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(searched for: doi:10.1038/s41597-021-00885-z)
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, Kevin F. Garrity, Nirmal J. Ghimire, , Francesca Tavazza
Physical Review B, Volume 103; doi:10.1103/physrevb.103.155131

Abstract:
Magnetic topological insulators and semimetals have a variety of properties that make them attractive for applications, including spintronics and quantum computation, but very few high-quality candidate materials are known. In this paper, we use systematic high-throughput density functional theory calculations to identify magnetic topological materials from the ≈40 000 three-dimensional materials in the JARVIS-DFT database. First, we screen materials with net magnetic moment >0.5μB and spin-orbit spillage (SOS) >0.25, resulting in 25 insulating and 564 metallic candidates. The SOS acts as a signature of spin-orbit-induced band-inversion. Then we carry out calculations of Wannier charge centers, Chern numbers, anomalous Hall conductivities, surface band structures, and Fermi surfaces to determine interesting topological characteristics of the screened compounds. We also train machine learning models for predicting the spillages, band gaps, and magnetic moments of new compounds, to further accelerate the screening process. We experimentally synthesize and characterize a few candidate materials to support our theoretical predictions.
Published: 19 February 2021
npj Computational Materials, Volume 7, pp 1-9; doi:10.1038/s41524-021-00498-5

Abstract:
Wannier interpolation is a powerful tool for performing Brillouin zone integrals over dense grids ofkpoints, which are essential to evaluate such quantities as the intrinsic anomalous Hall conductivity or Boltzmann transport coefficients. However, more complex physical problems and materials create harder numerical challenges, and computations with the existing codes become very expensive, which often prevents reaching the desired accuracy. In this article, I present a series of methods that boost the speed of Wannier interpolation by several orders of magnitude. They include a combination of fast and slow Fourier transforms, explicit use of symmetries, and recursive adaptive grid refinement among others. The proposed methodology has been implemented in the python code WannierBerri, which also aims to serve as a convenient platform for the future development of interpolation schemes for other phenomena.
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