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Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

[Image: see text] The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by...

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Detalles Bibliográficos
Autores principales: Slater, Anna G., Reiss, Paul S., Pulido, Angeles, Little, Marc A., Holden, Daniel L., Chen, Linjiang, Chong, Samantha Y., Alston, Ben M., Clowes, Rob, Haranczyk, Maciej, Briggs, Michael E., Hasell, Tom, Day, Graeme M., Cooper, Andrew I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2017
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5532722/
https://www.ncbi.nlm.nih.gov/pubmed/28776015
http://dx.doi.org/10.1021/acscentsci.7b00145
Descripción
Sumario:[Image: see text] The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal–organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groups into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure–energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy–structure–function maps.