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The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Porous Organic Materials: Strategic Design and Structure–Function Correlation

Das, Saikat, Heasman, Patrick, Ben, Teng, Qiu, Shilun·2017·Chemical Reviews

Abstract

Porous organic materials have garnered colossal interest with the scientific fraternity due to their excellent gas sorption performances, catalytic abilities, energy storage capacities, and other intriguing applications. This review encompasses the recent significant breakthroughs and the conventional functions and practices in the field of porous organic materials to find useful applications and imparts a comprehensive understanding of the strategic evolution of the design and synthetic approaches of porous organic materials with tunable characteristics. We present an exhaustive analysis of the design strategies with special emphasis on the topologies of crystalline and amorphous porous organic materials. In addition to elucidating the structure-function correlation and state-of-the-art applications of porous organic materials, we address the challenges and restrictions that prevent us from realizing porous organic materials with tailored structures and properties for useful applications.

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Crossref · 10.1021/acs.chemrev.6b00439

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Metadata

Authors
Das, S., Heasman, P., Ben, T., & Qiu, S.
Venue
Chemical Reviews
Published
2016-12-30
Volume
117
Issue
3
Pages
1515-1563
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2564707016
Cited by
1,286
References
4
FWCI
3.25
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Porous Organic Materials: Strategic Design and Structure–Function Correlation. https://app.cochat.ai/papers/10.1021/acs.chemrev.6b00439
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Das, S., Heasman, P., Ben, T., & Qiu, S. (2017). Porous Organic Materials: Strategic Design and Structure–Function Correlation. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.6b00439

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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.