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Data assimilation for microstructure evolution: Grain growth in kinetic Monte Carlo.
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Data assimilation for microstructure evolution: Grain growth in kinetic Monte Carlo
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The Heterogeneous Nature of Mechanically Accelerated Grain Growth
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Investigating the Grain Growth Kinetics of Sn-Modified PZT 95/5
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Probing Interstellar Grain Growth through Polarimetry in the Taurus Cloud Complex
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The grain growth of iron - Implications for the thermal conditions in a lunar ejecta blanket
The times and temperatures for the growth of single-domain to multidomain iron have been determined in a synthetic glass of Apollo 11 composition. All single-domain iron grows to multidomain iron under the following conditions: at 975 C in about 5 hours; at 900 C in about 18 days; at 810 C in about 320 days; and at 700 C in about 1100 years (extrapolated). The results, together with thermal constraints on the metamorphism of lunar breccias, indicate cooling rates of breccias containing single domain iron are appropriate for formation in an ejecta blanket.
Subsolidus reequilibration, grain growth, and compositional changes of native FeNi metal in lunar rocks
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The influence of grain growth in circumstellar dust envelopes on observed colors and polarization of some eruptive stars
R CrB stars are classical examples of stars where dust envelope formation takes place. Dust envelope formation was detected around the Kuwano-Honda object (PU Vul) in 1980 to 1981 when the star's brightness fell to 8(sup m). Such envelopes are also formed at nova outbursts. The process of dust envelope formation leads to appreciable variations in optical characteristics, which are seen in specific color and polarization variations in the course of light fading and the appearance of IR radiation. It is shown that the model of a circumstellar dust envelope with aligned particles of changing size can be successfully applied to explain most phenomena observed at the time of light minima for a number of eruptive stars. The polarization may arise in a nonspherical dust envelope or be produced by alignment of nonspherical particles.
Abnormal Grain Growth in S-816 Alloy
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Abnormal Grain Growth in Nickel-base Heat-resistant Alloys
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The Effect of Dispersoid Modification on Abnormal Grain Growth in Friction Stir Welded Al-Li 2195
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In-Situ Annealing of Pt-Au Alloys: Grain Growth with Temperature and Composition Dependence.
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Dynamic recrystallization of a wrought magnesium alloy: Grain size and texture maps and their application for mechanical behavior predictions
Effect of dynamic recrystallization (DRX) on the grain refinement and texture modification was studied by conducting a series of hot compression on AZ31B Mg alloy. Processing-grain size-texture maps were established as a function of temperature, strain rate, strain, and the Zener-Hollomon parameter (Z). Moreover, influence of simultaneous changes in the grain size and texture on tensile yield strength and ductility of the hot-worked Mg alloy was studied using the grain size and texture maps established. The processing-grain size map showed that the DRX grain size decreased with the increase in Z, also revealing various characteristics ranging from a grain growth, grain refinement, to a bimodal distribution of ultrafine grains and partially recrystallized grains. The effect of twinning on the grain refinement was also evident at high Z conditions. The processing-texture map revealed that the initial fiber texture was altered significantly to a shear, off-normal, or extension-twin texture with the increase in Z. The Schmid-factor maps were calculated to identify a dominant deformation mode during a subsequent tensile deformation of the hot-worked samples. Finally, a corresponding Hall-Petch relationship for each dominant deformation mode was used to establish tensile yield-strength maps, which agree well with the measured data.
UO2 microstructural evolutions induced by Ni, Mo, and W dopants for intentional forensics
The concept of tagging nuclear fuel with a chemical barcode to enable forensics analysis across the nuclear fuel cycle is an area of active investigation, particularly to ensure fabrication viability without disrupting current fuel performance. This study explored the feasibility of using Ni, Mo, and W isotopic double-spikes as dopants in UO2 fuel from the perspective of fuel fabrication. Doped UO2 pellets were produced using conventional fuel fabrication processes, including powder mixing, sieving, pressing, and sintering in a reductive atmosphere. Two composition levels, 100 and 1000 ppm, were evaluated for each dopant element with isotopic double-spike configurations. For the Ni system, additional dopant concentrations of 250 and 500 ppm were produced with nonperturbed isotopic ratios. The results demonstrated that successful incorporation of Ni, Mo, and W double-spikes into UO2 pellets occurred with minimal shift in final density or dopant loss during pellet fabrication. Isotopic analysis confirmed the presence of the double-spike signature even when diluted with natural isotopic material in ratio of 1:5 in the fabrication process. Microstructural examinations revealed different impacts on grain size compared with undoped UO2. This study showed that Ni incorporation up to ∼500 ppm promoted moderate grain growth, whereas the Mo and W systems caused grain size reduction at all concentrations. Changes in the UO2 lattice parameter as a function of composition were detected exclusively for Ni up to 500 ppm, indicating that the Ni solid solution was the main factor for the observed grain growth. Insoluble (Mo and W) or supersaturated (Ni > 500 ppm) conditions produced grain size reduction. The Ni-doped pellets in the solution range resulted in a final microstructure within fuel specifications, demonstrating its potential benefits of employing complex dopant systems for potential nuclear forensic applications.
Molecular dynamics studies of grain boundary mobility and anisotropy in BCC γ-uranium
Grain morphologies such as grain size and aspect ratio in uranium-based metallic fuels are important microstructural features that can impact various fuel performance properties such as fission-gas-induced swelling, thermal transport, high burnup structure formation, and radiation resistance. Accurate prediction of the fuel grain morphologies requires knowledge of critical grain growth parameters such as grain boundary (GB) mobility and anisotropy. In this work, molecular dynamics simulations were performed to study the GB mobility and its anisotropy in pure body-centered-cubic (BCC) γ uranium. Nine GBs with different combinations of misorientation angles (20°, 30°, 45°) and rotation axes (<100>, <110>, <111>), as well as an additional <111> 38.2° GB were studied using three interatomic potentials. Here, it is found that the GB mobility anisotropy has complex trends, depending on both rotation axis and misorientation. However, in general the <110> rotation axis has the fastest GB mobility at the same misorientation. The results of this work can be used as not only baselines for future studies of GB mobility in uranium-based alloys such as uranium-molybdenum (U-Mo) fuels, but also input for mesoscale modeling of grain growth in uranium-based alloys.
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.