Density functional theory (DFT) is the de facto standard for the ab-initio prediction of ground-state electronic, magnetic, and structural properties of materials. Using DFT in automatized frameworks for large scale materials screening is on the rise as a key factor for the development of future materials. Resulting databases can also be a foundation for machine learning approaches to extract trends and relations for physical quantities. Within the zoo of DFT implementations, the all-electron full-potential linearized augmented-plane-wave (FLAPW) method has emerged as a robust and precise state-of-the-art technique, especially for DFT calculations on crystals, surfaces, and thin films. It is widely accepted as providing the DFT-reference solution. However, the use and application of DFT methods and of FLAPW in particular require a thorough training where users meet developers of such methods.

Reference

[1] D. Wortmann, G. Michalicek, N. Baadji, M. Betzinger, G. Bihlmayer, J. Bröder, T. Burnus, J. Enkovaara, F.

Freimuth, C. Friedrich, C.-R. Gerhorst, S. Granberg Cauchi, U. Grytsiuk, A. Hanke, J.-P. Hanke, M. Heide, S.

Heinze, R. Hilgers, H. Janssen, D.A. Klüppelberg, R. Kovacik, P. Kurz, M. Lezaic, G.K.H. Madsen, Y.

Mokrousov, A. Neukirchen, M. Redies, S. Rost, M. Schlipf, A. Schindlmayr, M. Winkelmann and S. Blügel,

FLEUR, Zenodo, DOI: 10.5281/zenodo.7576163 (2023)

[2] The FLEUR project: www.flapw.de