A taxonomic approach to crystal engineering of coordination polymers: from design to application
New approaches to gas/vapour storage and purification are urgently needed to address the large energy footprint and cost/risk associated with existing technologies, which are mainly based upon chemisorption or solvent based processes. In this context, new classes of porous physisorbents, exemplified by porous coordination networks (PCNs), have emerged. There are now >100,000 entries in the Cambridge Structural Database (CSD) 2 metal-organic framework (MOF) subset3 and the number of publications grows unabatedly. This makes it infeasible to test all existing PCNs for sorption performance and it is therefore timely to introduce a classification approach based upon taxonomy to supplement topological classification of PCNs. In this system, each component of the PCN is given a taxonomic rank, which categorises existing PCNs in a manner useful to crystal engineers. In conjunction with databases such as the CSD, each component of a PCN can be assessed for potential modularity, helping to determine if the PCN represents a platform that can be readily expanded for systematic structure-property relationship studies. The internal consistency of the taxonomic approach is verified by case studies of several well-known PCNs whereas its utility is demonstrated upon understudied topologies and hard-to-rationalise infinite rod building blocks. Overall, taxonomic classification provides a traffic light system to enable crystal engineers in finding a “needle in haystack,” that is, a family (platform) of PCNs that is amenable to crystal engineering and systematic structure/property relationship studies. Taxonomic classification of PCNs has revealed that certain platforms stand out in terms of modularity. For example, pcu nets that are based on pillared sql nets, such as, hybrid ultramicroporous materials4-6 and DMOF7 analogues, as well as sql nets where the linker, metal cation and axial anions are modular.
History
Faculty
- Faculty of Science and Engineering
Degree
- Doctoral
First supervisor
Michael J. ZaworotkoAlso affiliated with
- Bernal Institute
Department or School
- School of Engineering