Abstract
Porous molecular materials exhibit permanent porosity in the solid-state; however, unlike network materials such as metal–organic frameworks (MOFs) and zeolites, porous molecular materials lack a continuous network of covalent bonds but are instead formed from the self-assembly of discrete molecules. Porous molecular materials achieve porosity through either an internal cavity in the molecule (intrinsic porosity) or through inefficient packing in the solid-state, such that the molecule is unable to pack in a way that removes all void space (extrinsic porosity). The focus of this chapter will be the application of computational techniques to rationalize the structures and properties of porous molecular materials, including the development of software and artificial intelligence techniques to assist in the understanding and discovery of these systems. The chapter will include a discussion of examples of experimental realization of computational predictions, as well as an analysis of the challenges associated with accelerating the discovery of these materials using artificial intelligence.
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