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DOE OSTI2025

High Radiation Resistance in the Binary W‐Ta System Through Small V Additions: A New Paradigm for Nuclear Fusion Materials

Abstract Refractory High‐Entropy Alloys (RHEAs) are promising candidates for structural materials in nuclear fusion reactors, where W‐based alloys are currently leading. Fusion materials must withstand extreme conditions, including i) severe radiation damage from energetic neutrons, ii) embrittlement due to H and He ion implantation, and iii) exposure to high temperatures and thermal gradients. Recent RHEAs, such as WTaCrV and WTaCrVHf, have shown superior radiation tolerance and microstructural stability compared to pure W, but their multi‐element compositions complicate bulk fabrication and limit practical use. In this study, it is demonstrated that reducing alloying elements in RHEAs is feasible without compromising radiation tolerance. Herein, two Highly Concentrated Refractory Alloys (HCRAs) − W 53 Ta 44 V 3 and W 53 Ta 42 V 5 (at.%) − were synthesized and investigated. We found that small V additions significantly influence the radiation response of the binary W–Ta system. Experimental results, supported by ab‐initio Monte Carlo simulations and machine‐learning‐driven molecular dynamics, reveal that minor variations in V content enhance Ta–V chemical short‐range order (CSRO), improving radiation resistance in the W 53 Ta 42 V 5 HCRA. By focusing on reducing chemical complexity and the number of alloying elements, the conventional high‐entropy alloy paradigm is challenged, suggesting a new approach to designing simplified multi‐component alloys with refractory properties for thermonuclear fusion applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Understanding Oxide–Metal Interactions During Hot Isostatic Pressing to Diffusion Bond Aluminum Alloy 6061 Plates

The interaction between Mg, Si, and Al 2 O 3 during hot isostatic pressing diffusion bonding of aluminum alloy 6061 (AA6061) plates was investigated through thermodynamic calculations and experimental microstructural characterization. Thermodynamic calculations as functions of temperature, pressure, and composition revealed that the interaction among Mg, Si, and Al 2 O 3 yields Mg 2 Si and either MgO + Al or MgAl 2 O 4 + Al, facilitating the reduction of Al 2 O 3 and allowing Al/Al metallic bonds to form. Total pressure variation had a negligible influence on the oxygen partial pressure, and consequently, the reaction product formation. Oxygen partial pressure variation as a function of temperature and initial amount of Al 2 O 3 determined the formation of either MgO or MgAl 2 O 4 . Experimental Hot Isostatic Pressure (HIP) bonding at 723 K and 833 K under a constant pressure of 1017 atm documented the cooling rate-dependent formation of β–Mg 2 Si precipitates. High-resolution transmission electron microscopy imaging and selected area electron diffraction patterns verified the formation of β–Mg 2 Si and MgO at the interface but did not detect MgAl 2 O 4 . In conclusion, findings from this study clarify the role of thermochemical interactions in oxide disruption and bonding mechanisms during HIP diffusion bonding of AA6061 and provide guidance for optimizing joining processes for monolithic nuclear fuel assemblies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

DOE OSTI2026

Insights on carbon dioxide adsorption in a flexible 1-D coordination polymer from in situ X-ray scattering and density functional theory

A combination of in situ small-angle X-ray scattering (SAXS) microstructure characterization over scales ranging from 1 nm to 10 µm and powder X-ray diffraction (XRD) structure characterization under various gas/pressure/temperature conditions with density functional theory (DFT) calculations provides new insights for the CO2 sorption behavior of a one-dimensional porous coordination polymer: catena-bis(dibenzoylmethanato)(4,4′-bipyridyl)nickel(II), denoted NiDBM-Bpy. The NiDBM-Bpy chains are held together by van der Waals forces, but the structure of guest-free NiDBM-Bpy is unsolved due to a lack of suitable crystals and high-quality powder XRD patterns. Nevertheless, SAXS and powder XRD can follow microstructural and structural changes as a function of gas pressure, composition and temperature. Both mixed-gas flow and static supercritical CO2 regimes are explored experimentally. DFT calculations are used to model the structural variation associated with XRD changes and hysteresis in the sorption isotherms. XRD and DFT calculations suggest that an orthorhombic Fddd structure with two CO2 per Ni emerges following a transition from the structure with lower molar volume and symmetry that exists without CO2 present.

Allen, Andrew J.↗

DOE OSTI2024

Role of interfaces on the mechanical response of accumulative roll bonded nanometallic laminates investigated via dislocation dynamics simulations

Unraveling the effects of continuous dislocation interactions with interfaces, particularly at the nanometer length scales, is key to a broader understanding of plasticity, to material design and to material certification. To this end, this work proposes a novel discrete dislocation dynamics-based model for dislocation interface interactions tracking the fate of residual dislocation on interfaces. This new approach is used to predict the impact of dislocation/interface reactions on the overall mechanical behavior of accumulative roll bonded nanometallic laminates. The framework considers the dynamic evolution of the interface concurrent with a large network of dislocations, thus, accounting for the local short and long range effects of the dislocations under the external boundary conditions. Specifically, this study focuses on two-phase Fe/Cu nanometallic laminates, and investigates the role of the underlying elastic and plastic contrast of the Fe and the Cu layers on the composite response of the material. Moreover, the role of initial microstructures, resulting from processing is also investigated. Subsequently, the model is used to examine the effect of layer thickness and interface orientation relationship on the residual stresses of the relaxed microstructure. The associated mechanical response of these laminates are compared when loaded under normal direction compression, as well as shear compression. Finally, this work predicts a dominant effect of the layer thickness, as compared to the interface orientation relationship, on the macroscopic response and on the residual stresses of these nanolaminates, while the local dislocation transmission propensity through the interface is significantly influenced by the corresponding orientation relationship.

36 MATERIALS SCIENCE↗

DOE OSTI2024

DISCOVARY PROJECT: Material Background Report

UC/UO 2 composites have been proposed as a next generation fuel for light water reactors (LWRs). Accident tolerant fuels (ATF) have been a focus in the Advanced Fuels Campaign (AFC) to improve the safety and performance of LWRs and includes research and development efforts on the cladding and fuel. The 10 wt.% UC/UO 2 composite fuel was selected as a result of an extensive literature review and was selected due to the improvement of the fuel cycle cost. The inclusion of a UC phase in the composite material improves on the properties of standard UO 2 by increasing the uranium density of the fuel and increasing the thermal conductivity. Significant development has been carried out to refine the processing and sintering parameters and has led to a dense composite without ternary phases present. Characterization of the chemistry and microstructure has been carried out to send ahead of neutron irradiations in the Belgium Research Reactor (BR2) at SCK-CEN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Electrical, structural and thermomechanical properties of doped-LaCrO3 ceramics for high temperature electronics and sensing applications.

Many important electrical and sensor applications require stable conductors under working temperatures up to 1500oC various redox environments. Common high temperature conductors such as nitrides and carbides are not stable under oxidizing atmospheres, for this reason low redox behavior materials would be more attractive. In this work, further dopant studies of the LaCrO3 system were completed in order to control the electronic and ionic conductivity, as well as the relative chemical and microstructural stability. Neodymium and Niobium dopants were initially studied to control the p-type, and potentially n-type conductive mechanisms, respectively, but other dopants strategies were also investigated. The electrical conductivity and Seebeck coefficient were characterized up to 1500oC under varying oxygen partial pressures. The phase and microstructural evolution of each material was also investigated for these compositions by XRD and SEM. The materials showing the best electrical and thermomechanical performance were included within thick films sensors and were tested.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Thermally Insulating, Thermal Shock Resistant Calcium Aluminate Phosphate Cement Composites for Reservoir Thermal Energy Storage

This paper presents the use of hydrophobic silica aerogel (HSA) and hydrophilic fly ash cenosphere (FCS) aggregates for improvements in the thermal insulating and mechanical properties of 100- and 250 °C-autoclaved calcium aluminate phosphate (CaP) cement composites reinforced with micro-glass (MGF) and micro-carbon (MCF) fibers for deployment in medium- (100 °C) and high-temperature (250 °C) reservoir thermal energy storage systems. The following six factors were assessed: (1) Hydrothermal stability of HSA; (2) Pozzolanic activity of the two aggregates and MGF in an alkali cement environment; (3) CaP cement slurry heat release during hydration and chemical reactions; (4) Composite phase compositions and phase transitions; (5) Mechanical behavior; (6) Thermal shock (TS) resistance at temperature gradients of 150 and 225 °C. The results showed that hydrophobic trimethylsilyl groups in trimethylsiloxy-linked silica aerogel structure were susceptible to hydrothermal degradation at 250 °C. This degradation was followed by pozzolanic reactions (PR) of HSA, its dissolution, and the formation of a porous microstructure that caused a major loss in the compressive strength of the composites at 250 °C. The pozzolanic activities of FCS and MGF were moderate, and they offered improved interfacial bonding at cement-FCS and cement-MGF joints through a bridging effect by PR products. Despite the PR of MGF, both MGF and MCF played an essential role in minimizing the considerable losses in compressive strength, particularly in toughness, engendered by incorporating weak HSA. As a result, a FCS/HSA ratio of 90/10 in the CaP composite system was identified as the most effective hybrid insulating aggregate composition, with a persistent compressive strength of more than 7 MPa after three TS tests at a 150 °C temperature gradient. This composite displayed thermal conductivity of 0.28 and 0.35 W/mK after TS with 225 and 150 °C thermal gradients, respectively. These values, below the TC of water (TC water = 0.6 W/mK), were measured under water-saturated conditions for applications in underground reservoirs. However, considering the hydrothermal disintegration of HSA at 250 °C, these CaP composites have potential applications for use in thermally insulating, thermal shock-resistant well cement in a mid-temperature range (100 to 175 °C) reservoir thermal energy storage system.

58 GEOSCIENCES↗

DOE OSTI2025

Phase-field modeling of radiation-induced composition redistribution: An application to additively manufactured austenitic Fe–Cr–Ni

Multicomponent alloys undergoing irradiation damage develop radiation-induced composition redistribution at point defect sinks such as grain boundaries (GBs) and dislocations. Such redistribution results in undesired changes to their mechanical behavior and corrosion resistance. Additively manufactured alloys proposed for future nuclear applications are expected to demonstrate a distinct response to irradiation owing to their unique microstructure with as-solidified dislocation density and chemical microsegregation. To capture the composition redistribution in such systems, we develop a mesoscale model with coupled evolution of atomic and point defect components in the presence of dislocation density, dislocation heterogeneity, and thermodynamic interactions at the GB. The model is parameterized for an FCC Fe–Cr–Ni alloy as a representative system for austenitic stainless steels, and simulations are performed in 1D and 2D as a function of irradiation temperature, dose, dislocation density, and grain size. Radiation-induced segregation (RIS) characterized by Cr depletion and Ni enrichment is predicted at both the GB and the dislocation cell wall, with RIS being lower in magnitude but wider at the cell wall. Strongly biased absorption of self-interstitials by dislocations is found to suppress Ni enrichment but slightly enhance Cr depletion under certain conditions. Thermodynamic segregation at the GB is predicted to be narrower and opposite in sign to RIS for both Cr and Ni. Importantly, non-monotonic segregation is found to occur when both thermodynamic and RIS mechanisms are considered, providing a novel physical interpretation of experimental observations. The model is expected to serve as a key tool in accelerated qualification of irradiated materials.

additively manufactured microstructure↗

DOE OSTI2021

Achieving strong and stable nanocrystalline Al alloys through compositional design

Abstract Al alloys often suffer from low mechanical strength and lack high-temperature microstructural and mechanical robustness. A series of binary and ternary nanocrystalline (NC) Al transition metal alloys with supersaturated solid solution and columnar nanograins have been recently developed by using magnetron sputtering, manifesting a new realm of mechanical properties and thermal stability. Distinct solutes cause evident differences in the phase transformations and efficiencies for grain refinement and crystalline-to-amorphous transition. Certain sputtered Al-TM alloys have shown room-temperature mechanical strengths greater than 2 GPa and outstanding thermal stability up to 400 °C. In addition, the NC Al alloys show mechanical anisotropy and tension–compression asymmetry, revealed by micromechanical tests. Through the process encapsulating various compositionally distinct systems, we attempt to illuminate the solute effects on grain refinement and properties and more importantly, tentatively unravel the design criteria for high-strength and yet thermally stable NC Al alloys. Graphic Abstract

36 MATERIALS SCIENCE↗

DOE OSTI2023

Development of a Novel Magnesium Alloy for Thixomolding® of Automotive Components (Final Report)

Magnesium (Mg) alloy die-castings are increasingly used in the automobile industry to achieve cost effective mass reduction, especially in systems where multiple components can be integrated into a single thin wall die-casting. However, there are several component quality restrictions in thin-walled Mg die castings, including variability in dimensional accuracy, part-to-part variation in mechanical properties, and porosity in the final part, which has limited the continued growth of die-cast components in the automobile industry. An alternative to die-casting is the process of thixomolding®. While the die-casting process relies on filling a mold at high speeds with the alloy in the completely molten state, the thixomolding® process fills a mold with a thixotropic alloy in a semi-solid slurry state at a temperature between the liquidus and solidus temperatures. Ideally, the material should be ~30–65% solid rather than being completely liquid at the beginning of the injection process. Advantages of the thixomolding® process include a finer grain structure, lower porosity, improved dimensional accuracy, improved part-to part consistency, improved mechanical properties, particularly ductility in the component, the ability to reduce wall thickness for mass savings, and longer tool life due to lower process temperatures. The objective of this collaborative project between Oak Ridge National Laboratory, FCA US LLC, and Leggera Technologies was to develop one or more novel Mg alloys more suitable for thixomolding® automotive structural components than the current die-casting alloys used for this process. The primary interest was to improve ductility while maintaining tensile and fatigue strengths, as these are properties that are critical for use in body and chassis structural applications. Since good corrosion resistance is also desirable for this application, this property was also considered when evaluating promising alloy compositions. An initial evaluation of existing components thixomolded® using AM60 was performed and microstructure, and tensile properties were evaluated for the baseline alloy. Targets were established for ease of processing (characterized by the melting range defined as the difference between the liquidus and the solidus), strength, and ductility. Computational modeling was used to identify promising alloys and selected alloys were cast in laboratory scale heats. Properties measured from laboratory scale heats were used to down-select two alloys for further evaluation and component fabrication. Two alloys were prepared in industrial scale heats, cut into small pieces (chips), and thixomolding® trials were initiated. Trial components were successfully fabricated using one alloy composition, but it was concluded that further refinement of the thixomolding® process parameters are required to successfully fabricate component using second alloy. Microstructure and mechanical properties were evaluated on the material removed from the fabricated component and properties were compared to the baseline alloy. Although mechanical properties of the alloys showed improvement over the baseline alloy, it was determined that modifications to the thixomolding® process would result in better microstructure control with further improvement in properties leading to successful commercialization. A provisional patent application has already been filed on the new alloys developed as part of the project.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Effect of Initial Microstructure on the Toughness of Coarse-Grained Heat-Affected Zone in a Microalloyed Steel

Toughness of the coarse-grained-heat-affected-zone (CGHAZ) strongly depends on the prior austenite grain size. The prior austenite grain size is affected not only by chemical composition, thermal cycle, and dissolution of second-phase particles, but also by the initial microstructure. The effect of base metal microstructure (ferrite/pearlite obtained by air cooling and martensite obtained by water-quenching) on Charpy impact toughness of the CGHAZ has been investigated for different heat inputs for high-heat input welding of a microalloyed steel. A welding thermal cycle with a heat input of 100 kJ/cm and 400 kJ/cm were simulated on the MMS-300 system. Despite a similar microstructure in the CGHAZ of both the base metals, the average Charpy impact energy for the air-cooled base metal was found to be higher than the water-quenched base metal. Through thermo-kinetic simulations, it was found that a higher enrichment of Mn/C at the ferrite/austenite transformation interface of the CGHAZ of water-quenched base metal resulted in stabilizing austenite at a lower A1 temperature, which resulted in a coarser austenite grain size and eventually lowering the toughness of the CGHAZ.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Additive manufacturing is increasingly being employed to produce components of complex geometries in structural alloys because of the expected energy savings associated with the near-net-shape capability and the ability to build in novel internal features that are not possible with many conventional manufacturing approaches. However, because of the extreme thermal conditions encountered, the non-equilibrium microstructures produced during powder bed-based additive manufacturing processes must be subjected to custom post-heat treatment processes to recover the target mechanical properties. Phase-field models and simulation techniques have matured to a state where the microstructure evolution paths, and the morphologies of the resulting precipitate phases can be predicted reasonably accurately, considering alloy-specific thermodynamic and kinetic aspects of the nucleation and growth processes. However, phase-field simulations are computationally intensive, which precludes the ability to apply the simulations directly to the length scale of the entire component. Therefore, it is highly desirable to develop low-computational-cost surrogate models that effectively capture the physics at the microstructural length scale, while facilitating the design of optimized processing conditions resulting in location-specific targeted microstructures at the component scale. The work presented here demonstrates the application of the materials knowledge system framework to develop a surrogate model that effectively captures the microstructural path during annealing of a Ni–Mo–Nb alloy containing different Mo and Nb compositions known to segregate during solidification under additive manufacturing conditions. Specifically, the surrogate model built in this work is based on a Gaussian process autoregressive model informed by statistical representation of simulated microstructures using two-point correlations and dimensionality reduction through principal component analysis. In conclusion, this surrogate model is shown to capture the bifurcation of the microstructural path during precipitation, which yields a microstructure dominated by the $\gamma^{\prime\prime}$ phase at high Nb concentrations and the $\delta$ phase at low Nb concentrations.

36 MATERIALS SCIENCE↗

DOE OSTI2020

3Y-TZP Toughened and Oxidation-resistant U 3 Si 2 Composites for Accident Tolerant Fuels

In this work, we report an innovative approach synergizing multiple effects of microstructure control, oxide protection and phase transformation-induced mechanically toughening to develop advanced U 3 Si 2 fuels with state-of-the-art materials properties. 3Y-TZP (3 mol% yttria doped stabilized tetragonal zirconia) additives are incorporated and uniformly distributed into the SPS-densified U 3 Si 2 fuel matrix, enhancing materials fracture toughness up to 4.04 MPa m 1/2 . The 3Y-TZP incorporated U 3 Si 2 composite pellets show significantly improved onset temperature of oxidation above 560 °C, which can be further improved to 617 °C with 3 vol% addition by post-sintering thermal annealing. We report the development of mechanically tough and oxidation-resistant U 3 Si 2 with minimal additive represents a major step forward towards realizing the potential of high density U 3 Si 2 as the leading fuel concept to increase accidence tolerance of nuclear energy systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

In situ synchrotron diffraction and modeling of non-equilibrium solidification of a MnFeCoNiCu alloy

The solidification mechanism and segregation behavior of laser-melted Mn 35 Fe 5 Co 20 Ni 20 Cu 20 was firstly investigated via in situ synchrotron x-ray diffraction at millisecond temporal resolution. The transient composition evolution of the random solid solution during sequential solidification of dendritic and interdendritic regions complicates the analysis of synchrotron diffraction data via any single conventional tool, such as Rietveld refinement. Therefore, a novel approach combining a hard-sphere approximation model, thermodynamic simulation, thermal expansion measurement and microstructural characterization was developed to assist in a fundamental understanding of the evolution of local composition, lattice parameter, and dendrite volume fraction corresponding to the diffraction data. This methodology yields self-consistent results across different methods. Via this approach, four distinct stages were identified, including: (I) FCC dendrite solidification, (II) solidification of FCC interdendritic region, (III) solid-state interdiffusion and (IV) final cooling with marginal diffusion. It was found out that in Stage I, Cu and Mn were rejected into liquid as Mn 35 Fe 5 Co 20 Ni 20 Cu 20 solidified dendritically. During Stage II, the lattice parameter disparity between dendrite and interdendritic region escalated as Cu and Mn continued segregating into the interdendritic region. After complete solidification, during Stage III, the lattice parameter disparity gradually decreases, demonstrating a degree of composition homogenization. The volume fraction of dendrites slightly grew from 58.3 to 65.5%, based on the evolving composition profile across a dendrite/interdendritic interface in diffusion calculations. Postmortem metallography further confirmed that dendrites have a volume fraction of 64.7 ± 5.3% in the final microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2020

First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys

Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

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)↗

DOE OSTI2025

Local chemical ordering of a neutron-irradiated CrFeMnNi compositionally complex alloy

While ion-irradiation studies are a critical first step in studying compositionally complex alloys (CCAs) for nuclear applications, they do not capture all the microstructural changes occurring under the low irradiation dose rates and different particles’ scattering patterns experienced in a nuclear reactor setting. To explore these phenomena in reactor-relevant conditions for the first time in CCA, the single-phase solid-solution Cr 10 Fe 30 Mn 30 Ni 30 was neutron irradiated up to 6.61 displacements per atom at 395 and 579 °C. Irradiation-enhanced local chemical ordering (LCO) well beyond the range of short range ordering was observed, and is predicted to be the precursor to the precipitation of a coherent Ni-Mn L1 0 phase and a Cr-rich α’ phase, though TEM analysis did not indicate the presence of either in any irradiation condition. The line density of faulted dislocation loops decreased from 6.47 to 1.69 ∙ 10 15 m -2 from 3.43 to 6.61 dpa at 579 °C despite no appreciable faulted loop content in the unirradiated material. LCO is expected to increase the complexity of the energy landscape within this alloy, restricting interstitial point defect mobility and creating local regions of greater stacking fault energy. These contribute to the negative correlation between irradiation dose and faulted dislocation loop density in this study, as well as the lack of void swelling observed.

36 MATERIALS SCIENCE↗