Published June 1, 2023 | Version v1
Dataset Open

Automated mixing of maximally localized Wannier functions into target manifolds

  • 1. Theory and Simulations of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
  • 2. Laboratory for Materials Simulations (LMS), Paul Scherrer Institut (PSI), CH-5232 Villigen PSI, Switzerland

* Contact person

Description

Maximally localized Wannier functions (MLWFs) are widely used to construct first-principles tight-binding models that accurately reproduce the electronic structure of materials. Recently, robust and automated approaches to generate these MLWFs have emerged, leading to natural sets of atomic-like orbitals that describe both the occupied states and the lowest lying unoccupied ones (when the latter can be meaningfully described by bonding/anti-bonding combinations of localized orbitals). For many applications, it is important to instead have MLWFs that describe only certain target manifolds separated in energy between them — the occupied states, the empty states, or certain groups of bands. Here, we start from the full set of MLWFs describing simultaneously all the target manifolds, and then mix them using a combination of parallel transport and maximal localization to construct orthogonal sets of MLWFs that fully and only span the desired target submanifolds. The algorithm is simple and robust, and it is applied to some paradigmatic but non-trivial cases (the valence and conduction bands of silicon, the top valence band of MoS₂, the 3d and t2g/eg bands of SrVO₃ and to a mid-throughput study of 77 insulators.

Files

File preview

files_description.md

All files

Files (944.1 MiB)

Name Apps Size
md5:90579286c7df199846deb9ea91fa7cb0
328 Bytes Preview Download
md5:3f3b706f55908bfc11a2a0c84503bb48
24.3 KiB Preview Download
md5:385f3c75abef75e0dc78697af0f6ba9a
944.1 MiB Download
md5:0082efa3a839ff4f2c2d74a06a3e7d99
2.8 KiB Preview Download

References

Journal reference
J. Qiao, G. Pizzi, & N. Marzari, Automated mixing of maximally localized Wannier functions into target manifolds. npj Comput Mater 9, 206 (2023), doi: 10.1038/s41524-023-01147-9

Preprint
J. Qiao, G. Pizzi, and N. Marzari, Automated mixing of maximally localized Wannier functions into target manifolds, arXiv.2306.00678 (2023), doi: 10.48550/arXiv.2306.00678