constituent element interdiffusion at the deposition temperatures with the Cu having orders of magnitude higher mobility than Ta at the deposition temperatures. This research of processing–microstructure relationship will be useful in guiding the design of hierarchical multiphase microstructures in binary or multicomponent thin films with tailored mechanical properties.

36 MATERIALS SCIENCE↗

Multiscale Modeling of Silicon Carbide Cladding for Nuclear Applications: Thermal Performance Modeling

The complex multiscale and anisotropic nature of silicon carbide (SiC) ceramic matrix composite (CMC) makes it difficult to accurately model its performance in nuclear applications. The existing models for nuclear grade composite SiC do not account for the microstructural features and how these features can affect the thermal and structural behavior of the cladding and its anisotropic properties. In addition to the microstructural features, the properties of individual constituents of the composites and fiber tow architecture determine the bulk properties. Models for determining the relationship between the individual constituents’ properties and the bulk properties of SiC composites for nuclear applications are absent, although empirical relationships exist in the literature. Here, a hierarchical multiscale modeling approach was presented to address this challenge. This modular approach addressed this difficulty by dividing the various aspects of the composite material into separate models at different length scales, with the evaluated property from the lower-length-scale model serving as an input to the higher-length-scale model. The multiscale model considered the properties of various individual constituents of the composite material (fiber, matrix, and interphase), the porosity in the matrix, the fiber volume fraction, the composite architecture, the tow thickness, etc. By considering inhomogeneous and anisotropic contributions intrinsically, our bottom-up multiscale modeling strategy is naturally physics-informed, bridging constitutive law from micromechanics to meso-mechanics and structural mechanics. The effects that these various physical attributes and thermo-physical properties have on the composite’s bulk thermal properties were easily evaluated and demonstrated through the various analyses presented herein. Since silicon carbide fiber-reinforced SiC CMCs are also promising thermal–structural materials with a broad range of high-end technology applications beyond nuclear applications, we envision that the multiscale modeling method we present here may prove helpful in future efforts to develop and construct reinforced CMCs and other advanced composite nuclear materials, such as MAX phase materials, that can service under harsh environments of ultrahigh temperatures, oxidation, corrosion, and/or irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Mechanical response and microstructure evolution from multiaxial stress relaxation in textured zircaloy nuclear cladding

Modern energy markets provide motivation for nuclear reactors to increase operational flexibility and load following capacity of existing reactor designs. The operational power changes result in fuel pellet expansion and contraction resulting in pellet-cladding mechanical interaction (PCMI) and high cladding stresses that are strongly related to stressed corrosion cracking (SCC) which can lead to fuel rod failure. This work aims to quantify the stress fields in cladding with a focus on multiaxial stress relaxation response from an imposed strain and the resulting microstructure changes in textured zircaloy claddings. Stress relaxation tests resulting in multiaxial stress fields are performed to measure the material response of Zircaloy-4 nuclear cladding. Multiple experiments using samples from the same piece of cladding are performed so samples with the same processing history may be removed at strategic points throughout mechanical testing for microstructure characterization. The microstructure evolution is analyzed with mechanical response to evaluate the static recovery impact on crystallographic texture and grain morphology. Experiments are performed at Idaho National Laboratory using an experimental device capable of applying internal pressure and independent axial load to commercial nuclear cladding at elevated temperatures with stress- or strain-controlled experimental capability. X-ray diffraction and electron backscatter diffraction are used for microstructure analysis. Rheological models are used to visualize the multiaxial stress-strain relationships and isolate elastic, plastic, and viscoplastic material properties for analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Surface and grain boundary carbon heterogeneity in CH 3 NH 3 PbI 3 perovskites and its impact on optoelectronic properties

Rivaling state-of-the-art crystalline silicon, organic-inorganic hybrid perovskites have been intensely studied in recent years. Surface and interfacial engineering have been a focus for performance improvement. Even though significant progress has been made during the last decade in terms of the diversity and capability of perovskite-based devices, the structure-property relationship, particularly at the surface, which governs the real-world performance of these applications, is still unresolved. In the article, this issue was addressed by employing synchrotron-related experimental measurements, and a mechanism that correlates microstructure with surface chemistry was resolved. As a powerful and highly sensitive spectromicroscopy, soft x ray photoemission electron microscopy (X-PEEM) was used to probe the surface of perovskite films varying in post solvent annealing. Furthermore, static and in situ grazing incidence hard x ray diffraction (GIXD) was used to track the grain growth dynamics during the film formation process. It was found that the nature of the surfaces was dictated by the local chemistry that varied due to mass flow during the development of the microstructure. Combining optical and electronic characterizations, it was confirmed that a more homogenous chemistry, i.e., uniform chemical components and properties, along with reduced strain and grain boundary energies, yielded more defect-tolerant films. Grain boundaries were more favorable for screening carriers than those in the control film. Our findings underscore the importance of the uniformity in the surface for developing a chemistry-structure-property relationship in perovskite materials, as well as engineering local chemistry toward high-performance and stable devices.

42 ENGINEERING↗

Additive manufacturing of nickel-based superalloys: A state-of-the-art review on process-structure-defect-property relationship

Fusion-based additive manufacturing (AM) has significantly grown to fabricate Nickel-based superalloys with design freedom across multiple length scales. Several phenomena such as feedstock/energy source/melt pool interactions, solidification and phase transformations occur during fusion-based AM processes of Nickel-based superalloys, which determine the ultimate microstructure and mechanical performance of the built parts. In this review, here we elaborate a comprehensive discussion on AM Nickel-based superalloys and influential factors including feedstock characteristics (powder morphology, chemistry, contamination, flowability, recycling) and AM processing (parameters, and powder spreading/wall/balling/spattering effects) on their microstructure (micro-segregation, phases formations and grain structures), defect generation (sub-surface/internal defects, microcracks, surface roughness, and residual stress). Furthermore, the mechanical properties of AM Nickel-based superalloys such as tensile, creep and fatigue at room/elevated temperatures are analyzed in accordance with the initial, and post processing effects. Additionally, the commonly utilized modeling approaches in literature to predict the microstructure and mechanical behavior of these alloys are highlighted. Finally, the current challenges and mitigation approaches for future research are identified considering the gaps in the AM Nickel-based superalloys.

36 MATERIALS SCIENCE↗