npj Computational Materials (Feb 2023)

Finding stable multi-component materials by combining cluster expansion and crystal structure predictions

  • Adam Carlsson,
  • Johanna Rosen,
  • Martin Dahlqvist

DOI
https://doi.org/10.1038/s41524-023-00971-3
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 10

Abstract

Read online

Abstract A desired prerequisite when performing a quantum mechanical calculation is to have an initial idea of the atomic positions within an approximate crystal structure. The atomic positions combined should result in a system located in, or close to, an energy minimum. However, designing low-energy structures may be a challenging task when prior knowledge is scarce, specifically for large multi-component systems where the degrees of freedom are close to infinite. In this paper, we propose a method for identification of low-energy crystal structures within multi-component systems by combining cluster expansion and crystal structure predictions with density-functional theory calculations. Crystal structure prediction searches are applied to the Mo2AlB2 and Sc2AlB2 ternary systems to identify candidate structures, which are subsequently used to explore the quaternary (pseudo-binary) (Mo x Sc1–x )2AlB2 system through the cluster expansion formalism utilizing the ground-state search approach. Furthermore, we show that utilizing low-energy structures found within the cluster expansion ground-state search as seed structures within crystal structure predictions of (Mo x Sc1–x )2AlB2 can significantly reduce the computational demands. With this combined approach, we not only correctly identified the recently discovered Mo4/3Sc2/3AlB2 i-MAB phase, comprised of in-plane chemical ordering of Mo and Sc and with Al in a Kagomé lattice, but also predict additional low-energy structures at various concentrations. This result demonstrates that combining crystal structure prediction with cluster expansion provides a path for identifying low-energy crystal structures in multi-component systems by employing the strengths from both frameworks.