Structure prediction of mixed-anion perovskites: systematic approach integrating octahedral tilting and anion ordering

Abstract

We present a systematic workflow for the structure prediction of mixed-anion perovskites. We consider both octahedral tilting and anion ordering in perovskites to predict potential new oxyfluoride, oxynitride, and nitrofluoride perovskites. The workflow is as follows: (1) pre-screen potential mixed-anion perovskite compositions with the τ tolerance factor, (2) build anion-ordered structure models for 11 perovskite tilt systems, (3) filter the ordered models with a machine-learning methodology, and (4) compare the energetics of the predicted mixed-anion perovskites to experimentally known reference compounds using hybrid density functional methods. We studied 16 novel mixed-anion perovskite compositions, where each composition included approximately 200 000 anion-ordered models. Of these 16 studied mixed-anion perovskite compositions, six are predicted to be energetically favorable compared to experimentally known competing phases.