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 linearied 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.