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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Neutron irradiation & thermomechanical experiment (NITE) - design

For the reliable long-term operation of fusion power plants, it is crucial to understand and predict the lifetime of materials in use. These materials include all structural and functional materials utilized at the first wall, blanket, magnets, and shielding. The key challenge is, that the harsh environment including high heat fluxes, high thermal stress and stress cycling, neutron irradiation, and sputtering on such materials should not be viewed separately. Currently, the synergistic loads cannot be evaluated experimentally because of the lack of adequate facilities. The purpose of that work is to design a synergetic Neutron Irradiation and Thermomechanical Experiment (NITE) for fusion materials. This design will leverage the existing Advanced-Test-Reactor (ATR), a fission reactor at the Idaho National Laboratory. We also acknowledge that with existing fission reactors the exact fusion condition cannot be created, and the limitations are critically discussed. The combination of neutron irradiation with a high heat flux is the focus. This is realized with an irradiation capsule design that includes a TRISO fueled region inside the capsule to enable a steady-state heat flux on one side of the specimen. In conclusion, the experimental design modeling showed that steady-state heat fluxes of 2.4 MW/m 2 with a thermal gradient of above 250°C can be achieved in a 5 mm thick specimen.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatial mapping of the localized corrosion behavior of a magnesium alloy AZ31B tungsten inert gas weld

Sections of a magnesium alloy, AZ31B, joined with tungsten inert gas (TIG) welding, were examined with scanning electrochemical microscopy (SECM) and scanning Kelvin probe force microscopy (SKPFM) to investigate corrosion mechanisms by correlating observed corrosion behavior with weld-affected microstructural variations. Insight into the changing nature of the galvanic couples between weld zones and at localized microgalvanic sites were investigated using SECM and SKPFM to map both electrochemically active regions and Volta potential differences across the weld-affected zones. The formation of an Al-Zn solidification network in the fusion zone (FZ) at and near the TIG weld epicenter differs from the outer heat-affected zone (HAZ), where intermetallic particles (IMPs) are the notable secondary phase from the magnesium matrix. These microstructures were mapped with SKPFM before and after brief exposure to a salt solution, revealing micro-galvanic couples as the main driving force to corrosion initiation and propagation within each zone. The IMPs and Al-Zn solidification network act as strong cathodes and govern the corrosion processes. The galvanic coupling and evolution of the intrinsic corrosion behavior between the weld zones is explained by monitoring the hydrogen evolution reaction (HER) with SECM over time. Anodically induced cathodic activation is confirmed for this welded material, as micro-galvanic couples between microstructural features are found to transition over time to broad electrochemically active areas within the weld-affected zones, resulting in polarity reversal as time of exposure proceeds.

Anodically induced cathodic activation↗
DOE OSTI2025

Transmission Electron Microscopy Characterization of Fuel Cladding Chemical Interaction between Minor Actinides bearing U-Pu-Zr Fuel and AIM1 Cladding

Minor actinides (MA) significantly contribute to the long-term radiotoxicity of spent nuclear fuel (SNF). Separating MA from SNF and incorporating it into metallic fuels for fast reactor transmutation is a potential method to reduce this radiotoxicity. Here, this study focuses on transmission electron microscopy characterization of two samples from the fuel cladding chemical interaction (FCCI) region of an americium (Am) and neptunium (Np)-bearing (MA-bearing) uranium-plutonium-zirconium (U-Pu-Zr) fuel irradiated in the Phenix fast reactor to 9.5 % FIMA burnup at approximately 550 °C cladding temperature. The results show that despite the complex chemical interactions between MA and AIM1 cladding elements, excessive FCCI was not induced, and Am penetration depth in the cladding limited to less than 4 µm. Np remained mostly inside fuel. The Zr-rich compounds layer effectively limited the accumulation of lanthanide on the inner cladding surface. Overall, the FCCI behavior between investigated MA-bearing U-Pu-Zr fuel and AIM1 cladding is benign.

Chemical interaction↗
DOE OSTI2025

Unpacking model inadequacy: The quantification of silver release from TRISO fuel by considering empirical and mechanistic approaches

Increasing adoption of the proposed tristructural isotropic (TRISO) particle fuel for both advanced and existing reactors makes it critical to assess and address any uncertainties and inadequacies of TRISO fission product release models. Model inadequacy stems from simplifications made to the computational model when compared to the experiments. The modeling and simulation efforts conducted using the BISON fuel performance code, along with the experimental campaigns carried out under the Advanced Gas Reactor Fuel Development and Qualification Program, afford a unique opportunity to conduct a rigorous modeling inadequacy assessment within the Bayesian uncertainty quantification (UQ) framework. Here, this study compares the standard Bayesian framework against the Kennedy-O'Hagan (KOH) framework, which explicitly represents modeling inadequacy, in regard to UQ for TRISO silver release models. For this purpose, both the traditional Arrhenius equation fitted to experimental data and the more advanced lower-length-scale (LLS)-informed model, which considers microstructure information, are independently considered. Applying the inverse UQ process on the AGR-2 and -3/4 datasets revealed modeling inadequacy to be the most dominant source of uncertainty. Experimental noise uncertainty is also significant; however, model parameter uncertainty can be considered negligible. Interestingly, both the Arrhenius equation and the LLS-informed model demonstrated similar levels of modeling inadequacy. For the forward predictive UQ, the KOH framework improved both the accuracy and quality of quantified uncertainties in comparison to the standard Bayesian framework. This is true for both the Arrhenius equation and the LLS-informed model. In comparing these modeling approaches, both demonstrated similar performance at the engineering scale, while the LLS-informed model expectedly outperformed the Arrhenius equation at the mesoscale. These conclusions highlight the importance of explicitly accounting for modeling inadequacy in the UQ process, and reinforce the need for continuous refinement of physics-based models in order to address the modeling inadequacy.

Advanced reactors↗
DOE OSTI2025

In-situ ion irradiation of fission products in a spent UO 2 fuel

This study investigates the behavior of fission gas bubbles and five metal precipitates (5MPs) (Mo, Ru, Rh, Tc, Pd) in spent uranium dioxide (UO 2 ) fuel under various ion irradiation doses, temperatures, and flux conditions. Utilizing in-situ ion irradiation and advanced transmission electron microscopy, we analyzed the evolution of fission gas bubbles and 5MPs in UO 2 samples from the Belgium Reactor 3 (BR-3). Our findings reveal significant shrinkage of fission gas bubbles and 5MPs with increasing irradiation dose, accompanied by a decrease in pair density. We demonstrate that ion irradiation induces a homogeneous re-solution process where individual atoms are ejected from bubbles and precipitates, leading to their dissolution and subsequent re-precipitation in the matrix. In conclusion, this study provides critical insights into the dynamic behavior of fission products under irradiation, facilitating the development of predictive models and contributing to the optimization of nuclear fuel performance and safety.

Fission products↗
DOE OSTI2025

3D pore structure reconstruction of fluff region in top of EBR-II irradiated fuel by X-ray micro-computed tomography

Metallic fuels comprised of U-Zr binary and U-Pu-Zr ternary alloys are a promising fuel candidate for sodium-cooled fast reactors and possess many advantages over ceramic fuels such as higher uranium density and improved thermal conductivity. Fluff is a highly porous structure forming at the top of metallic fuel slugs during irradiation and was extensively observed in past sodium-cooled fast reactor (SFR) experiments such as Idaho National Laboratory’s Experimental Breeder Reactor II (EBR-II). Previous investigations have shown that fluff is rich in fissile atoms and hence could have neutronics implications, but its formation mechanisms are not understood. In this work, two cube-shaped lift outs were taken from the fluff and bulk fuel regions of a high burnup U-19Pu-10Zr composition EBR-II fuel slug and characterized by micro computed tomography (Micro-CT) and energy dispersive x-ray spectroscopy (EDS). This was used to characterize differences in microscale porosity and composition between fluff and bulk fuel, and to support or oppose postulated fluff formation mechanisms. Surface EDS showed minimal differences between the elemental compositions of the fluff and fuel cubes. However, three-dimensional (3D) pore analysis from the tomography scans showed significant differences between the fluff and fuel cube pore size distributions at the microscale level. The high porosity and irregular pore distribution seen in macroscale fluff was also present within the micro-scale fluff cube, having a much higher porosity than the fuel cube which was concentrated in a few large pore networks. In conclusion, these results indicate support for a creep driven mechanism of fluff formation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

A mechanistic, multiscale model for predicting Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles use silicon carbide (SiC) as the primary structural member and barrier against metallic fission product (FP) release. palladiums (PDs), produced by fission in the fuel kernel, can diffuse to and chemically interact with the SiC layer, degrading its structural integrity and ability to contain radioactive FPs. Existing temperature-dependent correlations for predicting Pd penetration rely on experimental data with significant scatter due to varying conditions, potentially complicating ongoing fuel qualification and licensing efforts for advanced reactors that would subject TRISO fuels to operating conditions outside of those examined in the experiments. A mechanistic model of Pd production, transport, and reaction is developed in this work to better understand and predict PD attack of SiC in TRISO particles. molecular dynamicss (MDs) simulations are utilized to calculate the Pd diffusivity in SiC grain bulk and grain boundaries. A mesoscale phase-field diffusion model, informed by the MD diffusivities, is used to develop a reduced order model (ROM) for the effect of SiC microstructure on the Pd penetration rate. The engineering scale BISON model calculates Pd production and transport, utilizing the ROM to predict penetration rates consistent with experimental data. This novel mechanistic ROM captures the effect of temperature, microstructure, and irradiation history on Pd penetration. In conclusion, these new capabilities are expected to support ongoing qualification and licensing efforts associated with near-term TRISO-fueled reactor applications.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Site-specific nanoscale characterization of zirconium hydrides in the hydride rim structure of hydrogen-charged zircaloy-4 cladding

Zircaloy-4 cladding tubes were hydrogen-charged using a static pressure hydrogen charging method to experimentally produce a zirconium-hydride rim structure similar to that observed in Zircaloy-4 cladding tubes after operation in commercial light-water nuclear reactors. Detailed characterization was performed using electron energy loss spectroscopy (EELS) and four-dimensional scanning transmission electron microscopy (4D-STEM). By mapping the position of the plasmon peak in the low-loss EELS spectrum, it was determined that the zirconium hydrides formed were predominantly solid δ-phase zirconium hydrides. 4D-STEM was used to generate phase and strain maps at nanoscale. The interactions between two zirconium hydride platelets less than 200 nm apart leads to the localized lattice rotations and possible phase change, revealing a potential hydride growth mechanism.

4D-STEM↗
DOE OSTI2025

Investigating Grain Structure and Microcracking in SiCf-SiCm Composites Using 4D-STEM

Silicon carbide (SiC) fiber-reinforced SiC matrix composites (SiCf-SiCm) are promising materials for accident-tolerant fuel (ATF) cladding in light water reactors. This paper, using four-dimensional scanning transmission electron microscopy (4D-STEM), studied the microstructure of SiCf-SiCm at nanoscale and provided grain statistics at the CVI/fiber region. Here, the results reveal that CVI region mainly contain irregular sub-micron grains (115 nm to 1800 nm) with a preferred orientation, while the fiber region has nano equiaxed grains (21 nm to 78 nm) with random orientations. Centered dark field imaging over the fiber regions verified the grain size measurement by 4D-STEM. Through 4D-STEM virtual dark field imaging and orientation mapping, intragranular propagation was identified as the fracture mechanism for a microcrack observed within the CVI region. The amorphous pyrolytic carbon layer was also shown to effectively arrest the microcrack.

4D-STEM↗
DOE OSTI2026

FIB-ToF-SIMS characterization of irradiated U-10Zr

Post-irradiation examination (PIE) is critical for the performance assessment and qualification of nuclear fuels. Secondary ion mass spectrometry (SIMS) is a powerful materials characterization technique that allows for elemental and isotopic mapping with a depth resolution greater than EDS and EPMA. However, it has not yet been applied to PIE of metallic nuclear fuel. Here, in this work, we characterize an fast neutron spectrum irradiated U-10Zr fuel sample using a time-of-flight SIMS (ToF-SIMS) system connected to a FIB/SEM system, which allows for flexible sample analysis compared to a dedicated ToF-SIMS instrument. Analysis of the resulting hyperspectral micrograph data was aided by the development of an unsupervised machine learning (ML) algorithm that iterates on existing methods to segment the 3D micrographic datasets based on the similarity of mass spectra. The results showed that the FIB-ToF-SIMS instrument was potentially capable of spatially resolving closed fission gas bubbles in 3D by continued ion sputtering of the analyzed volume. Additionally, the ML algorithm proved useful in revealing the chemical segregation of light fission products (those with an atomic mass between approximately 85–105 amu, such as ruthenium and rhodium) plus matrix zirconium, heavy fission products (those with an atomic mass between approximately 135–150 amu, such as the lanthanides) and uranium. Future studies are planned to conduct FIB-ToF-SIMS analysis on more irradiated U-Zr samples to study the constituent redistribution.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Abnormal grain growth driven by high-temperature proton irradiation in nanocrystalline Ni

In this research we examine a nanocrystalline Ni thin film exposed to high-temperature proton irradiation and compare it with as-deposited and annealed-only counterparts. Despite lacking thermal spikes typical of heavy ions, 400 °C proton irradiation drives pronounced grain growth in select grains, whereas annealing alone yields only modest coarsening. Grain-boundary statistics show fewer low-angle boundaries (10–20°) and more high-angle boundaries (55–60°), consistent with irradiation-enhanced mobility of high-misorientation boundaries. The irradiated films retain a random texture, with no evidence of texture development or sharpening. Mechanisms, such as radiation-enhanced grain boundary diffusion, beam-induced heating, and ion channeling-mediated selective grain growth, are unlikely to be the predominant drivers to explain the resultant microstructure. Instead, we suggest irradiation-induced modifications of grain-boundary structure, including possible complexion transitions, as one plausible explanation for this selective grain growth and retention of random texture. However, additional temperature–dose studies are required to confirm the mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Sensitivity study of hydrogen Soret transport in yttrium Hydride-Based nuclear fuel

Yttrium hydride is an excellent solid neutron moderator material for high temperature nuclear reactor applications due to its high hydrogen density and exceptional hydride stability at high temperatures. Despite these attractive characteristics, the details of how hydrogen behaves within yttrium hydride while temperature gradients exist are still not well understood. The evolution of the hydrogen composition profile resulting from a temperature gradient requires knowledge of hydrogen’s heat of transport, a critical parameter that has not yet been measured for this material. In this work, we perform hydride redistribution, hydrogen dissociation, and hydrogen leakage calculations while varying the Soret heat of transport of hydrogen in yttrium hydride to elucidate the sensitivity of hydride stability under temperature gradients to this parameter. This study analyzes hydride stability of a hypothetical uranium-yttrium hydride nuclear fuel design during operation of a high temperature liquid metal-cooled nuclear reactor. Assuming U-YH x could be fabricated in a physically stabilized manner, this fuel system can likely maintain hydride stability while operating at very high power densities and temperatures. We find that even though the hydrogen dissociation pressure in the gas gap does vary by several percent as the heat of transport temperature parameter is varied, the hydrogen content in the U-YH x fuel meat is relatively insensitive to this parameter over the course of a high burnup fuel cycle; this is due to yttrium hydride’s excellent hydrogen retention under the high temperature conditions considered here. Here, this suggests that hydride stability analyses are insensitive to the value of the Soret heat of transport in U-YH x under steady state liquid metal-cooled reactor conditions. However, the susceptibility to internal gas overpressurization-induced stress-rupture of the cladding during a high temperature transient is more sensitive to this parameter due to the non-linear dependence of hydrogen gas dissociation pressure vs. composition and temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Open-source microreactor design models for technoeconomic assessments

Technoeconomic analyses for advanced nuclear technologies are essential for identifying cost drivers which allow for optimizing the technology to achieve better economic performance. Microreactors are emerging as a promising and reliable-energy solution, offering inherent safety, low capital investment, and rapid deployment capabilities. Past studies have conducted technoeconomic analyses for microreactors, but there remains a need for open-source technoeconomic models that can enhance collaboration, transparency, and consistency when performing this type of analysis. The present article introduces an open-source technoeconomic model for microreactors based on bottom-up cost estimation. Since no real cost data for microreactors exists, this model leverages cost data and insights gleaned from the Microreactor Applications, Research, Validation and Evaluation (MARVEL) project. It estimates the first-of-a-kind cost of two microreactor technologies and can also calculate the N th of a kind (NOAK) cost via accounting for learning and mass factory production. The two technologies considered in this paper are the liquid–metal thermal reactor (LTMR) and the gas-cooled microreactor (GCMR). In conclusion, the goal of this study is to demonstrate bottom-up cost estimation of these microreactor technologies and provide the cost estimation models that other users can leverage for various applications such as design optimization and financial planning.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗
DOE OSTI2025

Radiation-Induced Chemical Yields of Carbon-Centered Radicals and Hydrogen Atoms from the Gamma Irradiation of n -Dodecane

Here, this study investigates the radiolytic yields of carbon-centered radicals and hydrogen atoms in n-dodecane under gamma irradiation. Utilizing molecular iodine (I 2 ) and 2,4,6-tri-tert-butylnitrosobenzene (3tBNB) as radical scavengers, we quantified the yields of molecular hydrogen and various carbon-centered radicals formed from bond scission of the solvent excited states. The yield of primary alkyl radicals was significantly lower than that of the secondary radicals, aligning with expected stabilities and bond dissociation energies. For the overall loss of n-dodecane, total yields of 0.598 ± 0.004 species/100 eV for C–C bond scission, 1.648 ± 0.012 species/100 eV for C–H bond scission, and 3.20 ± 0.10 species/100 eV for unimolecular H 2 elimination were determined. Notably, the I 2 scavenging data provided robust estimates, while the 3tBNB displayed lower efficiency in radical trapping. This research enhances our understanding of radiolytic processes in n-dodecane and offers insights for future studies on the behavior of hydrocarbons under ionizing radiation, with implications for improving UNF reprocessing strategies.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗
DOE OSTI2025

Temperature-Dependent Speciation of Ni(II) in Molten Chloride, Bromide, and Iodide Salts

Understanding the fundamental speciation and local structure of metal cations─such as nickel, which is present as a corrosion product─in molten salt media is essential for assessing their impact on the thermal and physical properties of salts used for advanced nuclear energy applications. In this study, we employed an integrated approach of combining X-ray absorption spectroscopy (XAS), UV–vis spectroscopy, and ab initio molecular dynamics (AIMD) to investigate the halide-dependent speciation of divalent nickel ions, Ni(II), in LiCl–KCl, LiBr–KBr, and LiI–KI eutectic salt mixtures from room temperature to 600 °C. Our findings show that both halide type and temperature significantly influence the local coordination of nickel in these molten salt systems. A notable aspect of Ni(II) speciation in LiI–KI salts is the formation of a polyiodide species. In conclusion, our findings provide critical insights into metal ion speciation in molten salt systems, enhancing our understanding of the factors that govern the physicochemical properties of these complex fluids.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗