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

Rebecca L. Greenaway, Valentina Santolini, Angeles Pulido, Marc A. Little, Ben M. Alston, Michael E. Briggs, Graeme M. Day*, Andrew I. Cooper, Kim E. Jelfs

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)16275-16281
Number of pages7
JournalAngewandte Chemie - International Edition
Issue number45
Publication statusPublished - 10 Sept 2019


  • crystal engineering
  • crystal structure prediction
  • molecular design
  • porous organic cages
  • self-sorting

ASJC Scopus subject areas

  • Catalysis
  • General Chemistry


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