Dresden 2020 – scientific programme

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MM: Fachverband Metall- und Materialphysik

MM 26: Topical Session: Data Driven Materials Science - Machine Learning for Materials Properties

MM 26.2: Talk

Tuesday, March 17, 2020, 14:30–14:45, BAR 205

Analysis of magnetic properties in the Fe-Si system using first principles calculations — •Matteo Rinaldi, Matous Mrovec, and Ralf Drautz — Interdisciplinary Centre for Advanced Materials Simulation (ICAMS), Ruhr-Universität Bochum, Germany

Magnetic steels containing small amounts of silicon have been used extensively as soft magnetic materials in various technological applications. The behavior of magnetic materials can be simulated at the macroscale using a micromagnetic model whose key parameters, such as exchange stiffness constants and magnetic anisotropies can be derived from first-principles electronic structure calculations. In our work, we employ Korringa-Kohn-Rostoker (KKR) Green's function calculations together with a Wannier-based tight-binding (TB) method to investigate the dependence of the spin-wave stiffness and the first coefficient of the cubic magneto-crystalline anisotropy on the Si concentration. These two methodologies give a chemical and structural description of the changes in the micromagnetic parameters caused by the addition of Si. The KKR method is used in conjunction with the Coherent Potential Approximation to simulate chemical disorder while the TB method addresses local relaxations induced by the presence of Si in a supercell framework. The role played by the hybridization between the Si and Fe orbitals turned out be decisive to explain the trends in the micromagnetic parameters. Our calculated values are in excellent agreement with available experimental data.