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Cited by 444

The DOI matches its Crossref record; 117 of the 117 references it cites were found in a registry or an index.

Metal–organic frameworks and porous organic polymers for sustainable fixation of carbon dioxide into cyclic carbonates

Liang, Jun, Huang, Yuan-Biao, Cao, Rong·2019·Coordination Chemistry Reviews

Abstract

Abstract The capture and chemical fixation of carbon dioxide (CO2) into cyclic carbonates is considered to be a promising way to alleviate CO2 concerns and produce fine chemicals. This process can be effectively promoted by various kinds of newly developed porous heterogeneous catalysts with Lewis acidic and nucleophilic sites. These porous catalytic materials include metal–organic frameworks (MOFs), covalent-organic frameworks (COFs), nanoporous ionic organic networks (NIONs) and amorphous porous organic polymers. In this review, we have briefly classified these materials based on their different structural features and compositions. The syntheses and catalytic performances of these porous heterogeneous catalysts are described from the perspective of catalyst design. This review will guide material scientists attempting to design more efficient porous catalysts for CO2 capture and conversions.

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Metadata

Authors
Liang, J., Huang, Y.-B., & Cao, R.
Venue
Coordination Chemistry Reviews
Publisher
Elsevier BV
Published
2019-01
Volume
378
Pages
32-65
ISSN
0010-8545 (ISSN-L)
OpenAlex
W2774533651
Cited by
444
References
117
FWCI
10.44
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Metal–organic frameworks and porous organic polymers for sustainable fixation of carbon dioxide into cyclic carbonates. https://app.cochat.ai/papers/10.1016/j.ccr.2017.11.013
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Liang, J., Huang, Y.-B., & Cao, R. (2019). Metal–organic frameworks and porous organic polymers for sustainable fixation of carbon dioxide into cyclic carbonates. Coordination Chemistry Reviews. https://doi.org/10.1016/j.ccr.2017.11.013

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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.