Accelerating the Selection of Covalent Organic Frameworks with Automated Machine Learning.
Journal
ACS omega
ISSN: 2470-1343
Titre abrégé: ACS Omega
Pays: United States
ID NLM: 101691658
Informations de publication
Date de publication:
13 Jul 2021
13 Jul 2021
Historique:
received:
09
12
2020
accepted:
19
05
2021
entrez:
19
7
2021
pubmed:
20
7
2021
medline:
20
7
2021
Statut:
epublish
Résumé
Covalent organic frameworks (COFs) have the advantages of high thermal stability and large specific surface and have great application prospects in the fields of gas storage and catalysis. This article mainly focuses on COFs' working capacity of methane (CH
Identifiants
pubmed: 34278102
doi: 10.1021/acsomega.0c05990
pmc: PMC8280634
doi:
Types de publication
Journal Article
Langues
eng
Pagination
17149-17161Informations de copyright
© 2021 The Authors. Published by American Chemical Society.
Déclaration de conflit d'intérêts
The authors declare no competing financial interest.
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