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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Unraveling Thermodynamic and Kinetic Contributions to the Stability of Doped Nanocrystalline Alloys using Nanometallic Multilayers

Abstract Targeted doping of grain boundaries is widely pursued as a pathway for combating thermal instabilities in nanocrystalline metals. However, certain dopants predicted to produce grain‐boundary‐segregated nanocrystalline configurations instead form small nanoprecipitates at elevated temperatures that act to kinetically inhibit grain growth. Here, thermodynamic modeling is implemented to select the Mo–Au system for exploring the interplay between thermodynamic and kinetic contributions to nanostructure stability. Using nanoscale multilayers and in situ transmission electron microscopy thermal aging, evolving segregation states and the corresponding phase transitions are mapped with temperature. The microstructure is shown to evolve through a transformation at lower homologous temperatures (<600 °C) where solute atoms cluster and segregate to the grain boundaries, consistent with predictions from thermodynamic models. An increase in temperature to 800 °C is accompanied by coarsening of the grain structure via grain boundary migration but with multiple pinning events uncovered between migrating segments of the grain boundary and local solute clustering. Direct comparison between the thermodynamic predictions and experimental observations of microstructure evolution thus demonstrates a transition from thermodynamically preferred to kinetically inhibited nanocrystalline stability and provides a general framework for decoupling contributions to complex stability transitions while simultaneously targeting a dominant thermal stability regime.

25 ENERGY STORAGE↗

Distribution of 7 Li implants in Nb films for a sterile neutrino search

The Beryllium-7 Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for sub-MeV sterile neutrinos by measuring the 7 Li recoil spectrum from 7 Be decay in Ta-based superconducting quantum sensors. Its sensitivity is limited by spectral broadening from interactions between 7 Be/ 7 Li and the Ta host material. This study investigates Nb as an alternative sensor material using scanning transmission electron microscopy (STEM) and atom probe tomography (APT) on 7 Li-implanted Nb films (∼0.5 at. %). STEM shows no 7 Li cluster formation and no implantation-induced microstructural degradation, while APT reveals some limited 7 Li segregation to grain boundaries. Although this segregation may slightly influence binding energies, it is unlikely to affect the broadening of the recoil spectrum significantly. These findings support Nb as a viable sensor material for future phases of the BeEST experiment.

36 MATERIALS SCIENCE↗

Cluster Dynamics Simulations of Intra-Granular Fission Gas Bubble Size and Pressure Evolution in UO 2

Fission gases such as xenon (Xe) play a critical role in determining the behavior and response of nuclear fuel. Given that Xe has little solubility in UO 2 , it accumulates and forms bubbles, which significantly impact fuel performance. Intra- and inter-granular bubble nucleation and growth can lead to fuel swelling, and once bubbles interconnect at grain boundaries, fission gas can be released into the plenum. At low temperatures, limited uranium vacancy mobility can restrict swelling, therefore causing the bubbles to become highly pressurized. Consequently, this can induce micro-cracking, promote fission gas release (increasing the likelihood of cladding failure), and even lead to fuel pulverization under accident conditions such as a loss of coolant accident. As bubble evolution is strongly influenced by local temperature and fission rate, markedly different behavior occurs across the radial profile of the fuel pellet. Capturing the mechanisms that underpin bubble evolution is therefore important to predict these behaviors in the fuel. Previous models describing important mechanisms informed by lower length scale simulations have been developed under the NEAMS program. These can describe the evolution of a single bubble type (i.e., single value for radius and pressure) at each position in the pellet, for instance using the Centipede cluster dynamic code. However, in reality, a full distribution in bubble sizes and pressures exists within the microstructure at a given position in the pellet. To address this the cluster dynamics code Xolotl, which can predict Xe and vacancy phase space (i.e., bubble distributions) for intra-granular bubbles, has been used before. Prior work benchmarked the Xolotl code against the Centipede cluster dynamics code to ensure compatibility and to verify that mobile defect properties are adequately transferred between the two codes, along with some physics improvements. In this work, we go further by introducing a physics-based set of improvements that will allow us to accurately predict bubble size distributions and internal bubble pressures under representative UO 2 irradiation conditions. The improvements include (i) coupling bubble-defect reaction energies to a virial equation of state (EOS), (ii) including a bubble surface tension contribution, (iii) incorporating radiation-induced re-solution of Xe and vacancies, (iv) enabling pressure-driven dislocation loop punching through an effective emission of interstitial clusters informed by interstitial loop energetics, (v) accounting for radiation induced athermal diffusion of Xe, and (vi) implementing a Booth-type grain boundary sink representation for all mobile defects and defect clusters. After these modifications, we observe good agreement of Xolotl fission gas bubble size and concentration predictions with legacy experimental measurements. Additionally, it allows the distribution of Xe bubble pressures and radius to also be predicted and compared to data produced through the Advanced Fuels Campaign (AFC) program. Here, we have done this by running simulations under conditions similar to the AFC post-irradiation examination (PIE) samples irradiated at North Anna 2 light water reactor (LWR). Our results shows excellent agreement with these experimental measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data Science Techniques, Assumptions, and Challenges in Alloy Clustering and Property Prediction

Data analytics methods have been increasingly applied to understanding materials chemistry, processing due to the manufacturing approach, and uni-axial and cyclic property relationships in the highly complex space of alloy design. There are several benefits to applying data analytics to this space, including the ability to manage non-linearities in the responses of the alloy attributes and the resulting mechanical properties. However, key difficulties in applying and understanding the results of data analytics include the often lack of reported assumptions and data processing steps necessary to improve interpretation and reproducibility in derived results. In this work, the methods used to generate clustering and correlation analyses for experimental 9% Cr ferritic-martensitic steel data were investigated and the resulting implications for mechanical property predictions were assessed. This work uses principal component analysis, partitioning around medoids, t-SNE, and k-means clustering to investigate trends in composition, processing and microstructure information with creep and tensile properties, building on work done previously using a smaller version of the same dataset. The initial assumptions, preprocessing steps and methods are investigated and outlined in order to depict the fine level of detail required to convey the steps taken to process data and produce analytical results. Here, the variations in the resulting analyses are explored due to the influence of new and more varied data.

36 MATERIALS SCIENCE↗

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Statistical Descriptors of Composite Fiber Aggregation

This study introduces a method of characterizing fiber aggregation and resin rich regions in composite microstructures. Microscale models of representative elements (RVE) need to be indicative of the extend of clustering (i.e. close fiber-to-fiber interaction) and resin rich “pools” which may impact the overall strength and performance of a composite structure. This algorithm was used to evaluate different unidirectional 2-D microstructure scans, which will be compared to their manufacturing method or any special treatment processes. These cluster and pool scan statistics can be used as criteria to judge statistical equivalency of artificially constructed microstructures.

Statistics↗

Microstructure study of U–35 wt.% Zr alloy after quick annealing at 650 °C

Uranium-35wt.%zirconium (U-35wt.%Zr) alloy was annealed for 1 hour and 24 hours at 650 ºC and characterized to understand the early stage microstructure evolution. Dendritic microstructure with fine (~300 nm in length) α-U precipitates clustered between dendrite branches were observed in the 1-hour annealed sample. After 24-hour annealing 650 ºC, the α-U precipitates coarsened, and the dendritic microstructure disappeared due to microstructure homogenization. Furthermore, microchemical homogenization observed with Energy-Dispersive X-ray Spectroscopy analysis suggests that α-U precipitates are approaching thermodynamic equilibrium in the 24-hour annealed sample. The findings from this study have potential impacts on the manufacturing and computer modeling of metallic nuclear fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Gravity Induced Formation of Concentration Gradients in Supersaturated Binary Solutions

Experimental and theoretical studies of the formation of solute concentration gradient in supersaturated binary solutions in a gravitational field were carried out. The formation of solute concentration gradient was associated with the gravity induced redistribution of subcritical solute clusters. The birth-death process of the new solute-rich phase domains (subcritical solute clusters) was described in terms of the time-dependent Ginzburg Landau model developed for metastable state relaxation in binary (solute + solvent) non-critical solutions in the presence of a gravitational field. A new mathematical Ansatz was developed for solution of the model equations. This Ansatz has allowed to approach for the first time the following important problems: (1) Microstructure of solute distribution inside of the subcritical solute clusters. The analytical results obtained demonstrate that solute inside of the subcritical solute clusters is heterogeneously distributed with a spatially periodic structure. (2) Macrostructure of the solute subcritical clusters distribution in a gravitational field. The subcritical solute clusters are found to be distributed heterogeneously in a gravitational field. This heterogeneity, which is due to the heterogeneous birth-death process of the subcritical solute clusters in a gravitational field, initiates a noticeable solute concentration gradient in vertical columns of supersaturated binary solutions. An analysis and comparison of theoretical results and experimental data related to the solute concentration gradient formation in a gravitational field are presented. It is also demonstrated that the critical radius of solute clusters (radius of nucleation) and induction time are gravity-dependent.

Izmailov, Alexander F.↗

Atom probe tomography characterization of ion and neutron irradiated Alloy 800H

Alloy 800H is a high temperature and creep resistant alloy, and is considered as a candidate alloy for use in Generation IV nuclear reactor systems. To clarify the alloy's behavior under irradiation, samples were subjected to single ion irradiations up to 20 dpa at 440°C, a dual ion/He irradiation to 17 dpa at 460°C, and a neutron irradiation to 17 dpa at 385°C. The irradiated microstructures were characterized using atom probe tomography to complement previously published transmission electron microscopy studies. Additionally, after single ion irradiation, sparse fine Al and Ti clusters were observed after 1dpa, while high number densities of nanoscale Ni-Al-Ti clusters, Cr-Ti rich carbides, and Si-decorated dislocation loops developed after 10 and 20 dpa. The microstructure formed during single ion irradiation exhibited a strong depth dependence. No significant differences were observed between the single and dual ion irradiations. While Ni-Al-Ti clusters, Cr-Ti rich carbides, and Si-decorated dislocation loops were also observed after neutron irradiation, the neutron-irradiated microstructure differed from those found in the ion-irradiated samples.

36 MATERIALS SCIENCE↗

Microstructure‐Dependent Sodium Storage Mechanisms in Hard Carbon Anodes

Sustainable energy storage is essential to support the transition to renewables and meet the increasing demand for energy. Sodium‐ion batteries (NIBs) are attractive for grid‐scale energy storage due to the abundance and low cost of sodium, sustainability of other battery components, and electrochemical performance. Hard carbon (HC) is a leading anode material for NIBs, but its complex microstructure complicates the understanding of sodium storage mechanisms. Using X‐ray total scattering and density functional theory calculations, this study clarifies how HC's microstructural variations influence sodium storage across the slope (high potential) and plateau (low potential) regions of the potential capacity curve. In the slope region, sodium initially adsorbs at high‐binding energy defect sites and subsequently intercalates between graphene layers, adsorbing at low‐binding energy defect sites, correlating with different slopes observed during initial sodiation. Initial irreversibility arises from sodium trapping at surface defects and solid electrolyte interface formation. In the plateau region, sodium simultaneously intercalates and fills pores, influenced by pore size, interlayer spacing, and defect concentration. HCs with larger pore sizes form larger sodium clusters. In conclusion, the proposed mechanism underscores the role of microstructure engineering in enhancing HC performance and advancing NIBs for grid‐scale energy storage.

36 MATERIALS SCIENCE↗

Influence of nanoscale interfaces on the dynamic deformation and spall failure of Cu–Fe alloy microstructures

Additively manufactured immiscible Cu–Fe alloys can exhibit a distribution of nanoscale interfaces due to the distribution of nanoscale clusters in the equilibrium and metastable phases. Molecular dynamics simulations investigate the role of such interfaces on the phase stability and transformation behavior during shock compression, as well as the mechanisms of damage nucleation during spall failure. The model multiphase Cu–Fe systems studied here comprise a distribution of Fe clusters in an FCC Cu matrix, as well as Cu clusters in a BCC Fe matrix. The length scales of the nanoscale clusters determine the energetics of the interfaces that can result in FCC/BCC (equilibrium) or FCC/FCC (metastable) interfaces in the Cu system matrix, and BCC/FCC (equilibrium) or BCC/BCC (metastable) interfaces in the Fe matrix. The MD simulations demonstrate that nanoscale metastable interface microstructures can induce plastic deformation and also stabilize phases or suppress phase transformations in metastable phase clusters. In contrast, equilibrium interfaces can influence phase transformation thresholds and serve as additional void nucleation sites during failure.

36 MATERIALS SCIENCE↗

Effects of transition metal carbide dispersoids on helium bubble formation in dispersion-strengthened tungsten

Abstract The formation of helium bubbles and subsequent property degradation poses a significant challenge to tungsten as a plasma-facing material in future long-pulse plasma-burning fusion reactors. In this study, we investigated helium bubble formation in dispersion-strengthened tungsten doped with transition metal carbides, including TaC, ZrC, and TiC. Of the three dispersoids, TaC exhibited the highest resistance to helium bubble formation, possibly due to the low vacancy mobility in the Group VB metal carbide and oxide phases. Under identical irradiation conditions, large helium bubbles formed at grain boundaries in tungsten, while no bubbles were observed at the interfaces between the carbide dispersoid and tungsten matrix. Moreover, our results showed the interfaces could suppress helium bubble formation in the nearby tungsten matrix, suggesting that the interfaces are more effective in trapping helium as tiny clusters. Our research provided new insights into optimizing the microstructure of dispersion-strengthened tungsten alloys to enhance their performance.

36 MATERIALS SCIENCE↗

Shielded magnetic small-angle neutron scattering for characterization of radioactive samples

The development of a Pb-shielded fixture for the execution of a small-angle neutron scattering (SANS)-based workflow for interrogation of highly irradiated nuclear materials has been explored. The Pb shielding was specially designed to reduce the detected radioactivity from the specimen during SANS experiments, and the overall configuration is termed shielded magnetic SANS (SM-SANS). Two FeCrAl-based alloys, C35M and 125YF, were examined with the SM-SANS technique using a free-form size distribution locally monodisperse model in both the as-received and irradiated states. Quantitative values derived from the free-form size distribution were compared with atom probe tomography experiments. Microstructural and compositional parameters determined using the two characterization techniques were complements of each other. The results demonstrate that the SM-SANS technique is an effective means of characterizing nanoscale clustering in irradiated material systems and provides new avenues for investigating radioactive material microstructures.

FeCrAl↗

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

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

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The effect of Ti content on age hardening and mechanical properties of uranium-titanium alloys

Here, the effect of Ti content on age hardening and the resulting mechanical properties are described for -quenched U-Ti alloys containing 0.3 wt.% to 2.0 wt.%Ti. Age hardening occurs between ~250°C and ~450°C. Overaging occurs at higher temperatures by cellular decomposition. Age hardening kinetics suggest that different mechanisms occur depending on Ti content and initial microstructure. Strengthening in 'a acicular martensites begins by the formation of Ti clusters which evolve into thin U 2 Ti disc shaped precipitates and later mature into continuous U 2 Ti rods beginning at peak hardness. The mechanism of hardening in 'b banded martensite is more elusive, as significant hardening occurs where atomic mobility is lower than that required for precipitate formation, similar to that reported for age hardening in ''b banded martensite in U-6%Nb. The activation energy for aging varies with Ti content and microstructure. In fully martensitic alloys containing 0.75% to 2.0%Ti it is in the vicinity of ~44 kcal/mole (184 kJ/mole). But it is lower in alloys containing less than 0.6%Ti where quenched microstructures are less than fully martensitic. Tensile ductility is high prior to aging, decreases with age hardening, is effectively zero at peak hardness, and remains low in overaged conditions. Attractive combinations of strength and ductility are best obtained in alloys containing 0.6% to 1.0%Ti which have been partially aged to fractional hardening levels no greater than ~0.6. This corresponds to the very early stages of aging, associated with clustering and the earliest stages of U 2 Ti disc formation. Alloys containing 0.45%Ti or less are not as responsive to age hardening. Alloys containing 1.5% and 2.0%Ti can be aged to higher strengths, but extreme quench rate sensitivity prevents them from being effectively heat treated in realistic section thicknesses.

36 MATERIALS SCIENCE↗

Electric-field-assisted-sintering of rare-earth oxide dispersion strengthened Fe-Cr-Mo alloys

Oxide dispersion-strengthened (ODS) alloys are widely recognized for their exceptional high-temperature strength, creep resistance, and radiation tolerance, making them indispensable for advanced nuclear reactors, aerospace, and energy systems. Achieving a fine and stable dispersion of oxide nanoparticles is critical, as these particles act as strong barriers to dislocation motion and effective sinks for irradiation-induced defects, ensuring structural integrity under extreme conditions. Here, in this study, Fe–Cr–Mo-based ODS alloys were fabricated via mechanical alloying and consolidated using electric-field-assisted sintering (EFAS) with additions of Y 2 O 3 , La 2 O 3 , and CeO 2 . EFAS processing produced ultrafine-grained microstructures (average grain size <1 μm) with uniformly distributed oxide clusters (2–4 nm). Atom probe tomography revealed that La 2 O 3 -containing alloys exhibited the highest nanoparticle number density, resulting in superior tensile strength compared to yttria- and ceria-bearing counterparts. The combined effect of grain refinement and rare-earth oxide dispersion significantly enhanced mechanical performance, demonstrating the potential of EFAS for developing high-strength ferritic alloys for demanding environments such as nuclear systems.

36 - MATERIALS SCIENCE↗

The influence of containerless undercooling and rapid solid-state quenching on the superconductive and magnetic properties of some clustering alloy systems

The properties of clustering alloy systems and the manner in which they are influenced by rapid quenching from a containerless undercooled melt are discussed. It was postulated that rapid quenching under such conditions would result in highly disordered metastable alloys, and furthermore, that alloys in such conditions would possess physical properties characteristically different from those of alloys in the annealed equilibrium state. The scope of the program is essentially to gauge the influence of containerless undercooling on the submicrostructure of clustering-type alloys, using certain physical properties as diagnostic tools. Microstructures and macrostructures were to be examined using optical- and scanning-electron microscopy.

Collings, E. W.↗

An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction

Micrograph quantification is an essential component of several materials science studies. Machine learning methods, in particular convolutional neural networks, have previously demonstrated performance in image recognition tasks across several disciplines (e.g. materials science, medical imaging, facial recognition). Here, we apply these well-established methods to develop an approach to microstructure quantification for kinetic modeling of a discontinuous precipitation reaction in a case study on the uranium-molybdenum system. Prediction of material processing history based on image data (classification), calculation of area fraction of phases present in the micrographs (segmentation), and kinetic modeling from segmentation results were performed. Results indicate that convolutional neural networks represent microstructure image data well, and segmentation using the k-means clustering algorithm yields results that agree well with manually annotated images. Classification accuracies of original and segmented images are both 94% for a 5-class classification problem. Kinetic modeling results agree well with previously reported data using manual thresholding. The image quantification and kinetic modeling approach developed and presented here aims to reduce researcher bias introduced into the characterization process, and allows for leveraging information in limited image data sets.

36 MATERIALS SCIENCE↗