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Quantum Yields for the Photosensitized Formation of the Lowest Electronically Excited Singlet State of Molecular Oxygen in Solution

Wilkinson, Francis, Helman, W. Phillip, Ross, Alberta B.·1993·Journal of Physical and Chemical Reference Data

Abstract

Quenching of excited singlet and triplet states of many substances by ground state molecular oxygen produces singlet oxygen, the lowest electronically excited singlet state of molecular oxygen, O2(1Δg). The fractions of singlet and triplet states quenched which produce singlet oxygen and the quantum yields of formation of singlet oxgyen in fluid solutions have been critically compiled. Methods for determination yield parameters have been reviewed. Data have been compiled from the literature through 1991. Photosensitizers such as aromatic hydrocarbons, aromatic ketones and thiones, quinones, coumarins, fluoresceins, transition metal complexes, and heterocyclics are included in Table 1. Porphyrins and phthalocyanines are included in Table 2. Other materials which have been investigated for singlet oxygen production, such as dyes and drugs, are collected in Table 3 along with heterogeneous systems such as polymer-bound photosensitizers.

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Metadata

Authors
Wilkinson, F., Helman, W. P., & Ross, A. B.
Venue
Journal of Physical and Chemical Reference Data
Published
1993-01-01
Volume
22
Issue
1
Pages
113-262
ISSN
  • 0047-2689 (ISSN-L)
  • 1529-7845
OpenAlex
W2044533112
Cited by
1,192
References
0
FWCI
7.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Quantum Yields for the Photosensitized Formation of the Lowest Electronically Excited Singlet State of Molecular Oxygen in Solution. https://app.cochat.ai/papers/10.1063/1.555934
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Wilkinson, F., Helman, W. P., & Ross, A. B. (1993). Quantum Yields for the Photosensitized Formation of the Lowest Electronically Excited Singlet State of Molecular Oxygen in Solution. Journal of Physical and Chemical Reference Data. https://doi.org/10.1063/1.555934

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.