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DOE OSTI2024

Multiscale, mechanistic modeling of irradiation-enhanced silver diffusion in TRISO particles

Tristructural isotropic (TRISO) particles are under consideration for use in several proposed advanced nuclear reactor concepts. The silicon carbide (SiC) layer in TRISO acts as a barrier to prevent the release of the fission products. However, despite remarkable retention, silver (Ag) release has been observed from intact particles, which requires investigation since the Ag isotope ( 110m Ag) has a long half-life. Previous work focused on developing a multiscale, mechanistic model for Ag diffusion accounting for temperature and microstructure effect and has been successfully validated. In this work, we expand the previous model to account for irradiation-enhanced Ag diffusivity in SiC and improve its accuracy over a wider grain size and temperature ranges relevant for advanced reactor conditions. A temperature, grain size, and flux dependent diffusivity is therefore derived using the mesoscale code MARMOT and implemented in the fuel performance code BISON. The irradiation-enhanced Ag diffusivity in SiC is compared against experimental data and validated using BISON against Ag release measurements from the Advanced Gas Reactor Fuel Development and Qualification Program (AGR-1 and AGR-2). Herein, we quantify the impact of SiC grain size, irradiation, and temperature on Ag release. In agreement with previous studies, we find accounting for SiC grain size improves agreement between BISON predictions and experimental observations for most cases. In conclusion, we also find that accounting for irradiation improves agreement for cases where Ag release was underestimated, but the impact was less significant than accounting for microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2012

Development of Matrix Microstructures in UHTC Composites

One of the major issues hindering the use of ultra high temperature ceramics for aerospace applications is low fracture toughness. There is considerable interest in developing fiber-reinforced composites to improve fracture toughness. Considerable knowledge has been gained in controlling and improving the microstructure of monolithic UHTCs, and this paper addresses the question of transferring that knowledge to composites. Some model composites have been made and the microstructures of the matrix developed has been explored and compared to the microstructure of monolithic materials in the hafnium diboride/silicon carbide family. Both 2D and 3D weaves have been impregnated and processed.

Johnson, Sylvia↗

DOE OSTI2024

Deep operator network surrogate for phase-field modeling of metal grain growth during solidification

A deep operator network (DeepONet) has been constructed that generates accurate representations of phase-field model simulations for evolving two dimensional metal grain morphology growing from melt. These representations serve as lower resolution, computationally efficient stand-ins for quick parameter space exploration of solutions to the the Allen-Cahn equations that dictate the phase-field model simulations. The experimental target for the phase-field model is a uranium casting system cooling a 434 g uranium charge from a maximum temperature of 1400° C at an average rate of 30° C / min , traversing the crystallographic phases of the pure metal. Experimental parameters inform the phase-field model, whose higher resolution computational model solutions are used to train the DeepONet in a given parameter space with the aim of developing a faster, more efficient method for predicting the solidifying metal's microstructure at different potential experimental values. The final DeepONet generates high accuracy, lower resolution predictions with cumulative relative approximation error over all timesteps of less than 0.5%, while ensuring solutions remain within physically feasible ranges. Further, these relative error values are comparable with other state-of-the-art DeepONet models for microstructure evolution, while significantly reducing the amount of training data required. Training a convolutional neural network simultaneously with the DeepONet, enforcing realistic values at the complex metal grain boundaries, and mathematically encoding boundary conditions into the structure of the DeepONet improved prediction accuracy and computational efficiency over a standard DeepONet model.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

DOE OSTI2023

Slip localization behavior at triple junctions in nickel-base superalloys

Incipient slip localization in the vicinity of hundreds of grain boundary triple junctions (TJs) in a lightly deformed nickel-base superalloy IN718 is studied using a combination of three-dimensional (3D) crystal plasticity finite element (CPFE) modeling, high resolution digital image correlation (HR-DIC) and 3D electron back-scatter diffraction tomography (3D EBSD). A 3D reconstruction method enables identification of thousands of TJs and correspondence of any observed slip bands with their originating TJ lines below the specimen surface. Here, we present a large-scale CPFE model of the experimental 3D microstructure composed of high-fidelity representation of the TJ lines and the boundaries and interiors of the parent grains and use it to calculate the local micromechanical response and slip activity of all TJs at the onset of macroscopic yielding. Statistical analysis of the calculated quantities reveal TJs develop larger stress concentration and grain-average re-orientation than grain interiors and grain boundaries, however no substantial differences in cumulative slip were found among these microstructural regions. We find that TJs with observed slip bands generate lower grain-average re-orientation, fewer active slip systems, and more localized slip on a single system than those without. The distinctions in the reorientation and slip activity are stronger in TJs that experience more intense slip.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Influence of fine-scale B2 precipitation on dynamic compression and wear properties in hypo-eutectic Al0.5CoCrFeNi high-entropy alloy

The near equiatomic high-entropy alloys based on Al, Co, Cr, Fe, Ni have provided a novel microstructural template for alloy design. The face-centered cubic (FCC) matrix strengthened by body-centered cubic (BCC) based ordered B2 precipitates can be used to develop a new generation of precipitation strengthened alloys. The present study focuses on an Al0.5CoCrFeNi hypo-eutectic alloy consisting of an as-solidified FCC+B2 microstructure. Guided by solution thermodynamic modeling, this alloy has been isothermally aged for solid-state precipitation of a high fraction of fine-scale intragranular B2 particles. The dynamic compressive strength, hardness, and sliding wear response of the alloy as a function of B2 phase fraction is examined. The flow stress at 0.02% true strain increased from ~ 670 MPa to ~1350 (102%) MPa, the ultimate compressive strength increased from ~1160 MPa to 1500 MPa (20%), and the wear resistance increased more than 5 times with progressively increasing phase fraction of B2 precipitates.

Gwalani, Bharat↗

DOE OSTI2024

Analysis of radially resolved thermal conductivity in high burnup mixed oxide fuel and comparison to thermal conductivity correlations implemented in fuel performance codes

The thermal diffusivity and thermal conductivity of high burnup (19 % FIMA) mixed oxide (U, Pu)O 2 nuclear fuel has been measured along the radial direction using a thermoreflectance-based method. Measured thermal conductivity exhibits a notable radial variation consistent with the expectations that a large temperature gradient across the annular fuel pellet leads to a heterogeneous microstructure. A common fuel performance model of thermal conductivity, the Lucuta-Inoue model, is used to analyze the measured thermal conductivity profile. Further, this model adequately captures the radial dependence of thermal conductivity except in the periphery. The analysis suggests that the characteristic radial shape of the thermal conductivity profile follows the burnup profile within the fuel pin. In the periphery, the high burnup structure is formed and the conductivity model, not capturing this effect, likely overestimates the thermal conductivity.

36 MATERIALS SCIENCE↗

DOE OSTI2021

From classical thermodynamics to phase-field method

Phase-field method is a density-based computational method at the mesoscale for modeling and predicting the temporal microstructure and property evolution during materials processes. The focus of this article is on connecting the most common phase-field equations to the very basic first and second laws of classical thermodynamics through rudimentary irreversible thermodynamics. It briefly discusses the relations of the continuum phase-field equations to their counter parts at the microscopic and atomic levels. It attempts to clarify the contributions of long-range elastic, electrostatic, and magnetic interactions to domain structure evolution during structural, ferroelectric, and ferromagnetic phase transformations by separating order parameter changes due to the presence of quasi-static fields and those arising from phase transformations. A few examples are presented to demonstrate the possibility of employing the phase-field method to provide guidance to designing materials for optimum properties or discovering novel mesoscale phenomena or new materials functionalities. Here, the article ends with a brief perspective on a number of potential future directions on the development and applications of phase-field method beyond its traditional applications to structural alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Synchrotron Imaging of Pore Formation in Li Metal Solid-State Batteries Aided by Machine Learning

High-rate capable, reversible lithium metal anodes are necessary for next generation energy storage systems. In situ tomography of Li/LLZO/Li cells is carried out to track morphological transformations in Li metal electrodes. Machine learning enables tracking the lithium metal morphology during galvanostatic cycling. Nonuniform lithium electrode kinetics are observed at both electrodes during cycling. Hot spots in lithium metal are correlated with microstructural anisotropy in LLZO. Mesoscale modeling reveals that regions with lower effective properties (transport and mechanical) are nuclei for failure. Advanced visualization combined with electrochemistry represents an important pathway toward resolving non-equilibrium effects that limit rate capabilities of solid-state batteries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Formation kinetics and thermodynamic stability of the Aurivillius compounds in Bi 4 Ti 3 O 12 –BiFeO 3 system

Abstract The Aurivillius compounds in the Bi 2 O 3 –Fe 2 O 3 –TiO 2 system, combining ferroelectric, semiconducting, and ferromagnetic properties, have attracted particular interest. Formation kinetics and thermodynamic stability are the fundamental knowledge needed for modeling and predicting the temporal microstructure and property evolution during materials processing but have not yet been addressed by quantitative experimental measurement. This article focuses on the Bi n +1 Fe n –3 Ti 3 O 3 n +3 Aurivillius compounds on the Bi 4 Ti 3 O 12 –BiFeO 3 tie‐line to elucidate the mechanisms and thermodynamic controls responsible for phase formation of compounds with various perovskite‐like layers. Five high‐purity Aurivillius compounds Bi 4 Ti 3 O 12 , Bi 5 FeTi 3 O 15 , Bi 6 Fe 2 Ti 3 O 18 , Bi 7 Fe 3 Ti 3 O 21 , and Bi 8 Fe 4 Ti 3 O 24 with integer n = 3–7 values were synthesized and their phase transformation properties and enthalpies of formation were studied by X‐ray diffraction in situ, high temperature differential scanning calorimetry, and high temperature oxide melt solution calorimetry. Thermodynamic stability of the compounds decreases with increasing n , and formation kinetics gradually slow down, demonstrating the inherent difficulty to synthesize pure Aurivillius compounds with n larger than 8. This difficulty was confirmed by an impurity phase coexisting with Bi 9 Fe 5 Ti 3 O 27 .

Gong, Weiping↗

DOE OSTI2020

Characterizing Performance of Electrocatalyst Nanoparticles Infiltrated into Ni-YSZ Cermet Anodes for Solid Oxide Fuel Cells

The infiltration of nanoparticle electrocatalysts into solid oxide fuel cell (SOFC) electrodes has been proven to produce a high density of electrochemically active sites, and reduce charge transfer polarization losses for SOFC electrodes. This is crucial for intermediate temperature operation, as these losses increase greatly at lower temperatures. Nickel-yttria stabilized zirconia (NiYSZ) cermets are low-cost, and exhibit excellent stability, but their main disadvantage stems from nickel coarsening and performance loss over their operational lifetimes. Infiltration of electrocatalyst nanoparticles has been shown to mitigate nickel coarsening and the consequent anode degradation. In this study, the effects of these infiltrants are observed in a standard Ni-YSZ electrode. In addition to nickel, mixed ionic and electronic conducting (MIEC) phases were infiltrated into Ni-YSZ scaffolds and their performances were characterized using electrochemical impedance spectroscopy (EIS). Cross-sectional microscopy of fractured cells was used to compare electrode microstructure and particle statistics. A model is proposed for how the nanoparticle electrocatalysts improve the anode performance.

25 ENERGY STORAGE↗

DOE OSTI2024

FY24 Advanced Computing HPC Annual Report for allocation "vtocei"

This project aims to elucidate the mechanisms underlying the formation of the cathodeelectrolyte interphase (CEI) and its impact on the performance of Li-ion batteries during electrochemical cycling. Our approach integrates advanced multiscale modeling with multimodal characterization to offer a comprehensive understanding of CEI dynamics. We employ a validated multiscale modeling framework to analyze microstructure-dependent transport properties, alongside joint theory-experiment protocols for detailed resolution of interfacial chemistry via spectroscopy.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

36 MATERIALS SCIENCE↗

NASA NTRS1982

Lunar and Planetary Science Conference, 12th, Houston, TX, March 16-20, 1981, Proceedings. Section 1 - The moon. Section 2 - Planets, asteroids and satellites

Topics related to the mineralogy and petrology of lunar pristine rocks are considered, along with subjects concerning the mineralogy and geochemistry of lunar breccias. Other studies considered are connected with the lunar regolith, lunar surface geology, and aspects of lunar structure and evolution. Investigations regarding meteorites are reported, and a description is provided of explorations of Mars and Venus, giving attention to regional geology, surface properties, and the composition of Venus. Studies of the Galilean satellites are related to an Io thermal model with intermittent volcanism, the microstructure and particulate properties of the surfaces of Io and Ganymede, the structures on Europa, the sputter-generation of planetary coronae, the tectonic deformation of Galileo Regio and limits to the planetary expansion of Ganymede, and dark-ray craters on Ganymede. Experimental and theoretical studies concerning impact cratering are also considered.

Merrill, R. B.↗

NASA NTRS1990

Oxidation characteristics of Ti-14Al-21Nb ingot alloy

Static oxidation kinetics of Ti14Al21Nb (wt pct) ingot alloy were studied in air over the temperature interval of 649 to 1093 C in a thermogravimetric apparatus. The oxidation products were characterized by x ray diffraction, electron microprobe analysis, energy dispersive x ray analysis, and Auger electron spectroscopy. Cross-sections of the oxidized samples were also examined using light and scanning electron microscopy. The oxidation rate was substantially lower than the conventional alloys of titanium, but the kinetics displayed a complex behavior involving two or more oxidation rates depending on the temperature and duration of exposure. The primary oxide formed was TiO2, but this oxide was doped with Nb. Small amounts of Al2O3 and TiN were also present in the scale. Diffusion of oxygen into the alloy was observed and the diffusivity seemed to be dependent on the microstructure of the metal. A model was presented to explain the oxidation behavior of the alloy in terms of the reduction in the oxygen diffusivity in the oxide caused by the modification of the defect structure of TiO2 by Nb ions.

Sankaran, Sankara N.↗

NASA NTRS1992

Environmental fatigue of an Al-Li-Cu alloy. Part 2: Microscopic hydrogen cracking processes

Based on a fractographic analysis of fatigue crack propagation (FCP) in Al-Li-Cu alloy 2090 stressed in a variety of inert and embrittling environments, microscopic crack paths are identified and correlated with intrinsic da/dN-delta K kinetics. FCP rates in 2090 are accelerated by hydrogen producing environments (pure water vapor, moist air, and aqueous NaCl), as defined in Part 1. For these cases, subgrain boundary fatigue cracking (SGC) dominates for delta K values where the crack tip process zone, a significant fraction of the cyclic plastic zone, is sufficiently large to envelop 5 micron subgrains in the unrecrystallized microstructure. SGC may be due to strong hydrogen trapping at T1 precipitates concentrated at sub-boundaries. At low delta K, the plastic zone diameter is smaller than the subgrain size and FCP progresses along (100) planes due to either local lattice decohesion or aluminum-lithium hydride cracking. For inert environments (vacuum, helium, and oxygen), or at high delta K where the hydrogen effect on da/dN is small, FCP is along (111) slip planes; this mode does not transition with increasing delta K and plastic zone size. The SGC and (100) crystallographic cracking modes, and the governing influence of the crack tip process zone volume (delta K), support hydrogen embrittlement rather than a surface film rupture and anodic dissolution mechanism for environmental FCP. Multi-sloped log da/dN-log delta K behavior is produced by changes in process zone hydrogen-microstructure interactions, and not by purely micromechanical-microstructure interactions, in contradiction to microstructural distance-based fatigue models.

Robert S Piascik↗

NASA NTRS2024

Constraining the Thermal and Textural Evolution of Evolved Achondrite DOM 10100: Implications for Volatile Loss

Identification of evolved achrondritic clasts suggests that some early planetesimals experienced extensive differentiation and formed chemically evolved crusts. Many of these samples contain volatile-bearing phases (i.e., apatite, merrillite, nominally anhydrous minerals), which can be used to constrain volatile budgets and abundancies via in-situ measurements. These ancient crustal rocks are subject to high heat, moderate pressures, potentially hot mineral-rich fluids, and degassing that has likely modified many of these volatiles, and their abundancies do not represent the composition of the primary magma from which these achondrites formed. In this work we attempt to deconvolve the thermal evolution of these samples to provide petrologic information that can be used for making inferences regarding their volatile history, and ultimately constraining volatile budgets on planetary bodies in the early Solar System. Here, we combine in-situ major element geochemistry, thermodynamic modeling, and detailed textural and microstructural observations to reconstruct the thermal and textural evolution of howardite DOM 10100, which contains a dacite within its matrix. Previous analyses of several sections of DOM 10100 suggest that the dacitic clast is evidence for partial melting of Vesta’s differentiated basaltic crust, making it an ideal candidate for evolved crustal studies. While its igneous petrogenesis has been well constrained, there is still opportunity to better characterize its post-crystallization thermal history, including possible thermal metamorphism and cooling.

J S Gorce↗