2021/02/05 by Kamal Choudhary, Kevin F. Garrity, Nirmal J. Ghimire +3
Engineering · Materials Science · Physics and Astronomy · #Advanced Condensed Matter Physics #Condensed matter physics #Density functional theory #Electrical engineering #Electronic and Structural Properties of Oxides #Engineering #Materials science #Physics #Quantum mechanics #Spillage #Spintronics #Topological Materials and Phenomena #Topological insulator #Topology (electrical circuits) #cond-mat.mtrl-sci
paper · pdf · doi:10.1103/physrevb.103.155131
published as Phys. Rev. B 103, 155131 (2021)
arxiv created 2021/02/05 · openalex publication_date 2021/04/16 · arxiv updated 2021/04/21 · openalex created_date 2021/04/26 · openalex updated_date 2026/08/05
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 \ensuremath≈40 000 three-dimensional materials in the JARVIS-DFT database. First, we screen materials with net magnetic moment >0.5\phantom\rule0.16em0ex\ensuremathμB 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.