More recent work has extended this approach to a large number of physical and chemical properties of interest, among which we can list electronic properties, catalytic activity, mechanical behavior, thermal properties, etc. In many of these cases, the "direct" screening approach is complemented by the use of data-based prediction methods, such as machine learning, in order to lower the computational cost and limit the number of physicsbased calculations (often relying on DFT) that need to be performed. In such methodology, three stages are present: