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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 181 records · Page 10

Effects of hydrogen partial pressure on crack initiation and growth rate in vintage X52 steel

There is an increasing interest in ensuring compatibility of existing natural gas infrastructure with conveyance of hydrogen, especially for vintage (pre-1970s) pipeline steels. While hydrogen is known to affect the fatigue and fracture resistance of these materials, there is a lack of data on its effects on crack initiation at low hydrogen partial pressure. To address this gap, the current work presents a series of fatigue tests on vintage API Grade X52 steel in pure nitrogen, air and gaseous hydrogen at partial pressures of 1 and 207 bar. Circumferential notch tension (CNT) specimens with direct current potential difference (DCPD) measurements are used to get S–N curves for crack initiation and failure, and compact tension (CT) tests to assess crack growth rates. Results indicate that air accelerates crack initiation, low hydrogen partial pressure affects the crack growth rate, and higher pressures have the largest impact on both. Surprisingly, crack initiation is faster in air than at 1 bar hydrogen partial pressure. The CNT tests also reveal that the orientation of the banded microstructure has no effect on the crack initiation site, but it influences its growth behavior. Moreover, fractography shows that hydrogen also promotes instances of quasi-cleavage and intergranular fracture, linked to embrittlement of the material. Here, these results demonstrate that, while hydrogen may impact the entirety of the fatigue process, its effects on the early stages of damage accumulation become relevant only at larger pressures. More comprehensive studies of crack initiation in hydrogen atmospheres will be critical to future codes and standards for hydrogen infrastructure.

Circumferential notch tension↗

From Filamentary Failure to Durable Halide Perovskite Memristors

Halide perovskites have emerged as promising materials for memristive devices. While their pronounced electrochemical reactivity and fast ionic mobility enable numerous advantages including low-voltage operation and fast switching, the same features also render perovskite-based memristors vulnerable to metallic shunts and poor endurance, limiting their practical applications. Here, we elucidate both the resistive switching and failure mechanisms in perovskite memristors with a fluorine-doped tin oxide (FTO)/methylammonium lead triiodide (MAPbI3)/Ag structure and demonstrate a strategy to substantially enhance device durability. As opposed to commonly invoked filamentary mechanisms, electrical, structural, and spectroscopic analyses reveal that resistive switching arises from interfacial barrier modulation by reversible Ag redox reactions that drive electrochemical doping/dedoping within the perovskite. Device failure, however, originates from metallic Ag0 filamentation that ultimately forms permanent conductive pathways. Introducing an ultrathin Al2O3 interlayer at the inert-electrode interface improves device endurance by more than 30-fold, exceeding 15,000 switching cycles, without compromising other performance metrics. Interfacial characterization indicates that the Al2O3 layer modifies wettability of Ag deposits, promoting planar island growth rather than through-film filamentation. These findings establish a clear link between interfacial electrochemistry, metal precipitation behavior, and memristor reliability, highlighting inert-electrode interfacial engineering as an effective pathway toward durable perovskite-based memristors.

14 SOLAR ENERGY↗

Investigation of Abnormal Level Control Oscillations in a BWR Feedwater System

In the long-term operation of nuclear power plants, the aging of systems, structures, and components can lead to maintenance issues that must be dealt with to maintain cost-effective plant operations. One common issue affecting the currently operated boiling water reactors is the onset of unexpected level oscillations in feedwater heaters. This phenomenon can cause excessive cycling of drain valves and lead to premature failures. In this work, we develop a dynamic model of a set of feedwater heaters to determine the root cause of oscillations observed in an operating plant. Simulation results of various transient scenarios were used to investigate the effects of the controller parameters, boundary conditions, and possible valve and instrument issues. The analysis led to the conclusion that the most likely causes of the observed self-sustained oscillations in the system are the nonlinear behaviors of the drain valve and the level transmitter induced by degraded equipment condition. In conclusion, a partial plug of the pressure line used for level sensing in the system can account for a significant deadtime in the level transmitter, a nonlinear effect shown to induce self-sustained oscillatory behaviors.

Boiling water reactors↗

Reformulating a Gurson-based dynamic damage model and demonstrating improved predictive power and numerical robustness

The original Tepla (TEnsile PLAsticity) ductile damage model, based on the Gurson yield surface, has long been used to model damage evolution and material failure under dynamic loading. Unfortunately, Tepla suffered from mesh sensitivity, numerical instability, and limited predictive capability. Here, we theoretically reformulate Tepla to address these issues. We especially focus on the prediction of porosity, which is the key state variable used for modeling ductile damage, as compared to more easily measured surface velocities, which are at best an indirect measure of damage. Key model changes include separating the viscosity during volumetric void growth from underlying shear strength behavior and switching to an iterative bisection solver. The new Tepla is then calibrated on incipient spall experiments on half-hard copper and tantalum, which demonstrate its ability to simultaneously fit the model to recovered porosity distributions and measured surface velocities, a stringent test. Improved numerical behavior, such as greatly reduced mesh sensitivity, is also shown in those simulations. Finally, the new Tepla model is applied to several high-explosive loaded, sweeping wave experiments, showing the ability of the model to predict behavior on tests with significantly different loading conditions and histories than the calibration data.

36 MATERIALS SCIENCE↗

Operational Parameter Database for Molten Salt Thermal Energy Storage Tank Modeling

The second generation of concentrated solar power (CSP) plants is characterized by the use of a central receiver (either cavity or external), two molten nitrate salt tanks (60 wt.% NaNO 3 and 40 wt.% KNO 3 ), and a steam Rankine power-generation cycle connected through a primary heat exchanger. Molten salt thermal energy storage (TES) tanks have been widely deployed in commercial CSP plants worldwide and have been essential for increasing plant dispatchability and capacity factor, while also reducing the levelized cost of electricity (LCOE). These systems enable energy storage at the gigawatt-hour scale, typically providing 6 to 17 hours of storage duration. Despite being a commercial technology, the multiple failures observed after only a few months or years of operation in plants around the world demonstrate the technology's relative infancy and highlight the need for further research to improve its reliability. The National Laboratory of the Rockies (NLR), in collaboration with industry partners and academic and research institutions, has been leading multiple projects funded by the U.S. Department of Energy (DOE). These projects focus on addressing molten salt tank failures by improving tank design and welding fabrication practices, evaluating new alloys and weld fillers, and providing guidelines for tank commissioning and safe operation. In particular, this report presents modeling results on the effect of key tank operation parameters during 60 minutes of operation, including the mass flow rate and temperature of the salt inflow, tank salt inventory temperature, and inventory level for a representative molten salt tank design. These results form a database of tank operation behaviors that captures the effects of each specific parameter during charging, charging/discharging, and discharging processes.

14 SOLAR ENERGY↗

CRCNS US-France Research Proposal: Collaborative Research: Encoding reward expectation in Drosophilia

The fruit fly Drosophila melanogaster has been a valuable model for investigating the genetic and neural bases that underlie learning and memory. Early and most current studies use basic behavior conditioning protocols to study learning in controlled laboratory settings. More recently, the ability to transgenically manipulate many of the brain neurons in the fruit fly with exquisite specificity, and the recent knowledge of the synaptic ‘connectome’ of the fruit fly brain, makes these animals almost unique as a comprehensive model for studies of learning, memory and motivated behavior. In fact, the connectome has revealed many types of new connections that had until now been overlooked. Within this context, the thesis of this proposal is that studies of learning and memory will be greatly enhanced by using more sophisticated means for evaluating memory representations, such as have been developed in vertebrates, and combining those studies with information from the connectome guided by computational modelling. We propose to push beyond the boundaries of existing conditioning protocols for fruit flies to investigate more complex memory representations. In particular, we will investigate the function of reinforcement pathways in relation to the absence of expected reinforcement. More specifically, we propose a series of experiments designed to investigate the memory representations in fruit flies when an expected consequence of a Conditioned Stimulus (CS) fails to occur. Although studies have evaluated how this failure can establish extinction memory for the CS, our studies will go beyond studying extinction. Specifically, we predict that in Drosophila when a CS is associated with a failed expectation of an appetitive food reinforcement it will acquire aversive value, and vice versa for a failed expectation of an aversive reinforcer. We combine these studies with manipulations of reinforcement pathways in the CNS inspired from the connectome, iteratively knitted in with established computational models. Intellectual Merit: The concept of reinforcement expectation and incentive contrast have been influential in the development of studies of associative learning in mammals. These questions are particularly challenging to answer in vertebrates because they require exquisite cellular, temporal, and genetic specificity of experimental manipulations. The recent development of work with identified neurons and their connectomes makes the larval and adult fly brains ripe as models for pushing our understanding of neural bases for these higher- order conditioning phenomena. Broader Impacts: Public health: These analyses and the conceptual framework of prediction error processing underlying them have a profound impact on our understanding of reinforcement-related behavior in humans, including monetary rewards and the mnemonic consequences of traumatic experiences, and for pathologies of the dopamine reinforcement system. Educational: This project will provide interdisciplinary training for postdoctoral researchers, Ph.D. and undergraduate students. The PIs will act as co-supervisors or mentors of students working in the different labs via face-to-face and internet-based technologies. We will also work with ASU’s award-winning Ask- A-Biologist program. This is an online science program designed to enrich the learning experiences of students of all ages and to provide classroom material for use by K-12 teachers. We will develop an extension of a game developed under a prior NSF award, and the new game will include modules to teach K-12 students about how insects learn. We will also integrate into the AAB site a program developed by a collaborator (B Gerber) at the Leibniz Institut für Neurobiologie, Magdeburg, and now in use in schools in Germany, to teach K-12 students how to train animals using the fruit fly larval learning paradigm. Underrepresented groups: All PIs will work with their university offices of Academic Diversity and Equal Opportunity for reaching underrepresented students.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanical properties, strain hardening, and fracture behavior of ultrasonic additively manufactured Zircaloy-4 after low-temperature neutron irradiation

Ultrasonic additive manufacturing (UAM) is a solid-state, layer-by-layer advanced manufacturing process that has the potential to create custom spatially controlled composites with embedded wires and sensors for nuclear component manufacture. For this work, to assess the feasibility of using UAM for nuclear-relevant materials research, the technique was used to produce a 3.5-mm-thick Zircaloy-4 plate for irradiation testing. The UAM Zircaloy-4 specimens were irradiated in the High Flux Isotope Reactor at a target irradiation temperature of 117 °C to 2.9 displacements per atom (dpa) to assess differences in irradiation-hardening behavior as a function of alloy processing path. The UAM and reference baseplate (BP) materials increased in yield strength by 372±27 MPa and 346±21 MPa, respectively, and both suffered significant reductions in uniform and total elongation attributed to irradiation hardening at low-temperature. Although the materials had similar nanoscale defect structures, including nanoscale black dot/loop features and strain-induced dislocation channels, the UAM material’s processing-related defects resulted in accelerated strain localization and failure as demonstrated by lower post-irradiation uniform elongation of UAM specimens (0.5 %) compared to BP (1.5 %) material. The UAM material also showed considerable anisotropy in mechanical response due to crack propagation along weld boundaries, resulting in differences in strength & ductility when tested parallel and perpendicular to the prior UAM build orientation. Therefore, although the fundamental irradiation response of UAM-processed Zircaloy-4 was phenomenologically comparable to that of BP reference material, additional optimization of the UAM processing is needed to produce irradiation-resistant and nuclear-relevant materials.

Digital image correlation↗

A statistical representation of bond coating oxidation under environmental barrier coatings

Environmental barrier coatings (EBCs) protect SiC-based ceramic matrix composites (CMCs) in turbine hot sections from high-temperature volatilization in combustion gases. The formation of a SiO 2 thermally grown oxide (TGO) is expected under the EBC after long-term operation. The oxidation resistance of the EBC is understood as a life-limiting factor for the CMC, and this work predicts long-term oxidation behavior under EBCs through a simple statistical approach. Specimens were exposed to 1350°C isothermal conditions for 100-h thermal cycles in flowing steam for up to 1000 h. The EBC morphology, SiO 2 thickness, and SiO 2 cracking behavior were assessed. Using thousands of SiO 2 thickness measurements across many millimeters of the interface, a realistic representation of the entire TGO was captured via a lognormal distribution. The lognormal fit parameters were extrapolated out to 25 000 h to assess the degree of SiO 2 growth, the spread of SiO 2 thicknesses related to the rough oxidizing interface, and percentages of the intermediate bond coating consumed. In conclusion, local interfacial defects from the coating deposition process are identified as local failure points for EBC—CMC systems.

SiO 2↗

Siloxane-modified polycarbosilane flexible Prepregs for fabrication of ceramic matrix composites via compression molding and PIP densification

For this work, the development of ceramic matrix composites (CMCs) using 5 harness satin carbon fiber fabric impregnated with commercial polycarbosilane precursor plasticized by siloxane copolymer was investigated aiming to improve wetting behavior and shape conformability. The polycarbosilane precursor and polysiloxane plasticizer were mixed at varying weight ratios to obtain flexible preceramic resin prepreg cloths. 13 plies of preceramic polymer prepreg cloths were stacked in 0/90° layup and cured by compression molding, followed by densified via PIP process. The CMCs were densified with eight PIP cycles followed by final crystallization at 1600 °C. The CMCs made with 10 wt% polysiloxane loading showed lower viscosity of the prepreg resin as well as higher strength and displacement to failure compared to those fabricated from unplasticized polycarbosilane prepolymer. In contrast, at higher concentration of plasticizer, viscosity of the prepreg resin increased, and the CMC became more brittle; however, it exhibited considerably higher thermal conductivity.

Carbosilane↗

Streaming Analytics for Anomaly Detection in Large-Scale Data

Anomalous behavior poses serious risks to assured performance and reliability of complex, high-consequence systems. For spaceborne assets and their state-of-health (SOH) telemetry, the challenges of high-dimensional data of varying data types are compounded by computational limitations from size, weight, and power (SWaP) constraints as well as data availability. Automated anomaly detection methods tend to perform poorly under these constraints, while current operational approaches can introduce delays in response time due to the manual, retrospective processes for understanding system failures. As a result, presently deployed space systems, and those deployed in the near future, face situations where mission operations might be delayed or only be able to operate under degraded capabilities. Here, we examine a near-term lightweight solution that provides real-time detection capabilities for rare events and assess state-of-the-art anomaly detection techniques against real SOH telemetry from space platforms. This report describes our methodology and research, which could support more automated capabilities for comprehensive space operations as well as for other resource-constrained edge applications.

97 MATHEMATICS AND COMPUTING↗

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tunable amorphous carbon films formed on ultralow wear, Pt–Au alloys

The mechanocatalytic formation of carbonaceous films at the interface between sliding metallic contacts is simultaneously advantageous for reducing friction and adhesion in several tribological applications and detrimental for electrical contacts as they can induce device failure by increasing the contact resistance. Yet, remarkably little is still known about the chemistry, structural and mechanical properties, and tunability of these interfacial layers. In this study, we performed contact pressure-dependent tribological experiments in dry nitrogen containing trace organics on four, nanocrystalline Pt–Au alloys ([Au] from 0 at.% to 10 at.%) – a promising class of alloys for ultralow wear and electrical contact applications. The ex-situ, multi-technique characterization results did not only provide insights into the chemical nature and mechanical behavior of the mechanocatalytic, carbon-rich films formed on Pt–Au surfaces, but also revealed the interplay between catalytic and mechanochemical tribofilm formation controlled by the composition-dependent electronic structure of the Pt–Au substrate and the applied contact pressure. The results of this work provide guidelines for tailoring nanocrystalline alloys to control their mechanocatalytic activity on the basis of variations of the alloy mechanical properties and element's electronic structure with the alloy stoichiometry.

AFM↗

Thermochemical Modeling of Radionuclide Vapor-Liquid Equilibria in Sodium Pools for SFR Mechanistic Source Term Analysis

Mechanistic source term (MST) analysis of sodium fast reactors (SFR) requires understanding of various radionuclide (RN) transport phenomena influencing potential releases from the fuel to the environment. One such phenomenon includes the retention or release of RNs from the sodium coolant pool, representing the step after possible fuel failures and influencing transport to the cover gas region. Thermodynamic vapor-liquid equilibria (VLE) calculations were performed on systems representing SFR sodium pools containing oxygen impurities and radionuclide (RN) inventories. First, an assessment and recreation of a previously developed thermodynamic database was completed, including updates to thermodynamic parameters. The RN inventories used in VLE calculations represented hypothetical source terms that might be released to the pool during previously analyzed fuel failure scenarios. The calculations were performed for all possible combinations of sodium pool size (i.e., total oxygen) and number of failed fuel pins (i.e., total RNs). In this way, multiple ratios of the RN relative to the oxygen impurity (RN:O) were compared for their impact on RN volatility, which is discussed in terms of the vapor fraction (VF), defined as the fraction of the RN that is calculated to exist in the vapor phase at equilibrium above condensed phases of that element. Similar trends in VLE behavior are seen in the equilibrium calculation results for elements of similar chemistry, and for some element types, it was found that the RN:O ratio can be important due to oxide formation, which typically exist in the condensed phase.

Shahbazi, Shayan↗

AUTOMATIC GENERATION OF EVENT TREES AND FAULT TREES: A MODEL-BASED APPROACH

In the past few decades, increasing complexity in modern engineering systems has been driven by the integration of a large number of components and by the fact that the system operations involve many disciplines (e.g., thermal-hydraulics, plant operations, cyber-security). Current safety/reliability modeling approaches to such systems are labor intensive, difficult to learn, and rely heavily on simplistic Boolean logic to depict failure propagation and accident progression. While these methods serve well for simple systems (i.e., linear causal systems with limited small inter- and intra-system interactions), their results are difficult to verify when modeling complex systems (typically performed through the extensive use of modeling assumptions). The development of new methods is addressed to meet these challenges through a model-based system engineering (MBSE) lens. Under MBSE philosophy, every aspect of the system (form or function) is represented by a model that completely characterizes its architecture or behavior. MBSE approach greatly improves the management of design, analysis and verification of complex systems. An integration of Dynamic Probabilistic Risk Assessment (DPRA) methods with MBSE models is proposed to perform safety/reliability analyses of engineering systems. In particular, MBSE representation of the system (performed using Systems Modeling Language [SysML]) is coupled with DPRA methods to automatically generate event trees and fault trees.

97 - MATHEMATICS AND COMPUTING↗

Machine-learning interatomic potentials for interfaces in all-solid-state batteries: Perspectives on training data, model selection, and validation

Interfaces play a pivotal role in dictating the performance and reliability of all-solid-state batteries (ASSBs), where complex electro-chemo-mechanical phenomena at grain boundaries (GBs) and interfaces can lead to degradation and failure. Traditional atomistic simulation methods, such as first-principles calculations and classical molecular dynamics, face limitations in modeling these interfaces due to either high computational cost or insufficient transferability to the diverse atomic environments evolving at interfaces. Machine-learning interatomic potentials (MLIPs) have emerged as a transformative approach, enabling large-scale, high-accuracy simulations of disordered and chemically complex systems by leveraging the predictability of machine learning models trained on first-principles data. Recent applications of MLIPs have demonstrated their ability to capture intricate behaviors at ASSB interfaces, including ion transport, interfacial evolution, and degradation mechanisms, with accuracy and efficiency unattainable by conventional methods. This prospective paper presents comprehensive analysis and practical guidance for MLIP development for GBs and interfaces in ASSBs, with a focus on three key pillars: data generation, model selection, and validation. Here, we review the current state of MLIP applications for GBs and interfaces in both general and ASSB-specific materials, highlighting best practices and challenges in constructing diverse and representative datasets, choosing appropriate machine learning architectures, and rigorously validating model performance. We also discuss emerging strategies and opportunities for improved reliability and efficiency of MLIPs to simulate realistic interfaces in ASSBs.

Energy - Storage↗

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel Jana Howard1,3, Guang Yang3, Haiyan Zhao1*, Patrick Warren4, Tiankai Yao3, Steven Cavazos4 Elizabeth Sooby Wood4*, Ching-heng Shiau2 1 University of Idaho, Environmental Science, Idaho Falls, Idaho, USA 2 Boise State University, Microscopy and Characterization Suite, Idaho Falls, Idaho, USA 3 Idaho National Laboratory, Idaho Falls, Idaho, USA 4 University of Texas San Antonio, Department of Physics and Astronomy, San Antonio, Texas, USA *Corresponding author: haiyanz@uidaho.edu; elizabeth.soobywood@utsa.edu Tri-structural Isotropic (TRISO) particle fuel is the preferred choice for the newest and next-generation high-temperature nuclear reactors due to its robust construction [1]. The fuel design effectively contains fission products inside the particle at extremely high temperatures [2]. However, the effect of transition metal fission products on fuel performance and structural integrity remains largely unknown, creating uncertainties in predicting fuel performance and potential failure mechanisms [2]. For example, palladium (Pd) has a strong tendency to form intermetallic phases with uranium (U). These new phases tend to be hard and brittle which could lead to fracture of fuel kernel during irradiation [3,4]. Pd is not normally produced in high concentrations in normal fission reactions however, driving the production of Pd into the locality of a Uranium Oxycarbide (UCO) nuclear fuel provides an opportunity to closely observe the diffusion and chemical interactions. This study focuses on detailed transmission electron microscopy characterization of the intermetallic phases formed by the interaction between a UCO kernel and a Pd bar after annealing at 1100 °C for 100 hours. Figure 1 provides an overview of the UCO kernel in contact with the Pd bar. The UCO-Pd sample surface was examined using a Focused Ion Beam (FIB) Quanta 3D FEG FEI in VCD detector mode at 10kV, 83pA to reveal surface features. Several key surface features in the interaction region were observed including: (1) a small area with dendritic microstructure, (2) color contrast near the UCO kernel and Pd boundary, and (3) darker and lighter regions throughout the sample surface. To analyze diffusion behavior, FIB was used to prepare lamellae from five different areas of the UCO-Pd sample, as well as one for the as-received sample. These lamellae were examined using a Scanning Transmission Electron Microscope ThermoFisher Spectra 300 (STEM-Spectra). Energy Dispersive Spectroscopy results confirmed the diffusion between the UCO fuel and Pd bar. Figure 2 shows the identified phases of UC, UO2, and Pd dispersed throughout the interaction region. It was also found that the Pd concentration decreases as the radial distance from the UCO-Pd interface increases. The Pd concentration was 36.93% atomic fraction 11µm from the interaction region then decreased to 7.51% atomic fraction at 257 µm away from the interaction region. Figure 3 shows how concentrations of U and Pd vary across the interaction zone, highlighting the extent of diffusion. This study confirms that Pd interacts with surrounding material to form U-Pd phase and diffusion zones. These diffusion zones vary in composition depending on its radial distance from the point of contact with the Pd bar. These findings contribute to a deeper understanding of the fission product behavior in high temperature nuclear fuels, aiding in the prediction and mitigation of potential fuel degradation mechanisms. A B C Fig. 1. SEM micrographs of UCO fuel kernel in contact with solid Pd bar and the lift out locations. Figure 1A shows UCO fuel kernel in contact with solid Pd bar. Figure 1B shows a higher magnification image of the UCO fuel-Pd interaction zone. Figure 1C shows lift out sites for the lamellae. A B C Fig 2. EDS maps reveal the distribution of U, O, and Pd in location 3. Figure 2A shows the distribution of uranium. Figure 2B shows the distribution of oxygen. Figure 2C shows the distribution of palladium. A B C Fig 3. Palladium and uranium concentration across interaction zone in location 2. Figure 3A shows EDS map of lift out number 2. Figure 3B shows a zoomed in EDS map taken from the interaction zone. Figure 3C shows a line graph of uranium and palladium concentrations across the interaction zone. References: 1. B.E. Wells, N.R. Phillips, K.J. Geelhood. Pacific West Laboratory. (2021). TRISO Fuel: Properties and Failure Modes. https://www.nrc.gov/docs/ML2117/ML21175A152.pdf (Accessed January 16, 2025). 2. American Nuclear Society. TRISO Fuel Development Progresses in INL, ORNL. https://www.gen-4.org/gif/upload/docs/application/pdf/2014-03/nov13nn_fuel_reprint.pdf (Accessed January 16, 2025) 3. Clark R.A., M.A. Con

36 - MATERIALS SCIENCE↗

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel Jana Howard1,3, Guang Yang3, Haiyan Zhao1*, Patrick Warren4, Tiankai Yao3, Steven Cavazos4 Elizabeth Sooby Wood4*, Ching-heng Shiau2 1 University of Idaho, Environmental Science, Idaho Falls, Idaho, USA 2 Boise State University, Microscopy and Characterization Suite, Idaho Falls, Idaho, USA 3 Idaho National Laboratory, Idaho Falls, Idaho, USA 4 University of Texas San Antonio, Department of Physics and Astronomy, San Antonio, Texas, USA *Corresponding author: haiyanz@uidaho.edu; elizabeth.soobywood@utsa.edu Tri-structural Isotropic (TRISO) particle fuel is the preferred choice for the newest and next-generation high-temperature nuclear reactors due to its robust construction [1]. The fuel design effectively contains fission products inside the particle at extremely high temperatures [2]. However, the effect of transition metal fission products on fuel performance and structural integrity remains largely unknown, creating uncertainties in predicting fuel performance and potential failure mechanisms [2]. For example, palladium (Pd) has a strong tendency to form intermetallic phases with uranium (U). These new phases tend to be hard and brittle which could lead to fracture of fuel kernel during irradiation [3,4]. Pd is not normally produced in high concentrations in normal fission reactions however, driving the production of Pd into the locality of a Uranium Oxycarbide (UCO) nuclear fuel provides an opportunity to closely observe the diffusion and chemical interactions. This study focuses on detailed transmission electron microscopy characterization of the intermetallic phases formed by the interaction between a UCO kernel and a Pd bar after annealing at 1100 °C for 100 hours. Figure 1 provides an overview of the UCO kernel in contact with the Pd bar. The UCO-Pd sample surface was examined using a Focused Ion Beam (FIB) Quanta 3D FEG FEI in VCD detector mode at 10kV, 83pA to reveal surface features. Several key surface features in the interaction region were observed including: (1) a small area with dendritic microstructure, (2) color contrast near the UCO kernel and Pd boundary, and (3) darker and lighter regions throughout the sample surface. To analyze diffusion behavior, FIB was used to prepare lamellae from five different areas of the UCO-Pd sample, as well as one for the as-received sample. These lamellae were examined using a Scanning Transmission Electron Microscope ThermoFisher Spectra 300 (STEM-Spectra). Energy Dispersive Spectroscopy results confirmed the diffusion between the UCO fuel and Pd bar. Figure 2 shows the identified phases of UC, UO2, and Pd dispersed throughout the interaction region. It was also found that the Pd concentration decreases as the radial distance from the UCO-Pd interface increases. The Pd concentration was 36.93% atomic fraction 11µm from the interaction region then decreased to 7.51% atomic fraction at 257 µm away from the interaction region. Figure 3 shows how concentrations of U and Pd vary across the interaction zone, highlighting the extent of diffusion. This study confirms that Pd interacts with surrounding material to form U-Pd phase and diffusion zones. These diffusion zones vary in composition depending on its radial distance from the point of contact with the Pd bar. These findings contribute to a deeper understanding of the fission product behavior in high temperature nuclear fuels, aiding in the prediction and mitigation of potential fuel degradation mechanisms. A B C Fig. 1. SEM micrographs of UCO fuel kernel in contact with solid Pd bar and the lift out locations. Figure 1A shows UCO fuel kernel in contact with solid Pd bar. Figure 1B shows a higher magnification image of the UCO fuel-Pd interaction zone. Figure 1C shows lift out sites for the lamellae. A B C Fig 2. EDS maps reveal the distribution of U, O, and Pd in location 3. Figure 2A shows the distribution of uranium. Figure 2B shows the distribution of oxygen. Figure 2C shows the distribution of palladium. A B C Fig 3. Palladium and uranium concentration across interaction zone in location 2. Figure 3A shows EDS map of lift out number 2. Figure 3B shows a zoomed in EDS map taken from the interaction zone. Figure 3C shows a line graph of uranium and palladium concentrations across the interaction zone. References: 1. B.E. Wells, N.R. Phillips, K.J. Geelhood. Pacific West Laboratory. (2021). TRISO Fuel: Properties and Failure Modes. https://www.nrc.gov/docs/ML2117/ML21175A152.pdf (Accessed January 16, 2025). 2. American Nuclear Society. TRISO Fuel Development Progresses in INL, ORNL. https://www.gen-4.org/gif/upload/docs/application/pdf/2014-03/nov13nn_fuel_reprint.pdf (Accessed January 16, 2025) 3. Clark R.A., M.A. Con

36 - MATERIALS SCIENCE↗

Establishing the Stability of Cross-Linked Poly(ethylene oxide) Blended with Poly(pentyl malonate) against Lithium Metal Anodes

This work focuses on an electrolyte obtained by infusing linear poly(pentyl malonate) (PPM) chains into cross-linked poly(ethylene oxide) (PEO). A lithium salt is added to enable ion transport. Obtaining this electrolyte is only possible because PPM is miscible with PEO irrespective of salt concentration. The properties of this electrolyte are compared against two benchmarks: an electrolyte obtained by infusing linear PEO into cross-linked PEO and cross-linked PEO with no added linear polymer. Measurements of storage moduli and ion transport efficacies are found to be similar across the three electrolytes, suggesting similar stability behavior against lithium metal anodes, based on current theoretical models. Instead, the PPM infused electrolyte outperforms the other two electrolytes. In the cycling tests, the current supported by the PPM infused electrolyte was a factor of 20 higher than that of the PEO infused electrolyte and a factor of 4 higher than that of the cross-linked PEO electrolyte. In the unidirectional plating experiments, the other two electrolytes fail after about 4 h or less, while the PPM containing electrolyte did not fail during the 140 h testing period. Insight into the nature of failure modes was obtained using synchrotron hard X-ray microtomography.

Gido, Lily [University of California, Berkeley]↗