Automated high-throughput Wannierisation

TL;DR

This paper introduces an automated, robust method for generating maximally-localised Wannier functions suitable for high-throughput materials screening, using the SCDM approach within an AiiDA workflow, validated on 200 diverse materials.

Contribution

We developed an automatic procedure for Wannier function generation based on SCDM, enabling high-throughput applications without user intervention.

Findings

Successfully applied to 200 materials across diverse structures

Achieved accurate band-structure interpolation compared to full calculations

Provided a reproducible computational workflow and virtual machine

Abstract

Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high-throughput (HT) computational materials design is an emergent field that promises to accelerate the reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method (SCDM) and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space. We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations. Finally, we provide a downloadable virtual machine that can be used to reproduce the results of this paper, including all first-principles and atomistic simulations as well as the computational workflows.