ArticleChemical science2024
Streamlining the automated discovery of porous organic cages.
Article in Chemical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Ion-Permselective Porous Organic Cage Membranes.Angewandte Chemie (International ed. in English) · 2026Review
- Enabling technology for accelerated discovery of supramolecular materials.Chemical science · 2025Review
- Accelerated Porosity Screening Using a Multichannel Colorimetric Array.Angewandte Chemie (International ed. in English) · 2025Article
- Evolving Data-Driven Strategies for the Characterization of Supramolecular Polymers and Systems.Angewandte Chemie (International ed. in English) · 2025Review
- Development of an Automated Workflow for Screening the Assembly and Host-Guest Behavior of Metal-Organic Cages Towards Accelerated Discovery.Angewandte Chemie (International ed. in English) · 2025Article
- Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry.Chemical Society reviews · 2025Review
- Enhancing the Photoswitching Properties ofJournal of the American Chemical Society · 2025Article
- Beyond symmetric self-assembly and effective molarity: unlocking functional enzyme mimics with robust organic cages.Beilstein journal of organic chemistry · 2025Article
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Self-assembly through dynamic covalent chemistry (DCC) can yield a range of multi-component organic assemblies. The reversibility and dynamic nature of DCC has made prediction of reaction outcome particularly difficult and thus slows the discovery rate of new organic materials. In addition, traditional experimental processes are time-consuming and often rely on serendipity. Here, we present a streamlined hybrid workflow that combines automated high-throughput experimentation, automated data analysis, and computational modelling, to accelerate the discovery process of one particular subclass of molecular organic materials, porous organic cages. We demonstrate how the design and implementation of this workflow aids in the identification of organic cages with desirable properties. The curation of a precursor library of 55 tri- and di-topic aldehyde and amine precursors enabled the experimental screening of 366 imine condensation reactions experimentally, and 1464 hypothetical organic cage outcomes to be computationally modelled. From the screen, 225 cages were identified experimentally using mass spectrometry, 54 of which were cleanly formed as a single topology as determined by both turbidity measurements and
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.