The design of novel materials plays a key role in the advancement of technologies in any application field. It is therefore crucial that the materials research is pursued with optimal effectiveness and efficiency. Modern computational materials design in synergy with concepts from big data processing and -storage can largely contribute to meet this requirement. For example, the systematic investigation of a large set of bulk materials can be realized fast and cost effective with high-throughput (HT) electronic structure methods.
The general procedure for a HT-approach is to compute the properties of interest of a large set of possible materials. The information is then ideally stored in a searchable database. The last step is the materials search and selection. With statistical and graphical means, the properties of a large set of materials can be visualized. In fig. 1, the formation energy of a binary alloy (FePt) is shown as an example.
Fig. 1: The alloy formation energy of Fe-Pt alloys as function of the composition. Many different structures have been screened (red crosses) and the most stable structures lay on the blue line (convex hull). Data taken from the AFLOWLIB repository.