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MM: Fachverband Metall- und Materialphysik

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

MM 26.4: Vortrag

Dienstag, 17. März 2020, 15:00–15:15, BAR 205

Automatization of magnetic properties calculation using AiiDA-FLEUR — •Vasily Tseplyaev, Jens Bröder, Daniel Wortmann, Markus Hoffmann, and Stefan Blügel — Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany

Magnetic properties of thin films, e.g. magnetic anisotropy, Heisenberg exchange and Dzyaloshinskii-Moriya interaction constants define material quality for possible use in state-of-the art memory and other devices. These parameters can be determined via ab initio theory and the FLEUR [1] code. Together they provide precise simulations with the necessary predictive power. The current state of computational resources allows for high-throughput screening of materials, which means similar calculations are repeated for a large set of possible magnetic film structures that can be promising for further experimental study. Automated computing, data storage, provenance and thus reproducibility are provided by the open science platform AiiDA [2], when key-turn solutions for aforementioned magnetic calculations are implemented as AiiDA-FLEUR plugin. In this talk, we report the current state of AiiDA-FLEUR development, which covers the implemented architecture of general and magnetic workflows and other utilities.

We acknowledge the Center of Excellence MaX – Materials Science at the Exascale (EU H2020-INFRAEDI-2018) for financial support.

1. https://www.flapw.de

2. G. Pizzi et al., Comp. Mat. Sci. 111, 218 (2016).