Large-scale targeted exploration of metal–organic frameworks (MOFs) with characteristics such as specific surface chemistry or metal-cluster family has not been investigated so far. These definitions ...

We report the generation and characterization of the most complete collection of metal–organic frameworks (MOFs) maintained and updated, for the first time, by the Cambridge Crystallographic Data Centre (CCDC). To set up this subset, we asked the question “what is a MOF?” and implemented a number of “look-for-MOF” criteria embedded within a bespoke Cambridge Structural Database (CSD) Python API workflow to identify and extract information on 69 666 MOF materials. The CSD MOF subset is updated regularly with subsequent MOF additions to the CSD, bringing a unique record for all researchers working in the area of porous materials around the world, whether to perform high-throughput computational screening for materials discovery or to have a global view over the existing structures in a single resource. Using this resource, we then developed and used an array of computational tools to remove residual solvent molecules from the framework pores of all the MOFs identified and went on to analyze geometrical and physical properties of nondisordered structures.

Metal−organic frameworks (MOFs) have shown adsorption behavior that is not observed in other microporous materials such as zeolites or activated carbons. This study used grand canonical Monte Carlo si...

A multi-scale, hierarchical ‘Safety-by-Design’ pipeline combining machine learning, ex vivo human blood assays, and in vivo models enables the systematic immunotoxicity and biocompatibility profiling....