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Cited by 620

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

Powering the future of molecular artificial photosynthesis with light-harvesting metallosupramolecular dye assemblies

Frischmann, Peter D., Mahata, Kingsuk, Würthner, Frank·2013·Chem. Soc. Rev.

Abstract

Chemical ingenuity will play a significant role in solving the greatest challenge currently facing society: providing clean and carbon neutral energy for all of humanity. Molecular artificial photosynthesis is an emerging technology based on principles learned from Nature where individual components perform the essential light-harvesting, charge-separation, and water splitting functions to store solar energy in the form of chemical bonds. This tutorial review focuses specifically on the application of metallosupramolecular self-assembly strategies to interface solar fuel catalysts with photosensitizers and construct light-harvesting antennae capable of achieving panchromatic absorption and directional energy concentration.

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Crossref · 10.1039/c2cs35223k

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Metadata

Authors
Frischmann, P. D., Mahata, K., & Würthner, F.
Venue
Chem. Soc. Rev.
Published
2013
Volume
42
Issue
4
Pages
1847-1870
ISSN
  • 0306-0012 (ISSN-L)
  • 1460-4744
OpenAlex
W2067301242
Cited by
620
References
3
FWCI
1.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Powering the future of molecular artificial photosynthesis with light-harvesting metallosupramolecular dye assemblies. https://app.cochat.ai/papers/10.1039/c2cs35223k
The paper
Frischmann, P. D., Mahata, K., & Würthner, F. (2013). Powering the future of molecular artificial photosynthesis with light-harvesting metallosupramolecular dye assemblies. Chem. Soc. Rev. https://doi.org/10.1039/c2cs35223k

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.