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Cited by 1,070

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Energy Transfer Mechanisms and the Molecular Exciton Model for Molecular Aggregates1, 2

Kasha, Michael·2012·Radiation Research

Abstract

Energytransferphenomenacontinuetofascinatethebiologist, chemist, and physicist, and the literature contains numerous experiments designed to demonstrate the presence of excitation energy transfer. At the present stage of development of the theoryofsuchprocesses, thegoal oftheseresearchesmightwell be not merely the demonstration of the presence of energy transfer, but a more detailed investigation designed to establish which available mechanism of energy transfer is operative. The field of excitation energy transfer is replete with redundant and overlapping terms, whose multitude itself lends little order to the subject. Various authors quote, as energy transfer mechanisms, exciton transfer, resonance transfer, dipole-dipole transfer, inductive resonance, resonance force transfer, virtual photons, and diffuse excitation, among others. This paper will be devoted to the laying down of a further perspective for the discrimination and understanding of the main types of excitation energy transfer. A necessary

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Metadata

Authors
Kasha, M.
Venue
Radiation Research
Published
2012-08
Volume
178
Issue
2
Pages
AV27-AV34
ISSN
  • 0033-7587 (ISSN-L)
  • 1938-5404
OpenAlex
W2139680801
Cited by
1,070
References
1
FWCI
39.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Energy Transfer Mechanisms and the Molecular Exciton Model for Molecular Aggregates1, 2. https://app.cochat.ai/papers/10.1667/rrav03.1
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Kasha, M. (2012). Energy Transfer Mechanisms and the Molecular Exciton Model for Molecular Aggregates1, 2. Radiation Research. https://doi.org/10.1667/rrav03.1

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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.