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At least 73 records · Page 4

The complex structural and chemical nature of monolithic U-10Mo fuel and Zr barrier layer

Nanoscale microstructural characterization by advanced transmission electron microscopy techniques on a U-10Mo/Zr barrier layer monolithic fuel plate was performed to evaluate the microstructural evaluation after high burn-up. Gas bubble superlattice evolution, grain restructuring, and evolution of the Zr interaction layer is investigated through detailed electron microscopy characterization. The use of automated crystallographic orientation mapping to irradiated U-10Mo fuel highlights that the restructured ultra-fine grains are separated by high angle grain boundaries at a burn up of 4.42 × 10 21 fissions/cm 3 . Additionally, advanced chemical analysis and multi-variable statistical analysis shows spatial clustering of solid fission product precipitates. Finally, characterization of a newly observed porous nanocrystalline Zr region in the barrier layer is studied. Finally, this work provides insights into the grain subdivision and restructuring process while using advanced microscopy techniques to analyze fission products in neutron-irradiated U-10Mo fuel.

36 MATERIALS SCIENCE↗

Laser processing

Progress in the Progress ceramic materials is reported. Experiments and models for sintering and microstructure evolution are described. Models and data for understanding the kinetics of grain boundary motion and of pore coarsening and new materials for fuel cells and batteries; are developed. New experimental techniques using lasers for forming fine, monosized powders and for forming stable and metastable structures from liquids, and solar materials research are also developed. Colloidal science and ceramics processing are explored; and research programs on the presintering science necessary for controlled green microstructures are outlined.

Source record↗

Microstructural Coarsening Kinetics and Mechanical Property Changes in Long-Term Aged Sn–Pb–Sb Solder Joints

Tin-lead-antimony (50Sn–47Pb–3Sb wt.%) soldered assemblies were mechanically tested approximately 30 years after initial production and found to have solder joints of reduced strength. The microstructure of this solder alloy exhibits a ternary eutectic structure with Sn-rich, Pb-rich, and SnSb phases. Accelerated aging was performed to evaluate solder microstructural coarsening and associated strength of laboratory solder joints to correlate these properties to the “naturally aged” solder joints. Isothermal aging was conducted at room temperature, 55, 70, 100, and 135 °C and aging times that ranged from 0.1 to 365 days. The coarsening kinetics of the Pb-rich phase were determined through optical microscopy and image analysis methods established in previous studies on binary Sn–Pb solder. A kinetic equation was developed with time exponent n of 0.43 and activation energy of 24000 J/mol, suggesting grain boundary diffusion or other fast diffusion pathways controlling the microstructural evolution. Compression testing and Vickers microhardness showed significant strength loss within the first 20–30 days after soldering; then, the microstructure and mechanical properties changed more slowly over long periods of time. Further, by combining accelerated aging data and the microstructure-based kinetics, strength predictions were made that match well with the properties of the actual soldered assemblies naturally aged for 30 years. However, aging at the highest temperature of 135 °C produced anomalous behavior suggesting that extraneous aging mechanisms are active. Therefore, data obtained at this temperature or higher should not be used. Overall, the combined microstructural and mechanical property methods used in this study confirmed that the observed reduction in strength of ~ 30-year-old solder joints can be accounted for by the microstructural coarsening that takes place during long-term solid-state aging.

36 MATERIALS SCIENCE↗

Irradiation-induced grain boundary facet motion: In situ observations and atomic-scale mechanisms

Metals subjected to irradiation environments undergo microstructural evolution and concomitant degradation, yet the nanoscale mechanisms for such evolution remain elusive. Here, we combine in situ heavy ion irradiation, atomic resolution microscopy, and atomistic simulation to elucidate how radiation damage and interfacial defects interplay to control grain boundary (GB) motion. While classical notions of boundary evolution under irradiation rest on simple ideas of curvature-driven motion, the reality is far more complex. Focusing on an ion-irradiated Pt Σ3 GB, we show how this boundary evolves by the motion of 120° facet junctions separating nanoscale {112} facets. Our analysis considers the short- and mid-range ion interactions, which roughen the facets and induce local motion, and longer-range interactions associated with interfacial disconnections, which accommodate the intergranular misorientation. We suggest how climb of these disconnections could drive coordinated facet junction motion. These findings emphasize that both local and longer-range, collective interactions are important to understanding irradiation-induced interfacial evolution.

74 ATOMIC AND MOLECULAR PHYSICS↗

Anisotropic physics-regularized interpretable machine learning of microstructure evolution

Anisotropic Physics-Regularized Interpretable Machine Learning Microstructure Evolution (APRIMME) is a general-purpose machine learning solution for grain growth simulations. In prior work, PRIMME employed a deep neural network to predict site-specific migration as a function of its neighboring sites to model normal, isotropic, grain growth behavior. This work aims to extend this method by incorporating grain boundary misorientation-based grain growth behavior. APRIMME is trained on anisotropic simulations created using the Monte Carlo-Potts (MCP) model. Furthermore, the results of this work are compared statistically using grain radius, number of sides per grain, mean neighborhood misorientations, and the standard deviation of triple junction dihedral angles, and are found to match in most cases. The exceptions are small and seem to be related to two causes: (1) the deterministic model of APRIMME is learning from the stochastic simulations of MCP, which seems to accentuate triple junction behaviors; and, (2) a bias against very small grains is made evident in a quicker decrease in grains than expected at the beginning of an APRIMME simulation. APRIMME is also evaluated for its general ability to capture anisotropic grain growth behavior by first investigating different test case initial conditions, including a circle grain, three grain, and hexagonal grain microstructures.

36 MATERIALS SCIENCE↗

Unlocking superplasticity in medium and high-entropy alloys

Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.

klenam, Desmond [University of the Witwatersrand, ↗

Synergistic Effects of Molten Salt Corrosion and Proton Irradiation on Grain Boundary Strength in Ni-20Cr

Nickel-based alloys are leading contenders for use as structural materials in molten salt reactors. While there have been extensive studies on the impact of fluoride/chloride-based molten salt corrosion on the microstructural evolution of various nickel-based alloys, the effects of simultaneous molten salt corrosion and radiation on the mechanical integrity of grain boundaries (GBs) remain underexplored. In this study, we use a Ni-20Cr model alloy to investigate this issue, subjecting it to simultaneous molten fluoride salt corrosion and proton irradiation. We performed cross-sectional and chemically-sensitive electron microscopy characterization of the microstructures of these materials, identifying the characteristic corrosion-induced microstructure and local chemical heterogeneity near GBs. After developing a sample preparation method for reliable characterization of GB strength, we assess the mechanical degradation of GBs using in situ push-to-pull micro tensile tests. Our findings reveal that voids induced by corrosion are the primary influence on the failure mode of GBs, regardless of whether proton irradiation is present. For materials that exhibit ductile fracture, those subjected to simultaneous corrosion and radiation exhibit lower yield strengths than those exposed to corrosion alone, which may be linked to the previously observed phenomenon of proton irradiation-decelerated intergranular corrosion in molten salt.

36 - MATERIALS SCIENCE↗

Accelerate microstructure evolution simulation using graph neural networks with adaptive spatiotemporal resolution

Abstract Surrogate models driven by sizeable datasets and scientific machine-learning methods have emerged as an attractive microstructure simulation tool with the potential to deliver predictive microstructure evolution dynamics with huge savings in computational costs. Taking 2D and 3D grain growth simulations as an example, we present a completely overhauled computational framework based on graph neural networks with not only excellent agreement to both the ground truth phase-field methods and theoretical predictions, but enhanced accuracy and efficiency compared to previous works based on convolutional neural networks. These improvements can be attributed to the graph representation, both improved predictive power and a more flexible data structure amenable to adaptive mesh refinement. As the simulated microstructures coarsen, our method can adaptively adopt remeshed grids and larger timesteps to achieve further speedup. The data-to-model pipeline with training procedures together with the source codes are provided.

36 MATERIALS SCIENCE↗

In situ irradiation of spent nuclear fuels

To improve the economics of commercial nuclear reactors, nuclear vendors and utilities are seeking approval for increased burnup usage of the existing nuclear fleet. This is especially critical for meeting the clean energy initiative by the United States Government, Department of Energy (DOE). However, one of the key challenges the nuclear industry faces in this regard is that the regions exposed to high burnup and low temperatures exhibit a fine-grained microstructure with large bubbles known as high-burnup structure (HBS) [1]. The formation of HBS has been correlated to the diminished performance of the reactor, as well as fuel fragmentation and pulverization during transient and accidental conditions [2]. Therefore, it is paramount to understand the mechanisms for HBS formation along with its impact on the properties and performance of nuclear fuels. While existing programs, such as Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuel Campaign (AFC) are focusing on evaluating the performance impact of HBS, the physical mechanisms contributing to HBS formation are still not fully understood. In addition, having predictive capabilities and sound understanding of the microstructural evolution of nuclear fuel is essential for accelerated development, qualification, and deployment of new nuclear materials and novel reactor designs for advanced nuclear reactors. There is a lack of consensus among researchers regarding the mechanisms leading to such restructuring observed in HBS. Grain subdivision due to polygonization versus recrystallization, continuous versus discrete recrystallization occurring in tandem or conjunction, etc., have been proposed and debated. In general, it is hypothesized that defect accumulation and dislocation interaction within the grains cause the realignment of dislocations into grain boundaries, leading to the new subgrain formation, which over time transforms into new grains. However, due to the lack of transient data, the importance of fission rate, irradiation, thermal, and stress history of the fuel on the restructuring could not be assessed. In situ microstructural evolution under various irradiation conditions is desired to bridge this gap. Alternatively, phase-field-based models have been developed to capture HBS formation via discrete recrystallization utilizing the classical nucleation approach [3–5]. However, in these models, the grain nucleation criteria are often defined based on empirical relations for burnup and fission gas density leading to dislocation density change. A mechanistic approach to capture the dislocation interaction with the microstructural features leading to grain subdivision is lacking.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine learned interatomic potential for dispersion strengthened plasma facing components

Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high brittle-to-ductile transition temperature, and at fusion reactor temperatures (≥1000 K), it may undergo recrystallization and grain growth. Dispersion-strengthening W with zirconium carbide (ZrC) can improve ductility and limit grain growth, but much of the effects of the dispersoids on microstructural evolution and thermomechanical properties at high temperatures are still unknown. We present a machine learned Spectral Neighbor Analysis Potential for W–ZrC that can now be used to study these materials. In order to construct a potential suitable for large-scale atomistic simulations at fusion reactor temperatures, it is necessary to train on ab initio data generated for a diverse set of structures, chemical environments, and temperatures. Further accuracy and stability tests of the potential were achieved using objective functions for both material properties and high temperature stability. Additionally, validation of lattice parameters, surface energies, bulk moduli, and thermal expansion is confirmed on the optimized potential. Tensile tests of W/ZrC bicrystals show that although the W(110)–ZrC(111) C-terminated bicrystal has the highest ultimate tensile strength (UTS) at room temperature, observed strength decreases with increasing temperature. At 2500 K, the terminating C layer diffuses into the W, resulting in a weaker W–Zr interface. Meanwhile, the W(110)–ZrC(111) Zr-terminated bicrystal has the highest UTS at 2500 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heterogeneous microstructural evolution during hydrodynamic penetration of a high-velocity copper microparticle impacting copper

Microparticle hydrodynamic penetration (HDP) may be associated with the erosion regime in cold spray processing and other high-velocity impact events. Here, in an experimental approach where we can individually launch particles and study the impact sites, we explore copper microparticles impacted on copper substrates at velocities above 900 m/s where HDP begins. We lift cross-sectional lamellae from the impact sites with a focused-ion beam for further microstructural characterization using electron backscatter diffraction and scanning transmission electron microscopy. Due to the gradients of strain, strain rate, and temperature associated with HDP, heterogeneous microstructures result. The structural evolution processes observed include deformation twinning and multiple dislocation-mediated grain recrystallization mechanisms—geometric dynamic recrystallization (gDRX), discontinuous DRX (dDRX), and meta DRX (mDRX). The higher strains at the interface lead to the most significant structural changes and complex mechanisms. In contrast, there is a gradient to more conventional dislocation plasticity away from the interface (on either the particle or substrate side). Here, these microstructural observations are consistent with the deformation map for copper and extend the observations of impact-induced recrystallization across new regimes of behavior.

Cold spray process↗

Predicting microstructurally sensitive fatigue‐crack path in WE43 magnesium using high‐fidelity numerical modeling and three‐dimensional experimental characterization

Abstract Microstructurally small fatigue‐crack growth in polycrystalline materials is highly three‐dimensional due to sensitivity to local microstructural features (e.g., grains). One requirement for modeling microstructurally sensitive crack propagation is establishing the criteria that govern crack evolution, including crack deflection. Here, a high‐fidelity finite‐element modeling framework is used to assess the performance and validity of various crack‐growth criteria, including slip‐based metrics (e.g., fatigue‐indicator parameters), as potential criteria for predicting three‐dimensional crack paths in polycrystalline materials. The modeling framework represents cracks as geometrically explicit discontinuities and involves voxel‐based remeshing, mesh‐gradation control, and a crystal‐plasticity constitutive model. The predictions are compared to experimental measurements of WE43 magnesium samples subject to fatigue loading, for which three‐dimensional grain structures and fatigue‐crack surfaces were measured post‐mortem using near‐field high‐energy x‐ray diffraction microscopy and x‐ray computed tomography. Findings from this work are expected to improve the predictive capabilities of simulations involving microstructurally small fatigue‐crack growth in polycrystalline materials.

Engineering↗

Microstructural design in low alloy steels

The evolution of microalloyed steels from plain carbon steels is examined with emphasis on grain size control by use of Nb, Ti and V additions and by the application of controlled rolling. The structural changes during controlled rolling are described as well as the influence of alloying elements on these changes, and on the final microstructure. The achievement of high strength and toughness is discussed including the role of inclusions.

Honeycombe, R. W. K.↗

Microstructure and texture evolution of friction stir lap welded dissimilar multi-aluminum stack

Here this work investigates the microstructural evolution of a dissimilar multiple-aluminum alloy stack (AA7055, AA7055, AA6022) produced by friction stir lap welding (FSLW). A through-thickness analyses of grain orientation map, grain size and distribution, strain distribution, and texture evolution by electron backscattered diffraction-based characterization technique were performed. Two different welding parameters (combination of tool rotation and traverse speed) were used to study the effects of the welding parameters on these microstructural characteristics. The study shows that higher welding speed and higher rotation speed of the FSLW tool yield finer grains. FSLW resulted in shear texture formation in the weld regions due to high welding speeds. This texture development in the nugget zone is consistent with shear deformation, and (111) pole figures show ideal shear texture components. The Stir Zone (SZ) exhibits shear texture (A/A ̅ and B/B ̅ components), consistent with other shear-assisted processes. Recrystallization mechanisms observed are CDRX in SZ and DDRX in TMAZ (Thermo-Mechanically Affected Zone). Interface analysis reveals the presence of oxide layers between different aluminum sheets, affecting joint mechanical performance. The mechanical property of the lap welded joints was presented in terms of microhardness distribution across the weld cross section. Slightly higher hardness in higher speed welding setup was observed throughout the SZ and AA6022 layer, indicating greater grain refinement and uniform grain structure distribution.

36 MATERIALS SCIENCE↗

Defect Production and Microstructural Feature Impact for Radiation Damage in Additively Manufactured 316 Stainless Steel

This milestone presents multi-scale modeling research results for additively manufactured 316 stainless steel. A combination of phase field, cluster dynamics, molecular dynamics, and density functional theory with machine learning is used, allowing for predictions of radiation-driven microstructural evolution in additively manufactured 316 stainless steel over a range of temperatures, damage rates, neutron spectra, and microstructures, and supporting the development of combined ion and neutron irradiation for material qualification. Informed by ion irradiation and neutron irradiation results across the Advanced Materials and Manufacturing Technologies program, we investigate the unique aspects of radiation-driven microstructure evolution in additively manufactured 316 stainless steel. In particular, we focus on understanding the impact of carbon concentration (varying, for example, between the 316L and 316H standards) on void formation; radiation-induced segregation at dislocation cells and grain boundaries; and the evolution of dislocation loops and network dislocation populations. We find that the unique characteristics of the additively manufactured microstructures must be accounted for in understanding the evolution of dislocation populations under thermal and irradiation conditions, such as the variation in sink strengths arising due to the variation in dislocation density. We also find that the radiation-induced segregation of Cr and Ni to grain boundaries and cell walls differs due to the differences in their defect sink biases. We also find that increasing the Ni content can slow vacancy diffusion, which may provide a mechanism for the observed reduction in transient swelling rate for austenitic Fe-Cr-Ni alloys with increasing Ni content. In addition, ion irradiations have shown that increasing carbon content in 316 SS results in a larger population of smaller voids, suggesting reduced vacancy diffusion. Our results show that the carbon content of additively manufactured 316 SS has a significant impact on the migration rate of defect clusters. The presence of carbon atoms results in carbon-vacancy trapping, significantly reducing the diffusion rate of vacancies. Carbon atoms may also be trapped near the surface of a void, which may reduce void growth by trapping vacancies that diffuse toward the void.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Phase-field modeling of aging-induced microstructure evolution in pentaerythritol tetranitrate thin films and ramifications for shock initiation

Aging of energetic materials may change performance and affect their safety and reliability, but the relationship between microstructure changes induced by aging and consequent performance changes has not been fully established. This work presents results of phase-field method simulations used to model microstructure evolution of vapor-deposited pentaerythritol tetranitrate (PETN) thin films. Simulated aging is shown to induce grain coarsening and substantial changes of the configuration of porosity in the film: Specifically, we show that porosity tends to concentrate in large pores to a greater degree in aged films, a state that is arrived at by closure or consolidation of small pores. To evaluate the performance of the as-deposited and aged films, we perform two-dimensional hydrocode flyer-film impact simulations that incorporate the phase-field output microstructures directly, permitting us to connect features therein to changes in reactivity, a key metric of energy output for shock initiation. The results demonstrate that declining sensitivity obtained for the simulated aged films can be correlated with the loss of fine-structured pores relatively early in the aging process, while long-term microstructure evolution that gradually alters the shape of large, branching pores is less impactful. Finally, we discuss commonalities and discrepancies between our simulation results and high-throughput initiation experiments on shock initiation of aged PETN thin films.

36 MATERIALS SCIENCE↗

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

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↗