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Cited by 468

The DOI matches its Crossref record; 285 of the 285 references it cites were found in a registry or an index.

Theoretical Modeling of Singlet Fission

Casanova, David·2018·Chemical Reviews

Abstract

Singlet fission is a photophysical reaction in which a singlet excited electronic state splits into two spin-triplet states. Singlet fission was discovered more than 50 years ago, but the interest in this process has gained a lot of momentum in the past decade due to its potential as a way to boost solar cell efficiencies. This review presents and discusses the most recent advances with respect to the theoretical and computational studies on the singlet fission phenomenon. The work revisits important aspects regarding electronic states involved in the process, the evaluation of fission rates and interstate couplings, the study of the excited state dynamics in singlet fission, and the advances in the design and characterization of singlet fission compounds and materials such as molecular dimers, polymers, or extended structures. Finally, the review tries to pinpoint some aspects that need further improvement and proposes future lines of research for theoretical and computational chemists and physicists in order to further push the understanding and applicability of singlet fission.

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Metadata

Authors
Casanova, D.
Venue
Chemical Reviews
Published
2018-04-12
Volume
118
Issue
15
Pages
7164-7207
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2797333726
Cited by
468
References
285
FWCI
2.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Theoretical Modeling of Singlet Fission. https://app.cochat.ai/papers/10.1021/acs.chemrev.7b00601
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Casanova, D. (2018). Theoretical Modeling of Singlet Fission. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.7b00601

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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.