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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗

DOE OSTI2024

Phase-Field Modeling of Thermally-Grown Oxide and the Induced Damage Evolution in Environmental Barrier Coatings

The advent of next-generation hydrogen-based engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the critical role of thermally grown oxides (TGO) in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and microstructural evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

Cheng, Tianle↗

DOE OSTI2024

Polymer Additive Manufacturing for Marine Renewable Energy Applications: Best Practices, Research Trends, and Current Challenges

Additive manufacturing (AM) is a rapidly growing technology space, not only for prototyping, but is also becoming more feasible at larger scales and increasing component quantities. There are a large variety of AM processes and materials available to users and effectively applying those processes and materials to a specific use case can be challenging. One specific area where AM could be particularly beneficial is marine renewable energy (MRE). Not only is MRE a relatively nascent industry with a near-term need for rapid deployments and prototype testing, but developers could also see long-term benefits from the broad variety of environmentally resistant materials available and the ability to manufacture complex geometries that AM technologies offer. Over the past 4 years, AM materials have played an increasing role in the Advanced Materials project; a multi-year, multi-laboratory research project funded by the U.S. Department of Energy's Water Power Technologies Office, with the main goal of reducing barriers to the adoption of complex materials in the MRE industry. The primary focus of this project is to develop test methods and generate datasets to understand the long-term performance of advanced materials in marine environmental and address specific material challenges as they arise. This report provides an extensive overview of the research that has been performed specific to AM polymers as part of the Advanced Materials project. The intention of this document is to provide recommendations of best practices with regards to material selection, mechanical test method development, and design practices, lessons learned along the way, current research trends, and ongoing challenges with regards to AM polymers in marine environments. In particular, this report focuses on several key aspects: Material and process selection, Environmental conditioning and subsequent degradation quantification through mechanical characterization, Composite reinforcements on AM polymer substrates, Adhesion of instrumentation for mechanical characterization and loads measurements, Protective coatings for preventing biofouling and water ingress, Other MRE case studies where AM has proved particularly useful. Ultimately, we hope that the test methods that have been developed, data generated, and lessons learned from this research will be valuable to the MRE community (researchers and developers alike), as well as other industries, and can be used as a reference point as the respective MRE and AM industries continue to grow and mature.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Influence of Solidification Velocity on Partitioning and Precipitate Evolution in a Multicomponent, Soft Magnetic Alloy Processed by Laser Melting

Multicomponent alloys have recently been shown to overcome the structural-functional barrier associated with soft magnetic materials. Here, single laser tracks have been used to investigate the effects of solidification velocity on the Al 7 Fe 32.6 Co 27.7 Ni 27.7 Ta 5 (at pct) alloy. Ta-rich cell wall partitioning was shown to affect the final distribution and size of the precipitating L1 2 phase, after aging. These findings demonstrate that solidification rate control offers the potential to tailor localized performance in alloys with size-dependent precipitation properties.

Brookins, Jeffrey M. [Oak Ridge National Laborator↗

DOE OSTI2023

Dislocation generation in diamond under extreme loading

Diamond is, by virtue of its high bonding forces and Peierls-Nabarro barrier stresses, among the hardest materials on earth due to the difficulty of generating and moving dislocations. We demonstrate, using molecular dynamics and analytical calculations, that the generation of defects is dependent on loading orientation. Shock-loading single-crystal diamond along [001] and [011] to a stress of 137 GPa did not reveal dislocations, whereas loading along [111] generated profuse dislocations. The introduction of a void at the latter orientation generated dislocations at 72.6 GPa. Two slip systems were identified: <011>{100} and <112>{111}. The threshold for plastic deformation in diamond is orientation dependent and significantly lower than reported in previous studies: 0.14 G (shear modulus). The void collapse generated localized amorphization for [001]. In conclusion, these results on the anisotropy of plasticity and void effects have relevance for the improvement of symmetry in the collapse of diamond capsules in inertial fusion experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Self-Organization and Nitrogen Incorporation in Diamond-Like Carbon Microstructures Synthesized by Nonthermal Plasma

Nonthermal plasma activation of light alkanes is an encouraging decarbonization strategy to produce chemicals or fuels from abundant and/or flared carbon sources. However, prolific carbon growth on both the catalyst and electrode has limited its practicality, requiring additional knowledge of the carbon structure and growth mechanism before breakthroughs are realized. Furthermore, visual evidence is provided for nonuniform diamond-like carbon (DLC) microstructures that materialize in a coaxial dielectric barrier discharge (DBD) reactor flowing ethane and He at 278 K. Through a connection to known behaviors of DBD microdischarge patterns, the microstructure spacing was controlled by altering the applied voltage (ΔV) of the plasma or the burning voltage (U b ). Additionally, carbon valorization through nitrogen incorporation from N 2 was explored as an orthogonal solution to carbon mitigation, with N/C values >0.25 achieved and both sp 2 and sp 3 C–N bonding observed in the microstructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

ReaxFF Parameter Set for Boron Clusters and Icosahedral Boron Crystals: Comparison with Density Functional Theory and Machine-Learning Potentials

Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.

boron↗

DOE OSTI2021

Seismic Performance of Deeply Embedded Conceptual Advanced Reactors: Three-Dimensional Nonlinear Soil-Structure Interaction Analyses

The U.S. Nuclear Regulatory Commission’s functional containment concept provides advanced nuclear power plant designers with more flexibility in terms of the civil/structural design if the appropriate set of barriers for prevention of radioactive material release exist. Some of the conceptual advanced reactor structures, without the traditional pressure boundaries of large containment structures, are proposed to be deeply embedded or buried into soil. This approach is expected to provide (1) lesser seismic demands on the structures and safety-critical structures, (2) eased regulatory efforts and overall design against other external hazards such as aircraft impact, and (3) overall cost savings. Further, one of the important aspects of assessing the technical and economic viability of deeply embedding advanced reactor buildings is to assess the seismic performance with the understanding of effects with material and geometric nonlinearities. This study investigates the seismic response of deeply embedded or buried advanced reactors by conducting three-dimensional nonlinear soil-structure interaction analyses. Although the results indicate that there is a general trend of decreased seismic response with increased embedment depths, the change in the dynamic environment with different embedment depths and the nonlinear environment under high-intensity seismic inputs may result in increased peak response at increased embedment depths.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Inducing thermodynamically blocked atomic ordering via strongly driven nonequilibrium kinetics

Ultrafast light-matter interactions enable inducing exotic material phases by promoting access to kinetic processes blocked in equilibrium. Despite potential opportunities, actively using nonequilibrium kinetics for material discovery is limited by the poor understanding on intermediate states of driven systems. Here, using single-pulse time-resolved imaging with x-ray free-electron lasers, we found intermediate states of photoexcited bismuth nanoparticles that showed kinetically reversed surface ordering during ultrafast melting. This entropy-lowering reaction was further investigated by molecular dynamics simulations to reveal that observed kinetics were thermodynamically buried in equilibrium, which emphasized the critical role of electron-mediated ultrafast free-energy modification in inducing exotic material phases. This study demonstrated that ultrafast photoexcitations of electrons provide an efficient strategy to induce hidden material phases by overcoming thermodynamic barriers via nonequilibrium reaction pathways.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Advanced Multi-Tube Mixer Combustion for 65% Efficiency (Final Report)

This project targeted advanced low NOx combustion for advanced gas turbines capable of 65%, or greater, efficiency in combined cycle application. This technology advancement has further potential to benefit gas turbines used in coal based IGCC applications with pre-combustion carbon capture and hydrogen as the resulting fuel. The program developed and synthesized the most advanced combustion system capable of achieving low NOX emissions up to turbine inlet temperatures of 3100F while also supporting the load-following needs of a modern grid. The combustion system contributes to the overall gas turbine efficiency goal by setting the maximum cycle temperature achievable for a given NOX level and by minimizing the through-combustor air flow pressure drop. Focus areas for this project targeted maximizing the turbine inlet temperature entitlement, as constrained by emissions considerations. The design also minimized parasitic air flow pressure drop by using advanced cooling techniques and performance materials selections and by minimizing hot surface area. These two technology objectives (maximum, emissions-compliant cycle temperature and minimum air flow pressure drop) were integrated into a prototype design. The primarily analytical project sought to identify the most promising technologies to meet these objectives. Additional critical “jugular” data were obtained from multi-tube mixer tests to realize the potential of leveraging “micro flames” for minimizing overall hot surface area. This data was used, in conjunction with an understanding of advanced material and cooling design technologies, to analytically develop multiple design concepts. Phase I focused on in-depth engineering analysis and design, with minimal supporting laboratory testing to enable a selection of the top three combustion architectures for achieving these overall objectives. Phase II of the program developed the selected design through a combination of sub-scale testing and analytical efforts. Early tests included a cold-flow cascade to establish aerodynamic performance characteristics and a sub-scale fired test at GE Global Research in Niskayuna, NY, to establish cooling and heat transfer characteristics in conjunction with combustion performance. The data from these tests validated the analytical models to ultimately design a full-scale, test article to evaluate at prototypical pressure and temperature conditions at GE Gas Power’s Gas Turbine Technology Laboratory in Greenville, SC. GE Gas Power also developed, tested, and recommended a suitable seal design to be applied to the unique features of the combustor. To assess the technology challenges from prospective future production of the combustor from a ceramic matrix composite material, screening tests of Environmental Barrier Coatings were completed.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

In-situ optical monitoring of gas turbine blade coatings under operational extreme environments

High temperature material systems consisting of thermal barrier coatings and the underlying superalloys are key to achieving higher gas temperatures which in turn control engine efficiencies and reduce emissions. With engine temperatures in excess of the limits that metallic blades and vanes can endure, advanced monitoring techniques that ensure the integrity and durability of these coatings are paramount to continuous and safe operation. Optical methods have the benefit of being non-invasive and are able to capture data under limited access available for monitoring the hot-section of turbines. Addressing Topic 5 on Advanced Instrumentation, the research and development effort for this project titled “In situ optical monitoring of gas turbine blade coatings under operational extreme environments” was completed by University of Central Florida researchers, including Raghavan (PI) and Ghosh (co-PI). In this project, the research team leveraged intrinsic properties of coatings and rare-earth dopants as active and intelligent “sensors” through their optical properties. The outcomes of this project pave the way for diagnostics of turbine blade coatings, under operating environments, through the development of the sensing thermal barrier coating configurations, calibration and associated instrumentation while ensuring coating integrity and durability goals are concurrently met.

42 ENGINEERING↗

DOE OSTI2021

Method for fabricating superconducting devices using a focused ion beam

Nano-scale junctions, wires, and junction arrays are created by using a focused high-energy ion beam to direct-write insulating or poorly conducting barriers into thin films of materials that are sensitive to disorder, including superconductors, ferromagnetic materials and semiconductors.

Cybart, Shane A.↗

DOE OSTI2021

Impact on Cycle Efficiency of Small CHP Plants from Increasing Firing Temperature Enabled by AM of Turbine Blades

Combined Heat and Power (CHP) systems are gaining popularity because of their potential for high overall thermodynamic efficiency and increased need for distributed power generation. Most CHP systems include a gas turbine for electricity generation and a heat recovery steam generator (HRSG) for steam generation. The steam can be used to power a steam turbine for additional electricity generation or to drive rotating equipment, for space heating, for absorption chillers, etc. A CHP cycle configuration is often driven by the ‘principal’ utility for the facility that it services; steam or electricity. In either case, performance improvements in the gas turbine have the potential to increase the steam and power output from the cycle, which is a direct result of improvements in the gas turbine efficiency and power output. One possible opportunity to improve an existing gas turbine’s performance is to increase the firing temperature with improved turbine cooling and increased compression ratio.<br>In this study, the impact on CHP cycle performance from increasing the turbine firing temperature by 100 °C and improving the turbine blade cooling for a 6-MW scale gas turbine is estimated using an analytical cooled gas turbine model and a steam cycle model. A sensitivity analysis was performed to understand the impact of increasing the internal cooling effectiveness, thermal barrier coating performance and blade material upgrades on gas turbine and CHP cycle efficiency. The impacts of turbine blade cooling improvements were studied for three common CHP cycle configurations identified from the literature. Various definitions for CHP cycle efficiency from the literature are used in the comparisons. The results showed that a 100 °C increase in firing temperature can increase the gas turbine efficiency by 1 percentage point without improving cooling effectiveness and add 2 additional percentage points in efficiency by using advanced turbine blades with higher internal cooling efficiency. Studied engine upgrades showed potential for increasing the CHP cycle efficiency by 3 percentage points while increasing the steam generation rate by 8%.<br>

Uysal, Selcuk Can↗

DOE OSTI2024

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Friction-based riveting technique for AZ31 magnesium alloy

Rivet materials used in the aerospace and automotive industries are typically alloys of aluminum (Al) or steel. Magnesium (Mg) is an attractive alternative because it is 33% and 75% lighter than Al and steel, respectively. However, a primary barrier for using Mg as rivet material is its poor formability at room temperature, resulting in brittle fracture of the rivet head during cold riveting. Hot riveting is possible but suffers from high cycle time due to the need for pre-heating. A new friction-based riveting technique, Rotating Hammer Riveting (RHR), is reported to fully form AZ31 Mg rivet heads in a mere 0.23 seconds cycle time. Heat and pressure generated through severe plastic deformation during the process was sufficient to form the Mg rivet head without the need for a separate pre-heating operation. Due to dynamic recrystallization, AZ31 Mg grains in the rivet head were significantly refined from about 15 to 2.6 µm during RHR, which favors the formability of Mg rivet by triggering grain boundary sliding and reducing plastic anisotropy of Mg. In addition, RHR joints showed a metallurgical bond between the rivet head and top sheet, which eliminates a significant pathway for corrosion.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Temperature Evolution of the Activation Barriers Leads to Meyer−Neldel Rules for Structural Relaxation and Transport in Polymers

Understanding activation barriers controlling structural relaxation in glass-forming liquids, molecular transport, and ionic conductivity in amorphous polymers is a grand challenge of fundamental scientific and materials engineering interest across disciplines. Over decades, intriguing but puzzling empirical correlations between the elementary time scale of activated barrier crossing and the apparent Arrhenius activation energy, the so-called Meyer−Neldel (MN) rules, have been discovered in diverse liquids and glasses. Here, in this study, we formulate and successfully apply a new experimental analysis and an explicitly dynamical theoretical framework which provides an understanding of the origin, validity, and failure of such correlations, that bridge and unify the three fields of structural relaxation, molecular transport, and ionic conductivity in liquids and quenched glasses. Distinct quasi-universal laws are predicted in equilibrated liquids and nonequilibrium glasses, consistent with experiments. Our analysis reveals that even if the relaxation appears Arrhenius over a limited temperature range, the physical activation barrier is generally temperature-dependent in polymeric systems even below glass transition temperature. In addition, we show that the approximate validity of classical MN rules hinges on a linear temperature dependence of this barrier and the temperature range probed in experiments. Our findings are relevant for controlling the activation barrier in functional soft polymeric materials relevant to molecular separations, barrier coatings, and charge transport, and also provide new constraints on the theoretical understanding of the mechanism underlying slow activated dynamics in glass-forming condensed matter.

Meyer-Neldel rules↗

DOE OSTI2025

Stereochemical Control of Water Transport Properties in Thiol‐yne Polymers

Barrier polymers underpin almost every commercial sector, yet the needs of several emerging areas remain unmet by commercially‐available materials, including temporary orthopedic implants, transient health monitors, neural implants, and other long‐term implants. The ability to tune polymer composition independently of polymer structure positions thiol‐yne click chemistry as a promising platform to serve these emerging technologies. Here, this work describes the differences in the hierarchical structure of stoichiometrically identical materials which differ only in the proportion of the cis versus trans backbone alkene stereochemistry. Varying the isomer content in this way directs different temperature and rate dependent crystallization behavior, which affords control over micron‐scale structure. This investigation focuses on how these stereochemical features affect the water vapor permeation process by several methods and develops an understanding of how this unique structural regularity improves barrier performance relative to a commercially available water barrier polymer, poly(ethylene terephthalate).

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Fusion Blanket and Fuel Cycle Research at PNNL: FY22 Year-end Report

During the reporting period, research at PNNL focused on two tasks within the DOE Fusion Blanket and Fuel Cycle Program. Research on Task 1, Tritium Extraction from Pb-Li and He Using a Vacuum Permeator, focused on atomistic modeling to better understand tritium transport in Pd-coated V vacuum permeators. As a lower cost alternative to Pd permeators, thin coatings of Pd (or other noble metals) can be deposited over a substrate like V. However, the permeation performance of composite metal membranes degrades over time, due to the formation of intermetallics at the coating-substrate interface. Computational studies were performed to better understand tritium transport through these Pd-V intermetallics. The results of the FY22 Pd-V modeling study were recently submitted for publication in Computational Materials Science and presented at the Technology of Fusion Energy conference. Future work in this area will focus on interdiffusion barriers to prevent intermetallic formation that is deleterious to tritium transport. There are opportunities for collaboration with researchers at the Colorado School of Mines, who are manufacturing and testing candidate interdiffusion barriers. Research on Task 3, Solid Breeder Materials, included ion irradiation and post-irradiation characterization of lithium orthosilicate (Li 4 SiO 4 ) and lithium metasilicate (Li 2 SiO 3 ) to improve fundamental understanding of irradiation effects, in combination with atomistic modeling focused on the energetics of He clustering in these two ceramic phases. The results of the study suggested that the Li 4 SiO 4 phase, which is more desirable as a solid breeder due to its higher Li density, was amorphized during ion irradiation while the Li 2 SiO 3 phase appeared to be more resistant to irradiation damage. It is possible that Li loss contributed to the poor irradiation performance of the Li 4 SiO 4 , and some thoughts are provided regarding coatings that could be applied to solid breeders like this to prevent Li loss at elevated temperature while not hindering tritium diffusion. The results of the FY22 ion irradiation study were recently submitted for publication in Journal of Nuclear Materials and presented at the 22nd International Conference on Ion Beam Modification of Materials. Future work in this area will focus on Li-rich ceramics such as Li 5 AlO 4 and Li 8 ZrO 6 that have high Li density and should provide rapid tritium release based on previous work with less Li-rich ceramics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗