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Cited by 1,754

The DOI matches its Crossref record; 440 of the 440 references it cites were found in a registry or an index.

Metal–Organic Frameworks in Heterogeneous Catalysis: Recent Progress, New Trends, and Future Perspectives

Bavykina, Anastasiya, Kolobov, Nikita, Khan, Il Son, Bau, Jeremy A., Ramirez, Adrian, Gascon, Jorge·2020·Chemical Reviews

Abstract

More than 95% (in volume) of all of today's chemical products are manufactured through catalytic processes, making research into more efficient catalytic materials a thrilling and very dynamic research field. In this regard, metal-organic frameworks (MOFs) offer great opportunities for the rational design of new catalytic solids, as highlighted by the unprecedented number of publications appearing over the past decade. In this review, the recent advances in the application of MOFs in heterogeneous catalysis are discussed. MOFs with intrinsic thermocatalytic activity, as hosts for the incorporation of metal nanoparticles, as precursors for the manufacture of composite catalysts and those active in photo- and electrocatalytic processes are critically reviewed. The review is wrapped up with our personal view on future research directions.

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Crossref · 10.1021/acs.chemrev.9b00685

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Metadata

Authors
Bavykina, A., Kolobov, N., Khan, I. S., Bau, J. A., Ramirez, A., & Gascon, J.
Venue
Chemical Reviews
Published
2020-03-30
Volume
120
Issue
16
Pages
8468-8535
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W3014055873
Cited by
1,754
References
440
FWCI
5.62
Type
journal article
Language
en
Open access
closed

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Bavykina, A., Kolobov, N., Khan, I. S., Bau, J. A., Ramirez, A., & Gascon, J. (2020). Metal–Organic Frameworks in Heterogeneous Catalysis: Recent Progress, New Trends, and Future Perspectives. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.9b00685

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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.