Machine Learning for Organic Cage Property Prediction-Reference-Cited by-同舟云学术

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Machine Learning for Organic Cage Property Prediction

Published:2018-12-10 Issue:3 Volume:31 Page:714-727
ISSN:0897-4756
Container-title:Chemistry of Materials
language:en
Short-container-title:Chem. Mater.

Author:

Turcani Lukas¹,Greenaway Rebecca L.²^ORCID,Jelfs Kim E.¹^ORCID

Affiliation:

1. Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, White City Campus, Wood Lane, W12 0BZ, United Kingdom

2. Department of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool L7 3NY, United Kingdom

Funder

Royal Society

Engineering and Physical Sciences Research Council

H2020 European Research Council

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemmater.8b03572

Reference43 articles.

1. Porous organic cages: soluble, modular and molecular pores

2. Covalent Organic Frameworks and Cage Compounds: Design and Applications of Polymeric and Discrete Organic Scaffolds

3. Functional Molecular Flasks: New Properties and Reactions within Discrete, Self-Assembled Hosts

4. Porous Organic Cages for Gas Chromatography Separations

5. Molecular shape sorting using molecular organic cages

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