Machine‐Learning Prediction of Metal–Organic Framework Guest Accessibility from Linker and Metal Chemistry-Reference-Cited by-同舟云学术

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

Published:2022-01-12 Issue: Volume: Page:
ISSN:1433-7851
Container-title:Angewandte Chemie International Edition
language:en
Short-container-title:Angewandte Chemie Intl Edit

Author:

Pétuya Rémi¹²^ORCID,Durdy Samantha³⁴,Antypov Dmytro¹³^ORCID,Gaultois Michael W.¹³^ORCID,Berry Neil G.¹^ORCID,Darling George R.¹^ORCID,Katsoulidis Alexandros P.¹³^ORCID,Dyer Matthew S.¹³^ORCID,Rosseinsky Matthew J.¹³^ORCID

Affiliation:

1. Department of Chemistry and Materials Innovation Factory University of Liverpool 51 Oxford Street Liverpool L7 3NY UK

2. Present address: Nextmol (Bytelab Solutions SL) 08018 Barcelona Spain

3. Leverhulme Research Centre for Functional Materials Design University of Liverpool 51 Oxford Street Liverpool L7 3NY UK

4. Department of Computer Science University of Liverpool Ashton Street Liverpool L69 3BX UK

Funder

King Abdullah University of Science and Technology

Horizon 2020 Framework Programme

Publisher

Wiley

Subject

General Chemistry,Catalysis

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/anie.202114573

Reference33 articles.

1. Hybrid porous solids: past, present, future

2. Introduction to Metal–Organic Frameworks

3. The Chemistry and Applications of Metal-Organic Frameworks

4. Metal–Organic Frameworks for Separations

5. Selective gas adsorption and separation in metal–organic frameworks

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