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Opportunities of Covalent Organic Frameworks for Advanced Applications
Open accessAbstract
Covalent organic frameworks (COFs) are an emerging class of functional nanostructures with intriguing properties, due to their unprecedented combination of high crystallinity, tunable pore size, large surface area, and unique molecular architecture. The range of properties characterized in COFs has rapidly expanded to include those of interest for numerous applications ranging from energy to environment. Here, a background overview is provided, consisting of a brief introduction of porous materials and the design feature of COFs. Then, recent advancements of COFs as a designer platform for a plethora of applications are emphasized together with discussions about the strategies and principles involved. Finally, challenges remaining for this type material for real applications are outlined.
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Self-citationControlled Gas Uptake in Metal–Organic Frameworks with Record Ammonia Sorption
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Porous Liquids: A Promising Class of Media for Gas Separation
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Microtubular Self‐Assembly of Covalent Organic Frameworks
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Metadata
- Authors
- Song, Y., Sun, Q., Aguila, B., & Ma, S.
- Venue
- Advanced Science
- Publisher
- Wiley
- Published
- 2018-11-12
- Volume
- 6
- Issue
- 2
- Pages
- 1801410-1801410
- ISSN
- 2198-3844 (ISSN-L)
- OpenAlex
- W2901114803
- Cited by
- 586
- References
- 144
- FWCI
- 20.87
- Type
- journal article
- Language
- en
- Open access
- gold
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.