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Cited by 184

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Porous Polymers: Enabling Solutions for Energy Applications

Thomas, Arne, Kuhn, Pierre, Weber, Jens, Titirici, Maria‐Magdalena, Antonietti, Markus·2009·Macromolecular Rapid Communications

Abstract

A new generation of porous polymers was made for various energy‐related applications, e.g., as fuel cell membranes, as electrode materials for batteries, for gas storage, partly from renewable resources. This review intends to catch this emerging field by reporting on a variety of different approaches to make high performing polymers porous. This includes template techniques, polymers with inherent microporosity, polymer frameworks by ionothermal polymerization, and the polymerization of carbon from appropriate precursors and by hydrothermal polymerization. In this process, we try to not only identify the current status of the field, but also point to open question and tasks to identify the potentially relevant progress. magnified image

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Registry

Crossref · 10.1002/marc.200800642

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Metadata

Authors
Thomas, A., Kuhn, P., Weber, J., Titirici, M., & Antonietti, M.
Venue
Macromolecular Rapid Communications
Publisher
Wiley
Published
2009-02-06
Volume
30
Issue
4-5
Pages
221-236
ISSN
  • 1022-1336 (ISSN-L)
  • 1521-3927
OpenAlex
W2014730193
Cited by
184
References
6
FWCI
11.01
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Porous Polymers: Enabling Solutions for Energy Applications. https://app.cochat.ai/papers/10.1002/marc.200800642
The paper
Thomas, A., Kuhn, P., Weber, J., Titirici, M., & Antonietti, M. (2009). Porous Polymers: Enabling Solutions for Energy Applications. Macromolecular Rapid Communications. https://doi.org/10.1002/marc.200800642

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.