Double Perovskite Oxides

Jiangang He^1,2* , Chris Wolverton¹

¹Department of Materials Science and Engineering, Northwestern University, Evanston, IL 60208, USA

²School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083 China

EXTENDED ABSTRACT: Perovskite oxides have been intensively studied for decades due to the extraordinary variability of compositions and structures and their desirable properties for many important applications, such as superconductivity, magnetoresistance, multiferroicity, catalysis, solid oxide fuel cells, etc. Extending from single perovskite ABO3 to double perovskite A2BB′O6 significantly increases the tunability towards the targeted physical and chemical properties. However, the number of possible compositions of double perovskite is prohibitively large to be entirely explored experimentally. In this talk, we will present a strategy of performing high-throughput calculations to screen ~5,000 compositions of double perovskite A2BB′O6 (A=Ca, Sr, Ba, and La; B and B′ are metal elements). We identify the crystal structures and thermodynamical stabilities of ~2,000 compositions with more than 42,000 DFT calculations. With several hundred new stable/metastable (and so likely synthesizable) compounds predicted by our calculations, we will show how statistical learning of the large dataset can capture the correlation among composition, stability, and crystal structure (i.e., cubic perovskite, distorted perovskite, and non-perovskite). The results will accelerate new double perovskite oxides prediction and discovery.