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At least 73 records · Page 4

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗

Neutron Irradiation Induced Changes in Isotopic Abundance of 6Li and 3D Nanoscale Distribution of Tritium in LiAlO2 Pellets Analyzed by Atom Probe Tomography

Tritium, a radioactive isotope of hydrogen is produced by neutron irradiation of 6Li enriched LiAlO2 pellets in Tritium producing burnable absorber rods (TPBARs). Three-dimensional nanoscale mapping of Tritium in irradiated pellets is critical to understand its spatial variation and its association with various microstructural features in the pellets. Spatially resolved analysis of 6Li isotopic enrichment in such ceramic pellets before and after irradiation can provide insights to heterogeneities in Li isotopic distribution. However, Li being a light isotope, its spatially resolved compositional or isotopic analysis is a challenging task to most analytical methods. Here we used atom probe tomography, to evaluate the Li isotopic enrichment in both the LiAlO¬2 matrix and the Li deficient secondary phase LiAl5O8 before irradiation. These results were then compared with 6Li isotopic ratio measured by APT analysis of neutron irradiated pellets to clearly demonstrate the unique capability of APT to quantitatively analyze the isotopic enrichment of 6Li as well as for other light elements present in these materials. Evidence for heterogenous nanoscale distribution of 3H and O3H within irradiated pellet microstructure is also provided, which is attributed to 3H trapping in irradiation induced vacancy clusters or voids within the LiAlO2 matrix. The characterization results given here, now prove the feasibility for using APT for analyzing nanoscale spatially resolved isotopic enrichment of Li as well as other light elements such as Tritium in TPBARs. This work also paves way to adopt APT for analyzing light elements such as Li and tritium in materials used for nuclear fusion reactor applications, geochemistry, astrophysics as well as for energy storage applications.

Devaraj, Arun↗

Irradiation-induced chemical disordering in ceramics: The case of SiC

Chemical disordering is one feature of damage that occurs in irradiation environments and is common in ceramic compounds. This paper reviews irradiation-induced chemical disordering in SiC-based materials at elevated temperatures. Here the results were obtained using advanced analytical tools to characterize atomistic defects and to evaluate the chemistry of defect clusters and homonuclear bond structures. Finally, this paper demonstrates that chemical disordering is crucial to understanding microstructural stability and establishing a mechanistic modeling of microstructural evolution of irradiated SiC.

36 MATERIALS SCIENCE↗

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2600+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6,000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with great emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with a suite of experimental data obtained from x-ray diffraction, infrared spectroscopy, spectroscopic ellipsometry and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗

Atom Probe Tomography Investigation of Clustering in Model P 2 O 5 -Doped Borosilicate Glasses for Nuclear Waste Vitrification

Atom probe tomography (APT) has been utilized to investigate the microstructure of two model borosilicate glasses designed to understand the solubility limits of phosphorous pentoxide (P 2 O 5 ). This component is found in certain high-level radioactive defence wastes destined for vitrification, where phase separation can potentially lead to a number of issues relating to the processing of the glass and its long-term chemical and structural stability. The development of suitable focused ion beam (FIB)-preparation routes and APT analysis conditions were initially determined for the model glasses, before examining their detailed microstructures. In a 3.0 mol% P 2 O 5 -doped glass, both visual inspection and sensitive statistical analysis of the APT data show homogeneous microstructures, while raising the content to 4.0 mol% initiates the formation of phosphorus-enriched nanoscale precipitates. This study confirms the expected inhomogeneities and phase separation of these glasses and offers routes to characterizing these at near-atomic scale resolution using APT.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks

Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.

Sun, Yixuan (ORCID:0000000311093380)↗

Mechanisms for high creep resistance in alumina forming austenitic (AFA) alloys

Castable alumina forming austenitic (AFA) alloys have demonstrated superior creep life and oxidation resistance at temperatures exceeding 800⁰C. Despite the success in the applicability of these alloys in extreme environments, there is a limited understanding of the deformation modes and the influence of each alloying element guiding the alloy design strategies that could further enhance the creep strength of these AFA alloys, particularly at temperatures at and above 900⁰C. In this study, we reveal the mechanism underpinning the superior creep performance of castable AFA alloys that involves suppressing primary carbide formation through minor compositional modification. This approach results in a three-fold increase in creep strength at 900⁰C and 50 MPa. Here, by employing integrated characterization techniques, we analyzed the microstructures of two AFA alloys, both before and after the creep process. We discovered that the suppression of primary carbides permits the in-situ clustering of now-available interstitial elements such as C, Si, and O during high-temperature creep. This improved solid solution strengthening and reduced stacking fault energy of the alloy. Moreover, it also enabled controlled secondary carbide formation during testing, further improving the creep resistance. These findings underline the important interplay between alloy composition, microstructure, and creep properties, and offer a promising design strategy for developing economical high-temperature Fe-based alloys suitable for advanced applications.

36 MATERIALS SCIENCE↗

Adversarial Ensemble Modeling of Multi-modal Mechanical Properties for Iron-Based Alloys

Mechanical properties of alloys are controlled by their microstructure; and microstructure evolution is controlled by internal and external stressors. Chemical complexity during the alloy processing may result in heterogeneity and observation of multimodal performance patterns. Thus, to ensure the desired performance of stressed components it is important to understand the origin and mechanisms of such behavior. Adversarial ensemble modeling was introduced here to explain multimodal mechanical properties of the iron-based alloys. The modeling results showed that the areas of a single mechanism predominance were contiguous across the alloy compositions clustered by similarity, with sharp and persistent boundaries separating the single-mechanism domains. The marginal compositions resulted in increased competition between the adversarial models but only led to the multimodal behavior when the competing models diverged. Transparency of the clustering method allowed explicit interpretation of the chemistries leading to such competition. The adversarial ensemble was interpreted through transition from ductile to brittle microstructure.

36 MATERIALS SCIENCE↗

The interpenetration polymer network in a cement paste–waterborne epoxy system

The formation of the interpenetrating polymer network (IPN) structure within the cement-polymer system has been revealed by experiments from 2 dimensional to 3-dimensional scales. However, the microstructure design and performance prediction of IPN as a function of specific C-S-H/polymer components or ingredients' parameters e.g. water to cement ratios (w/c), polymer to cement ratios (p/c), monomer components, degree of polymerization (DP), etc. is by far not available. Here we developed a mesoscale model for IPN visualization based on the Flory-Huggins interaction theory which was applied to cement science for the first time. All the ingredients in the micro-structure were considered as soluble beads with rational sizes based on their properties obtained by molecular dynamic methods. The interaction parameters of each bead were then determined based on their element ratios and chemical backbones. The model was validated with the waterborne epoxy-cement material (WECM) in which a novel waterborne epoxy resin (WEP) was prepared and impregnated. The verification results on the 2D-3D scale show that the developed model predicts the WECM's IPN structures by rule and line concerning DP, w/c, and p/c in the mixture. The C-S-H beads were progressively scaled in size which alters the C-S-H texture to have completely different dissolution characteristics. Beads of diameter ~6 Å are more unstable and soluble which enable them to form a continuous phase in water or a composite structure with WEP. In contrast, beads with diameters larger than 10 Å have different properties with stronger nucleation effects. The results also suggest the impregnation content of WEP in cement-based material should be limited to 10% vol. to prevent the polymer IPN from decomposing into discrete clusters. The application of Flory-Huggins theory in cement-based composites demonstrates great potential in performance prediction and microstructure design.

36 MATERIALS SCIENCE↗

Cluster dynamics modeling of Mn-Ni-Si precipitates coupled with radiation-induced segregation in low-Cu reactor pressure vessel steels

Formation of precipitates enhanced or induced by irradiation causes hardening and embrittlement of nuclear structural materials. Post-irradiation microstructure characterization of reactor pressure vessel (RPV) steels has shown that precipitation can be strongly associated with radiation-induced segregation (RIS) of solutes on dislocations. However, RIS and precipitation have not been coupled in previous precipitation modeling of RPV steels. Here in this study, a new hybrid and spatially-dependent precipitation model is developed that couples cluster dynamics with RIS, providing an unique way to account for concurrent evolution of heterogeneous cluster densities as well as solute and point defect concentration profiles. The model is applied to study the segregation of Mn, Ni, and Si on dislocations and heterogeneous nucleation of Mn-Ni-Si rich precipitates (MNSPs) in a low-Cu RPV steel. The result shows that the onset of MNSP nucleation on dislocations occurs at the fluence of 2 x 10 23 n.m -2 . The number density and mean radius can reach ~ 10 24 m -3 and 1-2 nm at high fluence, respectively. These observations suggest that the role of RIS and heterogeneous nucleation can be significant for RPV steels under a high fluence of irradiation. Results of simulations adopting various dose rates and dislocation densities show an increased fraction of MNSPs on dislocations at the condition of low dose rate, high dislocation density, and high fluence.

36 MATERIALS SCIENCE↗

In situ molecular imaging of adsorbed protein films in water indicating hydrophobicity and hydrophilicity

Abstract In situ molecular imaging of protein films adsorbed on a solid surface in water was realized by using a vacuum compatible microfluidic interface and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Amino acid fragments from such hydrated protein films are observed and identified in the positive ion mode and the results are in agreement with reported works on dry protein films. Moreover, water clusters from the hydrated protein films have been observed and identified in both the positive and negative ion mode for a series protein films. Thus, the detailed composition of amino acids and water molecules in the hydrated protein films can be characterized, and the protein water microstructures can be revealed by the distinct three-dimensional spatial distribution reconstructed from in situ liquid ToF-SIMS molecular imaging. Furthermore, spectral principal component analysis of amino acid fragment peaks and water cluster peaks provides unique insights into the water cluster distribution, hydrophilicity, and hydrophobicity of hydrated adsorbed protein films in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neutron irradiation induced defects and clustering in NF616 and T91

NF616 is a third-generation ferritic martensitic steel, developed to have better creep resistance than the prior generation T91. Unlike relatively numerous studies of T91, there is a lack of understanding of the irradiation effect on the microstructural evolution and mechanical response of NF616. This work evaluated the microstructures and radiation hardening of NF616 irradiated up to 8.2 displacement per atom (dpa) at 292 °C – 431 °C, compared with T91 from two heats. Dislocation loops were observed in all investigated samples. NF616 exhibited comparable loop size but slightly lower loop density than those in the general T91 heat at 430 °C. Cavities were only observed in NF616 at 431 °C but absent at lower irradiation temperatures (292 °C and 359 °C). Ni-rich clusters were also observed in NF616 at 431 °C, while only weak Ni-clustering were observed at lower irradiation temperatures. Compared to the general T91 heat, NF616 demonstrated better swelling resistance (e.g., one third of swelling in the general T91 heat at 430 °C), a slightly higher number density of Ni-rich clusters, and slightly lower radiation hardening. The low-carbon T91 showed the greatest hardening with the largest swelling and loop sizes, despite its lowest irradiation temperature and intermediate dose. The calculated hardening from loops, cavities and Ni-rich clusters using the classic dispersed barrier-hardening model had reasonable agreement with the experiment-derived results, with the primary hardening contribution attributed to dislocation loops.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Combinatorial Exploration and Mapping of Phase Transformation in a Ni–Ti–Co Thin Film Library

Combinatorial synthesis and high-throughput characterization of a Ni–Ti–Co thin film materials library are reported for exploration of reversible martensitic transformation. The library was prepared by magnetron co-sputtering, annealed in vacuum at 500 °C without atmospheric exposure, and evaluated for shape memory behavior as an indicator of transformation. Composition, structure, and transformation behavior of the 177 pads in the library were characterized using high-throughput wavelength dispersive spectroscopy (WDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and four-point probe temperature-dependent resistance (R(T)) measurements. A new, expanded composition space having phase transformation with low thermal hysteresis and Co > 10 at. % is found. Unsupervised machine learning methods of hierarchical clustering were employed to streamline data processing of the large XRD and XPS data sets. Through cluster analysis of XRD data, we identified and mapped the constituent structural phases. Finally, composition–structure–property maps for the ternary system are made to correlate the functional properties to the local microstructure and composition of the Ni–Ti–Co thin film library.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ TEM annealing of neutron-irradiated Ti reveals a two-stage mechanism for elevated temperature radiation damage recovery

Understanding how irradiation-induced defects evolve at elevated temperatures is of critical importance to predicting materials' behavior under steady-state and accident scenarios. However, such mechanistic insight into microstructural evolution is limited by the nature of ex situ annealing and subsequent imaging. Here we show direct observation and quantification of defect recovery in neutron-irradiated Ti using in situ transmission electron microscopy (TEM) annealing experiments. In agreement with our prior work, and at temperatures below the irradiation temperature (T irr = 300 °C), dislocation loops are observed to glide. At elevated temperatures (>500 °C), dislocation lines become mobile and promote significant recovery of the microstructure. These mechanisms challenge the established electron irradiation-based model for radiation damage recovery, which originally suggests dissolution of static defect clusters, and demonstrates the importance of in situ characterization in understanding defect evolution in irradiated materials.

Hirst, Charles A. [Univ. of Michigan, Ann Arbor, M↗

Interpreting experimental measurements of helium bubbles using stochastic cluster dynamics models of heterogeneous nucleation and growth in irradiated ferritic alloys

Among a number of other advantageous features, ferritic/martensitic steels are being considered as fusion reactor structural materials due to their low intrinsic swelling under irradiation. However, under high-energy neutron irradiation, He produced through (n, α) reactions stabilizes vacancy clusters, which then act as seeds for bubble formation and growth, negating the intrinsic swelling resistance of these alloys. Standard models of irradiation damage accumulation and microstructural evolution consider homogeneous nucleation as the basis for bubble formation and growth. However, this generally does not explain the large bubble densities and sizes observed experimentally under a number of different conditions. Here, we propose a more realistic physical model of bubble nucleation, formation, and growth designed to capture recent experimental measurements of He-bubble formation and evolution during co-implantation of He and Fe ions in model ferritic alloys. We find that experimental results are explained only when the following three features are considered simultaneously: (i) heterogeneous nucleation of He-vacancy bubbles at defect sinks (e.g., dislocations, grain boundaries, and second-phase precipitates), (ii) nucleation and growth of bubbles via the ‘trap mutation’ mechanism (i.e., spontaneous production of Frenkel pairs due to absorption of He atoms), and (iii) transition from a growth-limited, He-stabilized bubble regime to a ‘runaway’ void-type growth scenario. The model is implemented into a stochastic cluster dynamics framework that takes advantage of cluster size grouping methods to accelerate the simulations, allowing us to reach 10 dpa of simulated irradiated dose, and to capture cluster sizes in excess of 20 nm. Further, a careful extrapolation exercise conducted assuming classical nucleation theory leads to excellent agreement with the experimental measurements at 50 dpa of irradiation.

36 MATERIALS SCIENCE↗

Multi stage and illumination dependent segregation in MAPb(I,Br)3

© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. An unsolved problem of mixed halide perovskites is the light induced compositional instability. Under illumination microscopic clusters with a higher iodide content form which act as efficient recombination centers reducing device performance. In photoluminescence measurements this leads to the development of a secondary peak at low energies that increases in intensity and shifts towards lower energies. Different theories for about the origin have been developed but the underlying key mechanisms are still under debate. In the presented study the photoluminescence evolution of MAPb(I1.5Br1.5) perovskites with varying microstructure is investigated at various excitation densities and temperatures. We find a more evolved segregation mechanism with an intermediate stage between the commonly reported mixed phase and the appearance of the I-rich clusters (Br content < 50%). In this intermediate stage perovskite domains with nearly pure iodide content form (Br content < 25%). Using low excitation densities, the interplay between the I-rich domains and the I-rich clusters leads to a blue shift of the conjunct I-rich luminescence peak. At high excitation densities the I-rich domains and the I-rich clusters are clearly distinguishable, due to a stronger PL response of the I-rich domains. With continuous illumination more I-rich cluster form acting as carrier traps and recombination centers. Due to this, the influence of the few I-rich domains on the PL signature decreases leaving only the commonly reported red shift of the I-rich clusters at later stages of the segregation. The formation of the I-rich domains is fully reversible in the dark and occurs also at elevated temperatures. Measurements on sample with varying grain size further indicate an enhanced formation of those I-rich domains on samples with high grain boundary density possibly by a faster halide mobility along them.

Babbe, F↗

Clustering Algorithm for AM Parts using GSH and EDT with Autoencoder

SAND2025-10103O The Clustering Algorithm for AM Parts Using GSH and (EDT With Autoencoder is a software tool. It uses a clustering algorithm for additive manufacturing (AM) parts using generalized spherical harmonics (GSH) and Euclidean distance transform (EDT) with an autoencoder to quantify material microstructure. The tool offers improved sensitivity to microstructural changes compared to traditional approaches. The tool integrates multiple microstructural properties, such as grain morphology, crystallographic orientation, and material phase information, to provide a comprehensive analysis of material microstructures. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rodgers, Theron [Sandia National Lab. (SNL-CA), Li↗

Phase stability and microstructure of neutron-irradiated substoichiometric yttrium dihydrides

The impact of the neutron-displacement damage on phase stability and microstructure of substoichiometric yttrium dihydrides (YH x , x <2) were investigated to assess their use as solid moderator in high-temperature nuclear reactors. YH x specimens were, thus, subjected to neutron irradiations in the range of 0.1–2 displacements per yttrium atom (dpa-Y) in the temperature range of 536–878°C at the Oak Ridge National Laboratory's (ORNL's) High Flux Isotope Reactor (HFIR). YH x specimens were initially prepared at stoichiometry (H/Y) ratios of 1.69 and 1.83. HFIR-irradiated specimens were characterized by variety of techniques to investigate H retention characteristics including dimensional analysis, optical microscopy, scanning electron microscopy electron back scatter diffraction (EBSD), transmission electron microscopy, thermal desorption spectroscopy (TDS), and high-energy x-ray diffraction (HE-XRD) characterizations. Overall, YH x exhibited notable structural and phase stability under short-term neutron-irradiation, except for the samples with significant silicon carbide (SiC) interaction at high doses and temperatures. Basic dimensional and mass measurements were misleading for accurate assessment of H retention, as confirmed by EBSD phase maps, XRD line profiles, and TDS signals. Thus, it was discussed that a robust H retention metric is needed to assess irradiated hydrides. Further, nanoscale cavities were observed as a result of the neutron irradiation in all samples. Although no clear impact of dose and irradiation temperature was determined, the initial H/Y ratio had an impact on the cavity number density where low H/Y specimens had high-resistance to cavity formation. The Y-vacancy cluster formation at the collision stage of the displacement cascade and their stabilization by H were considered to be the likely underlying mechanisms for the observed cavity microstructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗