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Updated: Jun 13, 2025

Time-resolved Photophysical Characterization of Triplet-harvesting Organic Compounds at an Oxygen-free Environment Using an iCCD Camera
Published on: December 27, 2018
Revisiting triplet state dissolved organic matter (3DOM⁎): Advances in probes, photoreactivity, and environmental
Vu Khac Hoang Bui1, Xuan Cuong Nguyen2, Jin Hur3
1Laboratory for Advanced Nanomaterials and Sustainable Energy Technologies, Institute for Computational Science and Artificial Intelligence, Van Lang University, Ho Chi Minh City, Viet Nam; Faculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, Viet Nam; Department of Environment and Energy, Sejong University, Seoul 05006, South Korea.
Abstract:
Triplet-state dissolved organic matter (3DOM⁎) plays a critical role in the photodegradation of organic pollutants in aquatic environments. This review offers a comprehensive overview of 3DOM⁎, focusing on monitoring methods using various probes, formation mechanisms, and photoreactivity. Traditional probes, such as 2,4,6-trimethylphenol (TMP) and sorbic acid, are widely used, while novel probes promise improved accuracy and sensitivity. The E2:E3 ratio emerges as a promising indicator for 3DOM⁎ due to its simplicity and correlation with photoreactivity, though further validation is needed to confirm its broader applicability. This review highlights the higher photoreactivity of DOM with low molecular weight, low aromaticity, and autochthonous sources, although DOM with contrasting features can also show significant photoreactivity. The presence of inorganic ions and nanomaterials significantly influences 3DOM⁎'s degradation capacity, demonstrating complex interactions with surrounding species. Additionally, the review underscores the importance of various environmental factors, including light source and DOM concentration, in affecting the photodegradation rates of contaminants. Recent literature suggests that future research should focus on developing new probes to capture different aspects of 3DOM⁎, exploring the synergistic effects of plastic leachate, and investigating the role of co-existing ions and nanomaterials on 3DOM⁎ activity. Employing machine learning (ML) techniques to predict 3DOM⁎-related parameters from easily measurable DOM descriptors presents an exciting research avenue. Enhanced understanding of 3DOM⁎ can lead to more effective strategies in wastewater treatment and environmental remediation.
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