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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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106 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of microstructure and neutron irradiation defects on deuterium retention in SiC

Retention of hydrogen isotopes is a critical concern for operating fusion reactors as retained tritium both activates components and removes scarce fuel from the fuel cycle. Radiation-induced displacement damage in SiC influences the retention of hydrogen isotopes compared to pristine SiC. Deuterium retention in neutron irradiated high purity SiC has been compared to different microstructures of non-irradiated high purity SiC using thermal desorption spectroscopy after gas charging and low energy ion implantation. Experimental results show lower deuterium retention in single crystal SiC than in polycrystal SiC indicating that grain boundaries are key trapping features in unirradiated SiC. Deuterium is released at lower temperatures in neutron irradiated polycrystal SiC compared to pristine polycrystal SiC, suggesting weaker trapping by radiation-induced defects compared to grain boundary trapping sites in the pristine materials. Low energy ion implantation caused a high deuterium release temperature, highlighting the sensitivity of deuterium release behaviour to radiation defect characteristics. First principles calculations have been conducted to identify energetically favourable trapping sites in SiC at the H ABc V Si and H TSi V C complexes, and migration barriers between interstitial sites. This helps interpret experimental results and derive effective diffusivity of hydrogen isotopes in SiC in the presence of vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nanoconfined Grain Boundaries Increase the Conductivity of Polycrystalline Molecular Crystals

Soft-solid molecular crystals consist of crystalline grains and fluid grain boundaries (GBs) that enhance the grain binding and transport of Li + ions between the grains. The total ionic conductivity consists of ion migration in both the grains and GBs. To unravel these contributions in adiponitrile (Adpn):LiPF 6 molecular crystals, the GB volume fraction was varied by changing the size of the crystals and the Adpn:LiPF 6 molar ratio. Molecular dynamics (MD) simulations indicate that ion motion was subdiffusive in the grains and “well-diffusive” in the GBs, with GBs characterized as disordered nanoconfined regions of higher charge carrier concentration (∼1 M) than in saturated Adpn:LiPF 6 solutions (0.04 M), and Li + ions predominantly solvated by cyano groups with few contact ion pairs. The diffusivity in the GBs is at least an order of magnitude higher than that in the crystalline grains. The emergent picture is the grains as a reservoir of ions that migrate to faster-conducting GBs.

Crystals↗
DOE OSTI2025

Crystallization Mechanisms of Poly(vinylidene Fluoride- co -chlorotrifluoroethylene): Nucleation Transitions, Growth Kinetics, and Microstructure Evolution

The crystallization kinetics of FK-800, a commercial semicrystalline copolymer of chlorotrifluoroethylene and vinylidene fluoride (poly(CTFE-co-VDF)), dictate its microstructure and functional performance. Crystallization occurs between the glass transition (T g ≈ 31 °C) and melting point (T m ≈ 110 °C), with grain boundaries playing a key role in applications such as memristors, where they regulate filament growth. This study integrates in situ atomic force microscopy (AFM), grazing-incidence wide-angle X-ray scattering (GIWAXS), and differential scanning calorimetry (DSC) to characterize nucleation, growth, and morphology across the full crystallization window. Hot-stage AFM reveals a transition from homogeneous to heterogeneous nucleation near 45 °C and a shift from reaction-limited to diffusion-limited growth above 60 °C. Kinetics are analyzed using Lauritzen–Hoffman, Turnbull–Fisher, and Avrami models to extract surface free energies and activation barriers. A multiscale modeling framework is developed in which nucleation densities and growth rates measured by AFM are used to reconstruct Avrami kinetics, which are then validated against coverage data, and extrapolated to predict bulk crystallization behavior observed by DSC. GIWAXS confirms a primarily flat-on chain orientation at all temperatures, linking orientation to domain morphology. This integrative approach quantitatively connects nanoscale crystallization dynamics with macroscopic phase evolution, establishing a quantitative framework for modeling crystallization across time, temperature, and length scales.

Crystallization↗
DOE OSTI2025

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗
DOE OSTI2024

Microstructural and material property changes in severely deformed Eurofer-97

Severe plastic deformation changes the microstructure and properties of steels, which may be favourable for their use in structural components of nuclear reactors. In this study, high-pressure torsion (HPT) was used to refine the grain structure of Eurofer-97, a ferritic/martensitic steel. Electron microscopy and X-ray diffraction were used to characterise the microstructural changes. Following HPT at room temperature to a maximum shear strain of 230, the average grain size reduced by a factor of ~30, with a marked increase in high-angle grain boundaries. Dislocation density also increased by more than one order of magnitude. The thermal stability of the deformed material was investigated via in-situ annealing during synchrotron X-ray diffraction. This revealed substantial recovery between 450 K – 800 K. Irradiation with 20 MeV Fe-ions to ~0.1 dpa caused a 20% reduction in dislocation density compared to the as-deformed material. However, HPT deformation prior to irradiation only had a minor effect in mitigating the irradiation-induced reductions in thermal diffusivity and surface acoustic wave velocity of the material. Microstructural and material property changes are dominated by deformation compared to irradiation. In light of this, the benefits of using HPT to improve the irradiation resistance of Eurofer-97 are limited. These results provide a multi-faceted view of the changes in ferritic/martensitic steels due to severe plastic deformation, and how these changes can be used to alter material properties.

ion-irradiation↗
DOE OSTI2024

Response of 11 B enriched ZrB 2 ultra-high temperature ceramic to neutron irradiation at elevated temperatures

ZrB 2 , an ultra-high temperature ceramic (UHTC) is being considered for use in fusion reactor first-wall structures, yet its response to irradiation remains poorly understood. This study employed scanning/transmission electron microscopy (S/TEM), synchrotron X-ray diffraction (XRD), finite element calculations, and thermal property measurements to thoroughly investigate the neutron-irradiation effects on 11 B-enriched ZrB 2 . Neutron irradiations were conducted at 220 °C and 620 °C, with a neutron fluence of 2.2 × 10 25 neutron/m 2 (energy > 0.1 MeV), resulting in 3.9 dpa and 4200 appm He. The study revealed the unusual prevalence of prism loops and a > c anisotropic lattice swelling, likely linked to the low c/a ratio of ZrB 2 , leading to grain boundary microcracking. Reducing the grain sizes was effective in reducing intergranular cracking and macroscopic swelling. The observation of cavities in ZrB 2 irradiated at 620 °C, as opposed to 220 °C, prompts questions about the temperature at which vacancies in ZrB 2 become mobile, and the role of neutron absorption by 10 B in elevating irradiation temperatures. Isotopic enrichment in 11 B proves to be a viable strategy for mitigating helium production in transition-metal diborides, which is a critical consideration for nuclear applications. Irradiation-induced defects reduce the thermal diffusivity and conductivity of ZrB 2 by a factor of 4–9, which has important implications for its role as a plasma-facing material in fusion reactors that drive high heat fluxes through first-wall materials. Here, this comprehensive study lays the foundation for understanding ZrB 2 behavior under neutron irradiation and highlights important phenomena to consider for various material applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Diffuse-Interface Model for Predicting the Evolution of Metallic Negative Electrodes and Interfacial Voids in Solid-State Batteries with Homogeneous and Polycrystalline Solid Electrolyte Separators

Here, this paper presents a novel diffuse-interface electrochemical model that simultaneously simulates the evolution of the metallic negative electrode and interfacial voids during the stripping and plating processes in solid-state batteries. The utility and validity of this model are demonstrated for the first time on a cell with a sodium (Na) negative electrode and a Na-β″-alumina ceramic solid electrolyte (SE) separator. Three examples are simulated. First, stripping and plating with a perfect electrode/electrolyte interface; second, stripping and plating with a single interfacial void at the electrode/electrolyte interface; third, stripping with multiple interfacial voids. Both homogeneous and polycrystalline SEs with low and high-conductivity grain boundaries (GBs) are considered for all three examples. Heterogeneous GB conductivity marginally impacts the thickness of the Na electrode in cases with a perfect electrode/electrolyte interface. Moreover, it results in local changes to void growth due to the interactions between the void edge and the GBs. The void growth rate is a linear function of the flux of Na atoms at the void edge, which in turn depends on the applied current density. We also show that the void coalescence rate increases with applied current density and can be marginally influenced by GB conductivity.

batteries↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Understanding Fundamental Mechanisms Behind Anomalous Segregation Behavior at Grain Boundaries during Diffusional Creep

Recent experimental studies in a nickel (Ni)-rhenium (Re) alloy demonstrated anisotropic elemental segregation around grain boundaries (GBs) while under tensile strain. Some GBs showed Re enrichment, while others showed Re depletion. We hypothesize that differing vacancy fluxes to GBs, caused by the anisotropic elastic stresses generated within the polycrystal, results in anisotropic creep-induced segregation (CIS) and grain growth. Using molecular dynamics simulations, we developed a mechanistic understanding of CIS and determined the contribution of elastic stresses and grain growth in Ni-Re alloys. We find that the stress state of the GB significantly changes the segregation energy profile for Re atoms, leading to significant Re redistribution. Further, as the GB migrates, the segregation/desegregation tendency of Re leads to bands of Re enrichment/depletion. Our results have important consequences for the quantitative predictions of diffusion creep and for the design of high-temperature creep-resistant Ni alloys.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Extreme Temperature Cryptography Based On Nitrogen-Incorporated Ultrananocrystalline Diamond

Physical entropy sources that remain stable under extreme temperatures are essential for cryptography in emerging technological frontiers in deep space exploration, geothermal energy harvesting, and nuclear energy. However, conventional semiconductor platforms fail to generate stable and reliable cryptographic keys above 200 degrees C due to performance degradation. Here, we report a diamond-based cryptographic primitive that exploits the defect-rich sp 2 -bonded grain boundary network in nitrogen-incorporated ultrananocrystalline diamond (n-UNCD) film as a robust entropy source to generate cryptographic keys that remain operationally stable even after enduring extreme temperatures of 700 degrees C for 54 h while also surviving thermal cycling between room temperature and 700 degrees C for 48 h. The strength of the generated keys is assessed through several cryptographic metrics such as bit uniformity, entropy, hamming distances, and correlation coefficients, all of which are found to be near their respective ideal values. Moreover, the generated keys pass the NIST SP 800 and SP 800-90B tests and are also resilient to supply bias variations and a regression-based machine learning attack model based on the Fourier series. The robustness of the keys is attributed to the better thermal stability and chemical inertness of the n-UNCD film. This is supported by high-resolution energy-dispersive X-ray spectroscopy (EDS), which shows no significant lateral diffusion of metal atoms into the n-UNCD layer, and by Raman spectroscopy, which reveals no significant changes in the bonding configuration of the n-UNCD structure. Our findings highlight the remarkable potential of n-UNCD film for extreme environment cryptography by expanding the operational limits of conventional hardware security platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nanoscopic strain evolution in single-crystal battery positive electrodes

Single-crystal Ni-rich layered oxides (SC-NMC) with a grain-boundary-free configuration have effectively addressed the long-standing cracking issue of conventional polycrystalline Ni-rich materials (PC-NMC) in lithium-ion batteries, prompting a shift in optimization strategies. However, continued reliance on anisotropic lattice volume change—a well-established failure indicator in PC-NMC—as a metric for understanding strain and guiding compositional design for SC-NMC becomes controversial. Here, in this study, by leveraging multiscale diagnostic techniques, we unravelled the distinct nanoscopic strain evolution in SC-NMC during battery operation, challenging the conventional composition-driven strategies and mechanical degradation indicators used for PC-NMC. Through particle-level chemomechanical analysis, we reveal a decoupling between mechanical stability and lattice volume change in SC-NMC, identifying that structural instability in SC materials is primarily driven by multidimensional lattice distortions induced by kinetics-driven reaction heterogeneity and progressively deactivating chemical phases. Using this mechanical failure mode, we redefine the roles of cobalt and manganese in maintaining mechanical stability. Unlike cobalt’s detrimental role in PC-NMC, we find cobalt to be critical in enhancing the longevity of SC-NMC by mitigating localized strain along the extended diffusion pathway, whereas manganese exacerbates mechanical degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effects of temperature and dose rate on ion-irradiated γ-LiAlO 2 pellets

Defect accumulation and microstructural evolution during ion irradiation at elevated temperatures are governed by competing processes of defect production, driven by the dose rate, and defect recovery, controlled by diffusion, interaction, and annihilation. Here, this study investigates the effects of irradiation temperature and the dose rate on microstructural evolution, deuterium retention, and lithium volatilization in γ-LiAlO 2 pellets subjected to sequential He + and D + ion irradiation. Experiments were performed to a total fluence of 3 × 10 17 (He + + D + )/cm 2 at 623, 673, 723, and 773 K with an average He + dose rate of 7.7 × 10 −4 dpa/s, and to 2 × 10 17 (He + + D + )/cm 2 at 773 K with dose rates of 6.8 × 10 −5 , 2.9 × 10 −4 , and 7.3 × 10 −4 dpa/s. At 623 K, the microstructure was dominated by cavities and fractures with no observable precipitate formation, while small precipitates emerged at 673 K. Increasing the irradiation temperature to 723–773 K promoted the formation of larger, faceted LiAl 5 O 8 precipitates, and surface amorphization, accompanied by pronounced lithium depletion and H–D isotopic exchange. At 773 K, medium and high dose rates produced an amorphized surface layer over a crystalline subsurface containing LiAl 5 O 8 precipitates and blisters at the crystalline–amorphous interface, whereas low-dose-rate irradiation preserved surface crystallinity with cavities distributed in the matrix, around precipitates, and along grain boundaries. Precipitate morphology was anisotropic with limited size dependence on the dose rate. These results elucidate the coupled effects of temperature and the dose rate and demonstrate that sequential He + and D 2 + irradiation at 773 K reproduces key microstructural features and H isotope behavior observed in neutron-irradiated γ-LiAlO 2 at 573 K.

dose rate effects↗
DOE OSTI2025

Effects of dose rate on the microstructure and deuterium retention in γ-LiAlO 2 pellets

This report presents experimental findings obtained from November 2024 to September 2025. Defect accumulation and microstructural evolution during ion irradiation at elevated temperatures are governed by two competing processes: defect production, driven by dose rate, and defect recovery, controlled by defect diffusion, interaction, and annihilation. At a given dose, the resulting microstructural evolution depends on both the dose rate and irradiation temperature. As a continuation of our FY24 tritium science project, which investigated temperature effects at a fixed dose rate, this study focuses on dose-rate effects at a fixed temperature to provide deeper insights into the irradiated microstructure and compositional changes in γ-LiAlO 2 pellets. The study aims to elucidate the impact of dose rate on microstructure, precipitate morphology, deuterium retention, and lithium volatility in γ-LiAlO 2 pellets under sequential 120 keV He + and 80 keV D 2 + ion irradiation. Three dose rates of 7.3×10 4 , 2.9×10 4 and 6.8×10 5 dpa/s were applied to achieve the same total ion fluence of 2×10 17 (He + +D + )/cm 2 at 500 °C, corresponding to a maximum combined dose of 7.55 dpa at ~255 nm. The irradiated pellets were subsequently characterized using scanning transmission electron microscopy (STEM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). The microstructural response of γ-LiAlO 2 to ion irradiation was found to be strongly dose-rate dependent. At medium and high dose rates, irradiation produced a surface amorphized layer and an underlying crystalline layer containing LiAl 5 O 8 precipitates, with implanted gases accumulating and forming blisters at the crystalline-amorphous interface. It remains to be investigated whether the amorphized layer was produced by He + ion irradiation prior to D 2 + ion irradiation. In contrast, at low dose rates, the material remained crystalline, with cavities, likely gas-filled, distributed around precipitates, within the γ-LiAlO 2 matrix, and along grain boundaries. While precipitate morphology exhibited anisotropy, their size showed little sensitivity to dose rate in the applied range of this study. This result, however, does not rule out the possibility that further reductions in dose rate could influence precipitate size. High dose-rate irradiation enhanced protonium–deuterium isotopic exchange and lithium depletion in the amorphized region. Collectively, the results show that dose rate governs amorphization, gas redistribution, isotopic exchange, and lithium depletion, providing important insights into the mechanisms underlying structural evolution in γ-LiAlO 2 pellets under reactor-relevant irradiation conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗