Density Functional Theory (DFT) Calculations of Point Defect Properties to Inform Nuclear Fuel Performance Models

Thermodynamic and kinetic properties of point defects are important for the performance of nuclear fuels in reactors; among others, they influence creep, fission gas release, swelling, densification and thermal conductivity. Being able to predict properties of point defects by density functional theory (DFT) calculations provides an avenue to develop mechanism-based engineering scale simulation codes for fuel performance using a multi-scale approach. In this presentation, DFT methodologies to simulate nuclear fuels will be reviewed. This will be followed by showcasing current applications of DFT to point defect properties of UO₂. For UO₂ the latest DFT methodology explicitly considers a dispersion correction, spin–orbit interaction, and noncollinear magnetic contributions. The importance of accurate DFT data will be shown by building a point defect model informed by defect energies calculated by DFT and vibrational entropies obtained by empirical potential calculations, followed by predicting point defect concentrations in UO_2±x over a wide range of conditions. Experimental validation is achieved by comparing to experimental data for the deviation of x in UO_2±x as a function of temperature and oxygen partial pressure and to the uranium self-diffusion coefficient for nearly stoichiometric UO_2±x. The link between point defect properties and the irradiation response of UO₂ is investigated by using the cluster dynamics code Centipede. In addition to the thermodynamic properties, this code captures defect production, self-interactions, sink-reactions, clustering, and kinetic properties governing the response to irradiation. The resulting defect behavior will be connected to in-reactor performance at the engineering scale through diffusion and retention/release of fission gas and creep. The application of similar simulation methodology to other fuel types, such as UN and TRISO fuels, will also be discussed.