The screening of mechanical properties in the elastic regime, whose softness and anisotropy are known to be characteristic signatures of flexible frameworks, is also a promising avenue of research but is still in its infancy. While it has not yet been applied to MOFs or supramolecular framework materials, some seminal works have been published on zeolites and other inorganic crystals. For example, Gaillac et al. screened hypothetical zeolites for auxeticity (see subsection 3.2) using a multi-scale modeling strategy combining a force field, DFT calculations, and a machine-learning predictor trained on the DFT results. This scheme is summarized in Figure and allowed the authors to screen a database containing 600,000 materials by performing DFT calculations on 991 structures only. Similar studies, performing DFT calculations on restricted subsets of materials to identify mechanical metamaterials, have been also performed on dense inorganic crystals, as well as more specific families such as two-dimensional metal dichalcogenides and dihalides. The main limitation of this approach is the computational cost of calculation of the elastic tensor through DFT calculations of strained unit cells, limiting the calculations to a small number of materials, or structures with limited unit cell size. However, Wen et al. recently proposed a new ML model that should alleviate some of this cost in the future. These authors published a materials tensor (MatTen) model, based on equivariant graph neural networks, that are suitable for the prediction of crystal tensors -ensuring independence of the frame of reference and preservation of material symmetry. Wen et al. trained this model to reproduce fourth-rank elasticity tensors of inorganic materials, and showed that it has good accuracy in the prediction of specific elastic moduli, such as bulk modulus, average shear modulus and Young's modulus (see Figure ). The publication of this ML model for tensorial properties of crystals opens the way to large-scale prediction and screening of other material-level properties, such as piezoelectric and dielectric tensors, and more.