The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Metal-organic frameworks for catalysis: State of the art, challenges, and opportunities
Abstract
Abstract Metal-organic frameworks (MOFs), also known as porous coordination polymers (PCPs), are a unique class of porous crystalline materials that are constructed by metal ions/clusters and organic ligands. The intriguing, numerous and tailorable structures as well as permanent porosity of MOFs make them very promising for a variety of potential applications, especially in catalysis. In this review, we systematically summarize the recent progress of MOF-based materials (including pristine MOFs, MOF composites, and MOF derivatives) for heterogeneous catalysis, photocatalysis and electrocatalysis, according to the category of active site origin. We clearly indicate the significant strengths (and also weaknesses) of the MOF-based materials, in reference to traditional catalysts, in catalytic studies. The challenges and opportunities in regard to the MOF-based materials for catalysis have also been critically discussed.
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Cites
Metal-organic framework materials as catalysts
Lee, J., Farha, O. K., Roberts, J., Scheidt, K. A., Nguyen, S. T., & Hupp, J. T. (2009) · Chemical Society Reviews · doi:10.1039/b807080f · Cited by 7,969
Frontiers, Opportunities, and Challenges in Biochemical and Chemical Catalysis of CO 2 Fixation
Appel, A. M., Bercaw, J. E., Bocarsly, A. B., Dobbek, H., DuBois, D. L., Dupuis, M., Ferry, J. G., Fujita, E., Hille, R., Kenis, P. J. A., et al. (2013) · Chemical Reviews · doi:10.1021/cr300463y · Cited by 2,193
Wu, H. B., Xia, B. Y., Yu, L., Yu, X.-Y., & Lou, X. W. (2015) · Nature Communications · doi:10.1038/ncomms7512 · Cited by 1,434
Xu, H.-Q., Hu, J., Wang, D., Li, Z., Zhang, Q., Luo, Y., Yu, S.-H., & Jiang, H.-L. (2015) · Journal of the American Chemical Society · doi:10.1021/jacs.5b08773 · Cited by 1,166
Self-citationJiao, L., Zhou, Y.-X., & Jiang, H.-L. (2016) · Chemical Science · doi:10.1039/c5sc04425a · Cited by 798
Self-citationHuang, Z.-F., Song, J., Li, K., Tahir, M., Wang, Y.-T., Pan, L., Wang, L., Zhang, X., & Zou, J.-J. (2016) · Journal of the American Chemical Society · doi:10.1021/jacs.5b11986 · Cited by 749
Zhang, H., Ma, Z., Duan, J., Liu, H., Liu, G., Wang, T., Chang, K., Li, M., Shi, L., Meng, X., et al. (2016) · ACS Nano · doi:10.1021/acsnano.5b05728 · Cited by 491
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Recent progress in metal-organic frameworks as active materials for supercapacitors
Wang, K.-B., Xun, Q., & Zhang, Q. (2020) · EnergyChem · doi:10.1016/j.enchem.2019.100025 · Cited by 474
Yan, Y., Li, C., Wu, Y., Gao, J., & Zhang, Q. (2020) · Journal of Materials Chemistry A · doi:10.1039/d0ta03749d · Cited by 260
High-performance non-enzymatic glucose detection: using a conductive Ni-MOF as an electrocatalyst
Qiao, Y., Liu, Q., Lu, S., Chen, G., Gao, S., Lu, W., & Sun, X. (2020) · Journal of Materials Chemistry B · doi:10.1039/d0tb00131g · Cited by 247
Metadata
- Authors
- Li, D., Xu, H.-Q., Jiao, L., & Jiang, H.-L.
- Venue
- EnergyChem
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 1
- Issue
- 1
- Pages
- 100005
- ISSN
- 2589-7780 (ISSN-L)
- OpenAlex
- W2954551512
- Cited by
- 562
- References
- 7
- FWCI
- 27.56
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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