Breaking the Aristotype: Featurization of Polyhedral Distortions in Perovskite Crystals

Kazuki Morita, Daniel W. Davies, Keith T. Butler, Aron Walsh

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

While traditional crystallographic representations of structure play an important role in materials science, they are unsuitable for efficient machine learning. A range of effective numerical descriptors have been developed for molecular and crystal structures. We are interested in a special case, where distortions emerge relative to an ideal high-symmetry parent structure. We demonstrate that irreducible representations form an efficient basis for the featurization of polyhedral deformations with respect to such an aristotype. Applied to a data set of 552 octahedra in ABO3 perovskite-type materials, we use unsupervised machine learning with irreducible representation descriptors to identify four distinct classes of behaviors, associated with predominately corner, edge, face, and mixed connectivity between neighboring octahedral units. Through this analysis, we identify SrCrO3 as a material with tunable multiferroic behavior. We further show, through supervised machine learning, that thermally activated structural distortions of CsPbI3 are well described by this approach.

Original languageEnglish
Pages (from-to)562-573
Number of pages12
JournalChemistry of Materials
Volume34
Issue number2
DOIs
Publication statusPublished - 2022 Jan 25

Bibliographical note

Funding Information:
We thank funding support from Yoshida Scholarship Foundation, Japan Student Services Organization, and Centre for Doctoral Training on Theory and Simulation of Materials at Imperial College London funded by the EPSRC (EP/L015579/1). Via our membership of the UK’s HEC Materials Chemistry Consortium, which is funded by EPSRC (EP/R029431), this work used the ARCHER2 UK National Supercomputing Service ( http://www.archer2.ac.uk ).

Publisher Copyright:
© 2022 American Chemical Society.

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Materials Chemistry

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