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Author ORCID ID is 000000019989219X
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  1. Applications of inorganic scintillators—activated with lanthanide dopants, such as Ce and Eu—are found in diverse fields. As a strict requirement to exhibit scintillation, the 4f ground state (with the electronic configuration of [Xe]4 fn 5 d 0) and 5 d 1 lowest excited state (with the electronic configuration of [Xe]4 f n–1 5 d 1) levels induced by the activator must lie within the host bandgap. Here we introduce a new machine learning (ML) based search strategy for high-throughput chemical space explorations to discover and design novel inorganic scintillators. Building upon well-known physics-based chemical trends for the host dependent electronmore » binding energies within the 4 f and 5 d 1 energy levels of lanthanide ions and available experimental data, the developed ML model—coupled with knowledge of the vacuum referred valence and conduction band edges computed from first principles—can rapidly and reliably estimate the relative positions of the activator’s energy levels relative to the valence and conduction band edges of any given host chemistry.« less
  2. Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less
  3. We present a study of the diffusion of krypton in UO 2 using atomic scale calculations combined with diffusion models adapted to the system studied. The migration barriers of the elementary mechanisms for interstitial or vacancy assisted migration are calculated in the DFT + U framework using the nudged elastic band method. The attempt frequencies are obtained from the phonon modes of the defect at the initial and saddle points using empirical potential methods. The diffusion coefficients of Kr in UO 2 are then calculated by combining this data with diffusion models accounting for the concentration of vacancies and themore » interaction of vacancies with Kr atoms. We determined the preferred mechanism for Kr migration and the corresponding diffusion coefficient as a function of the oxygen chemical potential μ O or nonstoichiometry. For very hypostoichiometric (or U-rich) conditions, the most favorable mechanism is interstitial migration. For hypostoichiometric UO 2, migration is assisted by the bound Schottky defect and the charged uranium vacancy, V U 4–. Around stoichiometry, migration assisted by the charged uranium–oxygen divacancy (V UO 2–) and V U 4– is the favored mechanism. Finally, for hyperstoichiometric or O-rich conditions, the migration assisted by two V U 4– dominates. Kr migration is enhanced at higher μ O, and in this regime, the activation energy will be between 4.09 and 0.73 eV depending on nonstoichiometry. The experimental values available are in the latter interval. Since it is very probable that these values were obtained for at least slightly hyperstoichiometric samples, our activation energies are consistent with the experimental data, even if further experiments with precisely controlled stoichiometry are needed to confirm these results. Finally, the mechanisms and trends with nonstoichiometry established for Kr are similar to those found in previous studies of Xe.« less
  4. Uranium silicides, in particular U 3Si 2, are being explored as an advanced nuclear fuel with increased accident tolerance as well as competitive economics compared to the baseline UO 2 fuel. Here we use density functional theory calculations and thermochemical analysis to assess the stability of U 3Si 2 with respect to non-stoichiometry reactions in both the hypo- and hyper-stoichiometric regimes. We find that the degree of non-stoichiometry in U 3Si 2 is much smaller than in UO 2 and at most reaches a few percent at high temperature. Non-stoichiometry impacts fuel performance by determining whether the loss of uraniummore » due to fission leads to a non-stoichiometric U 3Si 2±x phase or precipitation of a second U-Si phase. Lastly, we also investigate the U 5Si 4 phase as a candidate for the equilibrium phase diagram.« less
  5. The diffusivity of the solid fission products (FP) Zr (Zr 4+), Ru (Ru 4+, Ru 3+), Ce (Ce 4+), Y (Y 3+), La (La 3+), Sr (Sr 2+) and Ba (Ba 2+) by a vacancy mechanism has been calculated, using a combination of density functional theory (DFT) and empirical potential (EP) calculations. The activation energies for the solid fission products are compared to the activation energy for Xe fission gas atoms calculated previously. Apart from Ru, the solid fission products all exhibit higher activation energy than Xe. Furthermore, for all solid FPs except Y 3+, the migration of the FPmore » has lower barrier than the migration of a neighboring U atom, making the latter the rate limiting step for direct migration. An indirect mechanism, consisting of two successive migrations around the FP, is also investigated. The calculated diffusivities show that most solid fission products diffuse with rates similar to U self-diffusion. But, Ru, Ba and Sr exhibit faster diffusion than the other solid FPs, with Ru 3+ and Ru 4+ diffusing even faster than Xe for T < 1200 K. The diffusivities correlate with the observed fission product solubility in UO 2, and the tendency to form metallic and oxide second phase inclusions.« less

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