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From Concept to Crystals via Prediction: Multi-Component Organic Cage Pots by Social Self-Sorting

preprint
submitted on 23.07.2019 and posted on 24.07.2019 by Rebecca L. Greenaway, Valentina Santolini, Angeles Pulido, Marc A. Little, Ben M. Alston, Michael Briggs, Graeme Day, Andrew I. Cooper, Kim Jelfs

We describe the a priori computational prediction and realization of multi-component cage pots, starting with molecular predictions based on candidate precursors through to crystal structure prediction and synthesis using robotic screening. The molecules were formed by the social self-sorting of a tri-topic aldehyde with both a tri-topic amine and di-topic amine, without using orthogonal reactivity or precursors of the same topicity. Crystal structure prediction suggested a rich polymorphic landscape, where there was an overall preference for chiral recognition to form heterochiral rather than homochiral packings, with heterochiral pairs being more likely to pack window-to-window to form two-component capsules. These crystal packing preferences were then observed in experimental crystal structures.

Funding

RobOT, ERC Grant Agreement No. 321156,

ANGLE, ERC Grant No. 307358,

CoMMaD, ERC Grant No. 758370),

EP/M017257/1

EP/P005543/1

EP/N004884/1

EP/L000202/1

Royal Society University Research Fellow

History

Email Address of Submitting Author

k.jelfs@imperial.ac.uk

Institution

Imperial College London

Country

United Kingdom

ORCID For Submitting Author

0000-0001-7683-7630

Declaration of Conflict of Interest

No conflict of interest

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