New reactor concepts have motivated study of a variety of nuclear fuel types. Most nuclear fuels have their origins dating back to the very beginnings of nuclear materials. We survey the most prevalent types of nuclear fuels and their properties and give some historical context as to their development. We end with our perspective on what the next 50 years of nuclear fuel research might lead to. In our opinion, while optimized microstructures and chemistries are certainly on the horizon, the biggest developments will be the continued integration of modeling and simulation with experiments to extract the greatest amount of energy possible from existing fuel candidates in a safe and economical way. Graphical abstract

The compositional and structural variety inherent to oxide perovskites spawn wide-ranging applications. In perovskites, the band gap E g , a key material parameter for these applications, can be optimally controlled by varying the composition. Here, we implement a hierarchical screening process in which two cross-validated and predictive machine learning models for band gap classification and regression, trained using exhaustive datasets that span 68 elements of the periodic table, are applied sequentially. The classification model separates wide band gap materials, with E g ≥ 0.5 eV, from materials which have zero or relatively small band gaps, namely E g < 0.5 eV, and the second regression model quantitatively predicts the gap value of the wide band gap compounds. The study down-selects 13,589 cubic oxide perovskite compositions that are predicted to be experimentally formable, thermodynamically stable, and have a wide band gap. Of these, a subset of 310 compounds, which are predicted to be stable and formable with a confidence greater than 90%, are identified for further investigation. Our models are methodically analyzed via performance metrics and inter-dependence of model features to gain physical insight into the band gap prediction problem. Design maps to identify the variation of band gap with substitution of different elements are also presented.

The anticipated benefits of large grains in Cr2O3-doped UO2 pellets include improved mechanical and fission gas retention properties. To support the assessment of fission gas release (FGR) from doped pellets, the impact of doping on fission gas diffusivity for in-reactor conditions must be understood. In this work, we tackle this issue by informing the fission gas model within the BISON fuel performance code using material models developed at the atomic scale. The investigation of intra-granular fission gas diffusivity in Cr2O3-doped UO2 is carried out by adapting a cluster dynamics model that, accounting for UO2 thermochemistry, is capable of describing Xe diffusion under irradiation in undoped UO2 as the starting point. Using a thermodynamic analysis, it is shown that in stoichiometric UO2 with additions of Cr2O3, the oxygen potential is defined by the Cr-Cr2O3 two-phase equilibrium. Using the cluster dynamics model, the predicted Xe diffusivity in doped UO2 was significantly increased in both the intrinsic and irradiation-enhanced regimes compared to undoped UO2, as a result of higher concentrations of uranium and oxygen vacancies, respectively. This is a consequence of the more oxidizing conditions at high temperature, and more reducing conditions at low temperature, as a result of doping. Arrhenius functions have been fitted to the cluster dynamics results to enable implementation of the new diffusivities in the BISON fission gas behavior model. BISON simulations were carried out, showing the competing effects of the enlarged grains and the new fission gas diffusivity model, which act to suppress and enhance fission gas release, respectively. The new physics-informed model was validated against in-reactor experimental measurements under normal operation. Additionally, benchmarking was carried out for power ramp conditions. The predicted fission gas release agreed well with the experimental data, showing noticeable improvements over the standard UO2 model.

U3Si2 is an advanced fuel candidate due to its relatively high fissile density and attractive thermal properties. Compared to standard UO2 fuel, there are significant data gaps for the thermophysical and thermomechanical properties of U3Si2. Point defect concentrations and mobilities under irradiation govern a number of important fuel performance properties, such as creep and fission gas release. In this work, we utilized density functional theory (DFT) data to inform a cluster dynamics framework to predict point defect concentrations in U3Si2 under irradiation. Molecular dynamics (MD) simulations were used to examine the contribution of atomic mixing during ballistic cascades to diffusion, as well as the diffusivity of U and Si at grain boundaries. These atomic scale models for diffusivity were then used to inform a creep model based on bulk (Nabarro-Herring) and grain boundary (Coble) diffusional creep, and climb-limited dislocation creep. The model compares well against available experimental data and has been implemented in the BISON fuel performance code. A demonstration case using simple power profiles has been carried out, showing that negligible creep occurs due to the low temperatures experienced by U3Si2 in-reactor, a consequence of its high thermal conductivity.

Actinide materials exhibit strong spin–lattice coupling and electronic correlations, and are predicted to host new emerging ground states. One example is piezomagnetism and magneto-elastic memory effect in the antiferromagnetic Mott-Hubbard insulator uranium dioxide, though its microscopic nature is under debate. Here, we report X-ray diffraction studies of oriented uranium dioxide crystals under strong pulsed magnetic fields. In the antiferromagnetic state a [888] Bragg diffraction peak follows the bulk magnetostriction that expands under magnetic fields. Upon reversal of the field the expansion turns to contraction, before the [888] peak follows the switching effect and piezomagnetic ‘butterfly’ behaviour, characteristic of two structures connected by time reversal symmetry. An unexpected splitting of the [888] peak is observed, indicating the simultaneous presence of time-reversed domains of the 3-k structure and a complex magnetic-field-induced evolution of the microstructure. These findings open the door for a microscopic understanding of the piezomagnetism and magnetic coupling across strong magneto-elastic interactions.

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

Under radiative environments such as extended hard X- or γ-rays, degradation of scintillation performance is often due to irradiation-induced defects. To overcome the effect of deleterious defects, novel design mitigation strategies are needed to identify and design more resilient materials. The potential for band-edge engineering to eliminate the effect of radiation-induced defect states in rare-earth-doped perovskite scintillators is explored, taking Ce3+-doped LuAlO3 as a model material system, using density functional theory (DFT)-based DFT + U and hybrid Heyd-Scuseria-Ernzerhof (HSE) calculations. From spin-polarized hybrid HSE calculations, the Ce3+ activator ground-state 4f position is determined to be 2.81 eV above the valence band maximum in LuAlO3. Except for the oxygen vacancies which have a deep level inside the band gap, all other radiation-induced defects in LuAlO3 have shallow defect states or are outside the band gap, that is, relatively far away from either the 5d1 or the 4f Ce3+ levels. Finally, we examine the role of Ga doping at the Al site and found that LuGaO3 has a band gap that is more than 2 eV smaller than that of LuAlO3. Specifically, the lowered conduction band edge envelopes the defect gap states, eliminating their potential impact on scintillation performance and providing direct theoretical evidence for how band-edge engineering could be applied to rare-earth-doped perovskite scintillators.

Diffusion of fission gas in UO2 nuclear fuel impacts several important performance metrics, such as fission gas release, swelling, and thermal conductivity. Current empirical models of fission gas release have significant uncertainty, some of which derives from the bulk diffusion rate and its dependence on, for example, fuel chemistry and irradiation. We have applied the previously-developed Free Energy Cluster Dynamics (FECD) methodology in the code Centipede to calculate xenon cluster concentrations in UO2 under intrinsic (high temperature) and irradiation-enhanced (intermediate temperature) conditions in order to develop a model of the xenon diffusion coefficient based on the atomic scale mechanisms responsible for transport. While the diffusion mechanism for xenon in UO2 is adequately described by the Xe + U2O vacancy cluster for intrinsic conditions, a similar process is not capable of capturing measured in-pile fission gas diffusivity at intermediate temperatures. Therefore, a different diffusion mechanism must dominate under this regime. Using calculated atomistic data, we have shown that irradiation-enhanced diffusion at intermediate temperatures occurs via the larger Xe + U4Oy vacancy clusters, which have lower migration barriers and increase in concentration by several orders of magnitude compared to intrinsic conditions. This mechanism is enabled by the increased uranium vacancy concentration under irradiation due to Frenkel pair production. In addition, the fast migration of uranium interstitials with two attached oxygen interstitials lowers the total uranium interstitial concentration through reactions with sinks. This allows the extended defects, such as Xe + U4Oy vacancy clusters, to maintain high concentrations by limiting annihilation with attached vacancies. Predictions using the Xe + U4Oy diffusion mechanism are in good agreement with experiment, albeit with some differences in the Arrhenius slope, which we believe may be related to either experimental or model parameter uncertainty. Finally, an analytical expression suitable for application in fuel performance simulations was derived to capture the predictions of the Centipede simulations. Published by Elsevier B.V.

Heteroanionic oxysulfide perovskite compounds represent an emerging class of new materials allowing for a wide range of tunability in the electronic structure that could lead to a diverse spectrum of novel and improved functionalities. Unlike cation ordered double perovskites—where the origins and design rules of various experimentally observed cation orderings are well known and understood—anion ordering in heteroanionic perovskites remains a largely uncharted territory. In this contribution, we present and discuss insights that have emerged from our first-principles-based electronic structure analysis of a prototypical anion-ordered SrHf(O0.5S0.5)3 oxysulfide chemistry, studied in all possible anion configurations allowed within a finite size supercell. We demonstrate that the preferred anion ordering is always an all-cis arrangement of anions around an HfO3S3 octahedron. As a general finding beyond the specific chemistry, the origins of this ordering tendency are traced back to a combined stabilization effect stemming from electronic, elastic, and electrostatic contributions. These qualitative notions are also quantified using state-of-the-art machine learning models. We further study the relative stability of the identified ordering as a function of A (Ca, Sr, Ba) and B (Ti, Zr, Hf) site chemistries and probe chemistry-dependent trends in the electronic structure and functionality of the material. Most remarkably, we find that the identified ground-state anion ordering breaks the inversion symmetry to create a family of oxysulfide ferroelectrics with a macroscopic polarization >30 μC/cm2, exhibiting a significant promise for electronic materials applications.

An approach to transform and accelerate nuclear fuel development and qualification is outlined. The approach exploits advanced modeling and simulation at the outset to inform constituent and system selection and to enable integral fuel performance analyses. Analyses using these tools identify and prioritize the most important fuel performance parameters and phenomena for subsequent targeted characterization with separate-effects tests. Separate-effects testing spans out-of-pile and in-pile tests and is meant to iterate with and inform engineering-scale integral fuel performance analyses throughout the development process. Exercising this cycle in an agile fashion will increase confidence in the integral fuel performance predictions while reducing uncertainties. This process sets the stage for executing a much more limited set of well-defined integral irradiation tests designed to validate engineering-scale fuel performance codes and to confirm the performance and safety of the fuel system under prototypic conditions. This approach will reduce the time for development and qualification of a new fuel system, and it will also reduce associated costs.

To explore the formation of noncollinear magnetic configurations in materials with strongly correlated electrons, we derive a noncollinear LSDA + U model involving only one parameter U, as opposed to the difference between the Hubbard and Stoner parameters U - J. Computing U in the constrained random phase approximation, we investigate noncollinear magnetism of uranium dioxide UO2 and find that the spin-orbit coupling (SOC) stabilizes the 3k ordered magnetic ground state. The estimated SOC strength in UO2 is as large as 0.73 eV per uranium atom, making spin and orbital degrees of freedom virtually inseparable. Using a multipolar pseudospin Hamiltonian, we show how octupolar and dipole-dipole exchange coupling help establish the 3k magnetic ground state with canted ordering of uranium f orbitals. The cooperative Jahn-Teller effect does not appear to play a significant part in stabilizing the noncollinear 3k state, which has the lowest energy even in an undistorted lattice. The choice of parameter U in the LSDA + U model has a notable quantitative effect on the predicted properties of UO2, in particular on the magnetic exchange interaction and, perhaps trivially, on the band gap: The value of U = 3.46 eV computed fully ab initio delivers the band gap of 2.11 eV in good agreement with experiment, and a balanced account of other pertinent energy scales.

As fission fragments pass through UO2 nuclear fuel, a considerable concentration of Frenkel pair defects (i.e. vacancies and interstitials) are created. The steady-state concentration of these defects leads to enhanced uranium self-diffusion, one of several fundamental kinetic parameters that control key engineering properties such as creep and fission gas swelling in UO2 nuclear fuel. A cluster dynamics method to track point defects and defect clusters has been implemented in the MARMOT phase-field code in order to predict as-measured out-of-pile and irradiation enhanced thermal diffusivity. The calculated uranium self-diffusion coefficient compares well with non-irradiated fuel measurements, and shows similar trends to those observed in irradiated fuel, which is a good result given the complexities introduced by non-stoichiometric compositions.

Diffusion of Xe atoms in UO2 fuel is important for nuclear fuel performance, and is enabled by interaction with U and O vacancies. Previous work using atomistic calculations based on density functional theory (DFT) and empirical potentials (EP) focused on the role of small vacancy clusters (Xe-U2Oy, y = 0, 1, 2) for Xe transport, but the model predictions failed to reproduce the experimental observations by consistently underestimating Xe diffusivity. In this work, where we focused on out-of-pile conditions (i.e. in the absence of irradiation), we have explored two of the uncertainties associated with the model: the DFT methodology and the types of clusters considered. We found that using the energy barriers obtained with GGA + U DFT allows to reconcile simulation results and experimental observations in the intrinsic regime (i.e. out-of-pile conditions). The Xe-UO cluster is the preferred configuration at high temperature, while the mobile Xe-U2O cluster takes over below 1720 K. The latter cluster is also the main contributor to Xe diffusion and good agreement is obtained with current models empirically fitted to experiments for diffusion at high temperature. A simple expression that captures most of Xe diffusivity is proposed, relying on Xe-UO and Xe-U2O clusters only. We also determined the out-of-pile concentration and diffusivity of extended clusters Xe-UxOy, 3 <= x <= 9, and determined that these do not contribute significantly to the overall diffusivity under intrinsic conditions. However, we speculate that the Xe-U4O3 and Xe-U8O9 clusters, which have relatively low migration barrier, may play a role under irradiation conditions, because the radiation-induced enhanced vacancy concentration would rapidly increase the fraction of large Xe-vacancy clusters. (C) 2019 Published by Elsevier B.V.

The defect relaxation volumes obtained from density-functional theory (DFT) calculations of charged vacancies and interstitials are much larger than their neutral counterparts, seemingly unphysically large. We focus on UO2 as our primary material of interest, but also consider Si and GaAs to reveal the generality of our results. In this work, we investigate the possible reasons for this and revisit the methods that address the calculation of charged defects in periodic DFT. We probe the dependence of the proposed energy corrections to charged defect formation energies on relaxation volumes and find that corrections such as potential alignment remain ambiguous with regards to its contribution to the charged defect relaxation volume. We also investigate the volume for the net neutral defect reactions comprising individual charged defects, and find that the aggregate formation volumes have reasonable magnitudes. This work highlights the issue that, as is well-known for defect formation energies, the defect formation volumes depend on the choice of reservoir. We show that considering the change in volume of the electron reservoir in the formation reaction of the charged defects, analogous to how volumes of atoms are accounted for in defect formation volumes, can renormalize the formation volumes of charged defects such that they are comparable to neutral defects. This approach enables the description of the elastic properties of isolated charged defects within an overall neutral material.

The first AFQ workshop was held on Friday, May 31, 2019, in Washington, DC, with over 30 expert participants from industry (General Atomics, Framatome, Lightbridge, TerraPower, Westinghouse), national labs (ANL, INL, LANL, ORNL), DOE-NE, NRC and academia (University of Florida and University of Tennessee). The overall goal of the workshop was to discuss how modeling and experiments can be simultaneously exploited to markedly reduce the years of data (and associated costs) that are currently required for deployment of new nuclear fuels utilizing the new methodology of Accelerated Fuel Qualification (AFQ). There were nine presentations given during the workshop, which included an overview presentation, five case studies, summary of relevant national lab capabilities and on-going DOE programs, as well as perspective from the NRC.