Uranium mononitride (UN) is one of the ceramic nuclear fuels considered for light water reactor and advanced reactor designs, but knowledge gaps remain before it can be licensed. For instance, accurate prediction of fission gas swelling is essential for safety analysis, and fuel performance in UN is further complicated by an accelerated swelling rate at high temperatures and high burnups observed experimentally, sometimes referred to as breakaway swelling. In this work, we leverage an existing mechanistic model in the BISON fuel performance code for UN swelling and the atomic-scale-informed cluster dynamics diffusivity model it was built upon. However, since this workflow is computationally expensive, we train a neural network surrogate model to replace the full modeling chain. We then use a Bayesian calibration strategy, leveraging experimental measurements from separate effects testing and post-irradiation examinations, to compute the posterior distributions of various meaningful parameters, including DFT energetics and microstructure properties, such as the dislocation line density. Finally, the forward propagation of these distributions through the model leads to a mechanistic, data-informed, and uncertainty-aware prediction of fission gas swelling in UN fuel. The uncertainty in swelling ultimately underpins the probability of fuel-cladding contact as a function of operating conditions and burnup.

We present an automated MATLAB-based GUI for the analysis of microfluorimetry data inisolated neuronal cultures. The pipeline integrates signal extraction, quality control,responder classification, and stimulus-evoked quantification into a single workflowcompatible with both single-wavelength and ratiometric dyes. Applied to thermal and drugstimulations, the automated analysis reproduces the classification and quantitative outputsobtained using manual approaches, while substantially reducing analysis time. The GUI wedeveloped provides a practical and reproducible solution for higher throughput [Ca²⁺]ᵢimaging analysis across neuroscience, cell biology, and related fields.

We perform multilevel Bayesian calibration of a model for fission gas diffusivity in UO_2 nuclear fuel. Specifically, we use a two-level delayed acceptance method that couples a machine learning surrogate for Xe and U diffusivities with a high-fidelity cluster dynamics model, to improve upon surrogate-assisted, single-level Bayesian calibration that does not account for residual error in the fitted surrogate. We integrate multilevel delayed acceptance with parallel prefetching techniques to improve the computational throughput of the calibration process. Our results indicate an average speed-up of more than 48 × in terms of the computation time per effective sample.

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuels considered for light water reactor and advanced reactor designs, as it presents significant advantages such as high uranium density (better economics) and high thermal conductivity and melting point (increased safety). Self- and fission gas diffusivities need to be better understood, given that they influence key fuel performance phenomena like swelling and fission gas release. Recently, radiation enhanced diffusivity was investigated in UN by means of cluster dynamics simulations relying on empirical potential-based parameterizations, the reliability of which highly depends on the interatomic potential accuracy. In this work, we refine this approach by determining, using ab-initio calculations, the properties of defect clusters containing vacancies, self-interstitials and Xe impurities. We also consider larger clusters than previous studies. The obtained dataset (formation enthalpies, entropies, and migration barriers) is used to parameterize a cluster dynamics model of mobile clusters, and to calculate the defect cluster concentrations under irradiation. This gives us access to the radiation enhanced self- and fission gas diffusivities. Although the resulting diffusivities are close to the values reported in the literature, we find important qualitative differences in the diffusion mechanisms. Capturing the correct mechanisms is crucial to properly describe the chemistry and fission rate dependence of the model.

Computational design for fission reactor materials is ready to accelerate the development and qualification of nuclear materials. This review is primarily aimed at computational materials scientists that seek to apply ICME to the development of fission reactor materials. We summarize reactor materials and technology, discuss reactor material development and qualification today, show how ICME is being applied to the unique requirements of reactor materials, and provide a future vision.

OBJECTIVE:Osteoarthritis (OA) is a degenerative joint disease characterized by chronic pain. We investigated whether the ion channel transient receptor potential melastatin 3 (TRPM3), expressed in sensory neurons, mediates OA pain. DESIGN:We used genetically modified mice, pharmacological tools, and behavioural assessments to evaluate the role of TRPM3 in OA pain induced by monosodium iodoacetate (MIA) or partial medial meniscectomy (PMM). Mice with global Trpm3 knockout (Trpm3-/-) and conditional deletion in sensory neurons (Advillin-Cre/Trpm3fl/fl) were compared with control mice. Selective TRPM3 antagonists (ononetin and isosakuranetin) were tested for their ability to reverse established pain. Histological analyses were performed to assess cartilage damage. RESULTS:Global deletion of Trpm3 prevented the development of pain behaviours in both MIA (mean difference [MD] = -7.8, 95% CI: -13.6 to -2.1) and PMM (MD = -13.6, 95% CI: -22.3 to -4.9) models without inhibiting structural cartilage damage. Sensory neuron-specific Trpm3 deletion replicated this effect in PMM mice (MD = -9.0, 95% CI: -15.0 to -3.1), demonstrating a neuronal contribution. Furthermore, pharmacological inhibition of TRPM3 with ononetin (MIA: MD = -2.8, 95% CI: -4.4 to -1.4; PMM: MD = -1.5, 95% CI: -2.2 to -0.7) or isosakuranetin (MIA: MD = -3.0, 95% CI: -4.4 to -1.6; PMM: MD = -1.5, 95% CI: -2.2 to -0.8) reversed established mechanical hypersensitivity in OA mice. CONCLUSIONS:TRPM3 expressed in sensory neurons is a critical mediator of OA pain in mice. Selective TRPM3 antagonism effectively alleviates established pain, supporting this channel as a potential therapeutic target for chronic pain associated with OA.

In this study, the evolution of UN under ion irradiation is examined through in-situ transmission electron microscopy (TEM). The investigation focuses on irradiating UN with 1 MeV Kr2+ ions at elevated temperatures (700-1100 C-degrees), with a detailed analysis of the resulting microstructural evolution. The critical dose, at which loops reach saturation, remains constant across all temperatures tested (<1 dpa). Overall trends in dislocation evolution show that loop growth has no significant variation based on temperature changes with loop density values being higher at lower temperatures. Cluster dynamics simulations were performed using material properties derived from atomic scale simulations and were able to trace temperature dependencies in growth rates to underlying defect behaviors. These findings offer valuable experimental data to validate advanced fuel performance models.

The endogenous peroxisome proliferator-activated receptors (PPARγ) agonist 15-deoxy-Δ12,14-PGJ2 (15d-PGJ2) stimulates sensory neurons by activating transient receptor potential A1 (TRPA1). Synthetic thiazolidinedione PPARγ agonists have been used as antidiabetic agents but have also been explored as experimental analgesics. Here, we have used intracellular Ca2+-measurements and voltage-clamp recordings to examine the effects of several PPARγ ligands on TRPA1 in sensory neurons and cell lines and examined nociception produced by local intraplantar administration of troglitazone. Troglitazone, rosiglitazone, nTZDpa, and the PPARγ antagonist GW9662 evoked concentration-dependent Ca2+-influx responses in TRPA1 expressing, but not untransfected Chinese hamster ovary (CHO)cells. Furthermore, troglitazone, nTZDpa, and GW9662 evoked [Ca2+]i-responses in mouse DRG neurons expressing TRPA1. Responses were abolished by the TRPA1 antagonist A967079 and were absent in DRG neurons from Trpa1-/- mice. The TRPA1 agonist activity of troglitazone, nTZDpa and GW9662 were unaffected by incubation with an excess of cysteine-methyl ester, indicating that these ligands do not act by covalent modification of cysteine residues, but rather through a non-covalent interaction with TRPA1. The cysteine reducing agent DTT did not reverse the effects of Troglitazone, nTZDpa and GW9662, which suggests that the observed agonist effects were independent of cysteine oxidation. Intraplantar injections of troglitazone evoked pain-responses in wild-type mice, but not in Trpa1-/- mice. Our molecular docking studies indicate that nTZDpa and troglitazone bind to overlapping sites in a hydrophobic pocket in the pre-S1 helix These observations demonstrate that multiple PPARγ ligands stimulate TRPA1 and that nTZDpa may be a useful tool for investigations of TRPA1.

Despite more than 70 years of research on the thermodynamic properties of molten salts, there are still limited experimental data towards understanding the phase stability relations of molten mixtures containing PuCl3. While recent thermodynamic measurements of PuCl3-NaCl yielded some data, there have been significant differences in the reported values of heat capacity of PuCl3-NaCl in the liquid, or molten state. In this work, we conducted transpose temperature drop calorimetry of the PuCl3-NaCl eutectic using a commercial Tian-Calvet twin microcalorimeter and the Ni encapsulation technique developed by us previously. The transpose temperature drop enthalpy (ΔHttd) was measured to be 155.31 ± 8.03 kJ∙mol−1 at a temperature of 975.77 ± 0.08 K. To verify this value, a critical assessment of the literature was performed to determine that the enthalpy increment, ΔHT-298.15, of molten PuCl3-NaCl eutectic is 101.5 ± 8.1 kJ∙mol−1, which agrees well with the heat capacity (Cp) derived by Karlsson et al. [26] using differential scanning calorimetry. The original Cp equation of Karlsson et al. was then extended with confidence to 993 K (Cp = 101.9 ± 2.1 J∙mol−1∙K−1). In addition, the excess heat capacity (Cpex) of molten PuCl3-NaCl eutectic was determined to be 4.2 ± 2.1 J∙mol−1∙K−1, which was then used to determine the ΔHmix to be –5.3 kJ∙mol−1. These results provide the basis for modeling the thermodynamic stability of molten PuCl3-bearing chlorides for nuclear energy and other applications.

Uranium mononitride (UN) is a nuclear fuel candidate for advanced reactor designs and an alternative being considered for light water reactors due to its higher thermal conductivity and uranium density than UO2. As with any nuclear fuel, swelling and fission gas release are important factors for safety, while also being some of the hardest phenomena to predict with a high degree of confidence. Getting a grasp on the gas swelling behavior and release is crucial to lower the barrier for UN utilization. An accelerated swelling rate at high temperatures observed experimentally, sometimes referred to as “breakaway swelling,” further complicates the prediction of fuel performance of UN. A mechanistic model has been developed using a multiscale approach to describe the intragranular and intergranular fission gas behavior. Lower-length-scale calculations have been employed to inform models of the gas and self-diffusion behavior, resolution rate, and bubble shape. Leveraging previous work on high burnup UO2, two populations of intragranular bubbles are considered; small bulk bubbles and larger bubbles located along dislocations. The dislocation bubbles were found to be crucial to the overall swelling behavior, and the breakaway swelling transition was associated with the transition in the gas atom diffusion mechanism from an irradiation-induced athermal diffusion regime at lower temperatures to an intrinsic thermal equilibrium regime at higher temperatures, accelerating the growth of the dislocation bubbles. Similarly, the threshold for fission gas release was associated with the grain boundary vacancy diffusivity surpassing the gas atom diffusivity at sufficiently high temperatures, allowing the over-pressurized grain boundary bubble to grow in size and interconnect. Using thermo-mechanical models with the fission gas model, two integral fuel pin assessment cases were simulated. This work demonstrates the ability of a multiscale approach to accelerate the understanding of advanced fuel forms when experimental data is limited.

The mechanism by which chromium is accommodated in UO2 and its role in accelerating grain growth remain subjects of debate. This work presents an atomistic analysis of chromium incorporation in both bulk UO2 and grain boundaries, explicitly accounting for space-charge effects. A Sigma 9 symmetric tilt and an asymmetric boundary are modeled within a thermochemical framework to evaluate defect behavior. We predict hyperstoichiometric, negatively charged grain boundary cores, compensated by hole polarons in adjacent space-charge layers. Chromium is accommodated as Cr2+ in the bulk and segregates to grain boundaries in multiple states, with interstitial Cr1+ dominating under sintering conditions. This enhances grain boundary uranium vacancy concentrations, promoting densification and grain growth. The effect is predicted to occur within an oxygen potential window consistent with experimental observations of enhanced grain growth. Chromium also increases polaron concentrations at grain boundaries and raises the electron potential barrier across the boundary, reducing conductivity. The findings help clarify how dopants are accommodated in metal oxides and the consequent impacts on their chemical, electrical, and mechanical behavior.

Creep is an important deformation mode for nuclear fuel performance as it influences the pellet-cladding gap, which in turn affects the fuel temperature. It also impacts the cladding stress due to cladding-pellet mechanical interactions. Having a creep model that captures the correct mechanisms is essential for the accurate physical fidelity of nuclear fuel performance codes. We present a diffusional creep model for UO2 that has been informed using lower-length scale simulations. The simulations focus on the uranium vacancy concentration, diffusivity, and elastic dipole tensor, all of which underpin steady-state and transient diffusional creep in UO2. The results were compared against available experimental creep values and used to provide insight as to the likely role of uranium self-diffusion due to vacancies at grain boundaries. In this study, we also determine the dominant diffusional creep mechanism for UO2, and conclude that it is the Coble mechanism. Furthermore, the development of a creep model in general is an important first step towards modeling the complicated irradiation case, and is needed to support extension of the model to microstructures that have limited data, such as UO2 with enlarged grains due to dopants.

Fission gas bubbles in UO2 nuclear fuel have been observed to exhibit pressures in excess of the equilibrium bubble pressure; however, the cause of bubble over-pressurization has not yet been demonstrated. The mechanical interaction between a bubble and the surrounding matrix or grain boundary depends on the internal pressure of the bubble and local stress state, such that over-pressurized bubbles are thought to be responsible for fragmentation and pulverization, when exposed to a temperature ramp. Here, we investigate the role of U interstitials, produced through irradiation, in over-pressurizing bubbles by using a combined molecular dynamics (MD) and cluster dynamics approach. Firstly, the energies for the capture of interstitials and vacancies by bubbles have been determined from MD as a function of the ratio of gas atoms to vacancies that make up the bubble. Secondly, these reaction energies have been implemented in the cluster dynamics code Centipede to predict bubble over-pressurization as a function of temperature for typical fission rates. It was found that there is a transition from low pressure bubbles (at high temperatures) to high pressure bubbles (at lower temperatures). The cause of this behavior was shown to be the creation of irradiation-induced interstitials that are highly mobile relative to vacancies at low temperature; whereas, vacancies are sufficiently mobile at high temperatures to limit bubble pressures. This result supports the hypothesis that over-pressurized bubbles form during steady-state operation and that this behavior is highly sensitive to the local pellet temperature.

Chromium-doped UO2 has been investigated as an Accident Tolerant Fuel (ATF) concept to enhance the performance and safety of Light Water Reactors (LWR). This study explores the impact of varying Cr doping levels on its segregation to and precipitation at grain boundaries of UO2 through characterization analysis using transmission electron microscopy (TEM) and energy dispersive x-ray spectroscopy (EDS). A broad range of Cr doping levels is examined, from low solubility concentrations (750 ppm) to near-maximum solubility levels (2500 ppm) and extending beyond reported solubility limits (7800 ppm). The study compares these doping levels with undoped UO2, evaluating their effects on the atomic concentration of Cr at grain boundaries and grain boundary thickness, all of which are influenced by Cr segregation. Changes in oxidation state were determined via X-ray Absorption Near Edge Structure (XANES). Molecular dynamics simulations are compared to experimental results, discussing concentration evolution, grain boundary type, and segregation energies.

TRISO fuels are candidates for use in next generation reactors including gas reactors, fluoride salt-cooled high temperature reactors, and micro-reactors. The fuel kernels of TRISO particles can be in either UO2 or UCO form. Ag is an important fission product for the performance of TRISO fuels, since it can transport through TRISO coating layers and result in relatively high release from the fuel. In this study, the Ag diffusivity in the TRISO fuel kernels, in both UO2 and UCO forms, is modeled. The study relies on DFT and empirical potential calculations to determine Ag defect properties, which are then used in cluster dynamics simulations to estimate the impact of irradiation on defect transport. A new empirical potential is developed to describe Ag-UO2 interactions. CALPHAD calculations are used to determine the thermo-chemistry in the TRISO fuel kernels, which is an input to the cluster dynamics simulations. The results are compared to available experimental data. We found a much reduced Ag diffusivity under irradiation, as compared to that under thermal equilibrium conditions, and the reason leading to the result was discussed.

Molten salts play a crucial role in Generation IV nuclear energy technology, with chloride salts like NaCl-UCl3 garnering significant attention due to their distinctive properties and potential applications in fast-spectrum molten salt reactors (MSRs). The corrosive nature of molten salts can cause the dissolution of structural materials, leading to the formation of new species in molten chlorides. In addition, the radioactive decay of nuclear fuels results in the accumulation of fission products in the salts. Understanding the behavior of these corrosion and fission products and their impacts on the properties of molten salts is critical for the design of MSRs. This paper presents a systematic study on the properties of eutectic NaCl-UCl3 molten salt in the presence of corrosion products (CrCl2 and CrCl3) and fission products (CsCl and SrCl2) utilizing ab initio molecular dynamics (AIMD) simulations. We focus on essential structural and thermophysical properties such as density, mixing energy, coordination numbers (CN), and Radial Distribution Functions (RDF) with varying compositions of these corrosion and fission products from 0 % to 15.8 %. It is found that the mixing behavior of these corrosion and fission products is strongly driven by their coordination chemistry in eutectic NaCl-UCl3. Both CrCl2 and SrCl2 have identical coordination to eutectic NaCl-UCl3, thus exhibit negative mixing energies at a lower concentration. In contrast, CsCl exhibits significant different coordination compared to NaCl-UCl3, resulting to positive mixing energies. Our results offer valuable insights into the coordination chemistry and mixing behavior of corrosion and fission products in chloride molten salts and provide essential data that can be used as input to property databases to supplement experimental data.

This study investigates the impact of Mg and Ni doping on tritium diffusion in LiAlO2 and LiAl5O8 ceramics, that are used in tritium-producing burnable absorber rods (TPBARs). Utilizing Centipede simulations across a broad temperature range (500 K to 1250 K), we explore the interplay between defect dynamics, cluster formation, and tritium mobility. In LiAlO2, Mg doping significantly enhances tritium diffusivity by increasing tritium interstitial concentrations and diffusion coefficients of key species, thereby doubling the overall tritium diffusivity. Ni doping, while shifting the dominant defect to Li vacancies, maintains high tritium mobility due to the low binding energy of Li vacancy-tritium complexes, which ensures effective tritium migration. In LiAl5O8, Mg and Ni doping results in a slight reduction in the diffusion coefficients of key species, yet the dramatic increase in tritium interstitial concentrations compensates, leading to a net small increase in tritium diffusivity. The findings highlight the critical role of defects in tritium transport and the effect of Mg and Ni defects on the performance of these ceramics in demanding nuclear environments.

Traditional nuclear fuel qualification is a lengthy process challenged by erratic or incomplete irradiation experimental data, leading to many unqualified fuels. In response, this paper presents an accelerated fuel qualification (AFQ) framework that integrates multiscale modeling, machine learning, and legacy data assimilation to inform specific integral testing. The framework leverages atomistic simulations to elucidate fundamental mechanisms, such as xenon diffusion and defect kinetics, which inform mechanistic models of fuel behavior. These mechanistic models are then validated against legacy experimental data, while machine learning is used to refine critical parameters, such as Xe diffusivity, and to further reduce computational uncertainties.As a demonstration, the framework is applied to characterize uranium mononitride (UN) fuel, resulting in the quantification of swelling, which is a dominant failure mechanism, uncertainty quantification of the swelling process in UN, and the development of performance envelopes as a function of temperature, linear heat generation rate, and burnup. The AFQ methodology outlined here offers a robust proof-of-concept template for qualifying advanced nuclear fuels, supporting regulatory modernization efforts for next-generation reactor technologies.

The impact of defect generation during irradiation on grain boundary (GB) properties and associated transport phenomena lacks fundamental understanding, despite the influence GBs are known to exert over properties such as swelling, sintering, and creep. In this study, a cluster dynamics model is developed that predicts steadystate concentrations of defects at UO2 GBs by tracking the rate of point defect production and depletion, under irradiation conditions. Fast U interstitial self-diffusivity in bulk UO2 under irradiation results in their flux to GBs exceeding that of slower U vacancies. Incorporation of these interstitials at fission gas bubbles located at the GB results in their over-pressurization and cessation as effective sinks. As a consequence, U interstitials are predicted to be significantly enhanced in concentration under irradiation at UO2 GBs, and their fast mobility relative to defects in the bulk results in GB U self-diffusion orders of magnitude greater than that in the bulk. Creep controlled by diffusion of defects at GBs-Coble creep-is calculated using the predicted enhanced U self-diffusivity. The modeled creep rates compare favorably with experimental irradiation creep measurements, exhibiting the correct athermal behavior when GB defects are within a sink-limited regime. UO2 was studied here-the standard nuclear fuel-however, we expect the physical processes governing our results to extend beyond UO2.