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Cited by 160

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Photochemical energy conversion: from molecular dyads to solar cells

Durrant, James R., Haque, Saif A., Palomares, Emilio·2006·Chemical Communications

Abstract

Photochemical approaches to solar energy conversion are currently making rapid progress, increasing not only academic but also commercial interest in molecular-based photovoltaic solar cells. This progress has been achieved not only by increased understanding of the physics and physical chemistry of device function but also through advances in chemical and materials synthesis and processing, which now allows the design and fabrication of increasingly sophisticated device structures organised on the nanometer length scale. In this feature article, we review some progress in this field, focusing in particular upon the electron-transfer dynamics which underlie the function of dye-sensitised, nanocrystalline solar cells. The article starts by building upon the parallels between the function of such devices and the function of simple donor/acceptor molecular systems in solution. We then go on to discuss the optimisation of device function, and in particular the use of self-assembly-based strategies to control interfacial electron-transfer kinetics.

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Metadata

Authors
Durrant, J. R., Haque, S. A., & Palomares, E.
Venue
Chemical Communications
Published
2006
Issue
31
Pages
3279
ISSN
  • 1359-7345 (ISSN-L)
  • 1364-548X
OpenAlex
W2001886191
Cited by
160
References
0
FWCI
15.35
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Photochemical energy conversion: from molecular dyads to solar cells. https://app.cochat.ai/papers/10.1039/b601785c
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Durrant, J. R., Haque, S. A., & Palomares, E. (2006). Photochemical energy conversion: from molecular dyads to solar cells. Chemical Communications. https://doi.org/10.1039/b601785c

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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.