Machine-Learning Prediction of Metal-Organic Framework Guest Accessibility from Linker and Metal Chemistry



Petuya, Remi ORCID: 0000-0002-3118-6966, Durdy, Samantha, Antypov, Dmytro ORCID: 0000-0003-1893-7785, Gaultois, Michael W ORCID: 0000-0003-2172-2507, Berry, Neil G ORCID: 0000-0003-1928-0738, Darling, George R ORCID: 0000-0001-9329-9993, Katsoulidis, Alexandros P ORCID: 0000-0003-0860-7440, Dyer, Matthew S ORCID: 0000-0002-4923-3003 and Rosseinsky, Matthew J ORCID: 0000-0002-1910-2483
(2022) Machine-Learning Prediction of Metal-Organic Framework Guest Accessibility from Linker and Metal Chemistry. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION, 61 (9).

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Item Type: Article
Uncontrolled Keywords: Database, Guest accessibility, Machine learning, Metal-organic frameworks, Porosity
Divisions: Faculty of Science and Engineering > School of Physical Sciences
Depositing User: Symplectic Admin
Date Deposited: 24 Jan 2022 10:52
Last Modified: 24 Jun 2022 00:10
DOI: 10.1002/anie.202114573
Open Access URL: https://doi.org/10.1002/anie.202114573
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3147534