Symmetry Relation Database and Its Application to Ferroelectric Materials Discovery

TL;DR

This paper introduces a symmetry relation database derived from an automated algorithm, enabling the identification of potential ferroelectric materials and facilitating materials discovery through systematic structure screening.

Contribution

The authors developed a numerical algorithm to automate symmetry relation detection and created a comprehensive database of structure pairs, aiding ferroelectric materials discovery.

Findings

Identified ~4500 structure pairs with close symmetry relations.

Discovered several new ferroelectric materials.

Demonstrated the database's utility for materials prediction.

Abstract

The ability to understand the atomistic mechanisms that occur in the solid phase transition is of crucial importance in materials research. To investigate the displacive phase transition at the atomic scale, we have implemented a numerical algorithm to automate the detection of the symmetry relations between any two candidate crystal structures. Using this algorithm, we systematically screen all possible polar-nonpolar structure pairs from the entire Materials Project database and establish a database of $\sim$4500 pairs that possess a close symmetry relation. These pairs can be connected through a continuous phase transition with small atomic displacements. From this database, we identify several new ferroelectric materials that have never been reported in the past. In addition to the screening of ferroelectric materials, the symmetry relation database may also be used for other areas, such as material structure prediction and new materials discovery.