Here we demonstrate the deep dreaming experiment for a single MOF using a material property with intuitive optimisation trajectories: the void fraction (VF). The VF (among other structural features) are intrinsically linked to the functionality of a MOF. For instance, enhancing the pore space -and consequently the VF -can significantly increase the CO 2 working capacity in carbon capture applications or the storage capacity in hydrogen / methane storage applications. This is often achieved by extending the length of linker molecules. By this logic, we can expect that an ML model trained to increase the VF of a MOF would adopt a similar optimisation strategy.