Computationally Efficient DFT-based Sampling of Ion Diffusion in Crystalline Solids

We present a method for large scale DFT-based screening of ion diffusion in crystalline solids. This is accomplished by extending the Ionic TuTraSt method to sample the Potential Energy Surface (PES) using single-point DFT calculations. To drastically reduce the number of single-point DFT calculations, symmetry, interpolation and the exclusion of high-energy regions are employed. The method, together with the strategies to reduce the number of DFT calculations are tested on a large dataset. This allows to optimize the interpolation and high-energy exclusion with respect to balancing computational efficiency and accuracy of the diffusion properties. Furthermore, Ionic TuTraSt is validated by comparison with ab initio molecular dynamics (AIMD) simulations on a set of known Li-ion superconducting materials.