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Cited by 981

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Metal–Organic Frameworks as A Tunable Platform for Designing Functional Molecular Materials

Open access
Wang, Cheng, Liu, Demin, Lin, Wenbin·2013·Journal of the American Chemical Society

Abstract

Metal-organic frameworks (MOFs), also known as coordination polymers, represent an interesting class of crystalline molecular materials that are synthesized by combining metal-connecting points and bridging ligands. The modular nature of and mild conditions for MOF synthesis have permitted the rational structural design of numerous MOFs and the incorporation of various functionalities via constituent building blocks. The resulting designer MOFs have shown promise for applications in a number of areas, including gas storage/separation, nonlinear optics/ferroelectricity, catalysis, energy conversion/storage, chemical sensing, biomedical imaging, and drug delivery. The structure-property relationships of MOFs can also be readily established by taking advantage of the knowledge of their detailed atomic structures, which enables fine-tuning of their functionalities for desired applications. Through the combination of molecular synthesis and crystal engineering, MOFs thus present an unprecedented opportunity for the rational and precise design of functional materials.

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Metadata

Authors
Wang, C., Liu, D., & Lin, W.
Venue
Journal of the American Chemical Society
Published
2013-08-28
Volume
135
Issue
36
Pages
13222-13234
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2057523617
Cited by
981
References
3
FWCI
45.88
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Metal–Organic Frameworks as A Tunable Platform for Designing Functional Molecular Materials. https://app.cochat.ai/papers/10.1021/ja308229p
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Wang, C., Liu, D., & Lin, W. (2013). Metal–Organic Frameworks as A Tunable Platform for Designing Functional Molecular Materials. Journal of the American Chemical Society. https://doi.org/10.1021/ja308229p

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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.