Dual‐Response Fluorescence System using COF‐Based Materials Enables Ultra‐Selective Sarin Simulant Detection in Real‐World Environments

Abstract High‐performance detection of chemical warfare agents is essential for early warning and mitigation of associated hazards. However, achieving high selectivity detection remains a major challenge, especially under real‐world conditions where chemical interferences are ubiquitous. Herein, the ultra‐selective recognition of a nerve agent simulant, diethylchlorophosphate (DCP) is demonstrated, in complex environments with a novel dual‐response fluorescence system using COF‐based materials. The fluorescence system comprises two key sensing components: a fluorescent covalent organic framework ( COF ) and a fluorescent small organic molecule ( M1 )‐encapsulated COF ( M1@COF ). It exhibits the ultra‐selectivity for DCP vapor by two differential responsive signals, in which COF exhibits a turn‐on response and M1@COF displays a turn‐off response. Both materials demonstrate high sensitivity at 13 ppb and an ultra‐fast response time of 1.1 s. Remarkably, the system maintains excellent selectivity even under the presence of car exhaust and shower gel vapor, demonstrating its strong potential for practical applications. Mechanistic studies reveal that competing intermolecular interactions‐including hydrogen bonding between DCP and COF and covalent interactions between DCP and M1 ‐underlie the high selectivity of the system. This study highlights the promising potential of COF‐based materials for hazardous vapor recognition and paves the way for the development of high‐performance portable devices suitable for complex environments.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-11-17
DOI
https://doi.org/10.1002/adfm.202527199
Citations
1
Primary Topic
Covalent Organic Framework Applications
Type
article
Field-Weighted Citation Impact
0.52
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article

Dual‐Response Fluorescence System using COF‐Based Materials Enables Ultra‐Selective Sarin Simulant Detection in Real‐World Environments

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1 citations
Advanced Functional Materials
Covalent Organic Framework Applications
0.52
article

Dual‐Response Fluorescence System using COF‐Based Materials Enables Ultra‐Selective Sarin Simulant Detection in Real‐World Environments

Yanke Che, Mei Zhao, Yajie Song, Yongxian Guo, Ru‐Song Zhao, Yanjun Gong, Qiongzheng Hu, Mashooq Khan, Yiwei Liu, Leilei Wang, Shuya Liu, Qiaoru Zhang
article en
1 citations

Abstract

Abstract High‐performance detection of chemical warfare agents is essential for early warning and mitigation of associated hazards. However, achieving high selectivity detection remains a major challenge, especially under real‐world conditions where chemical interferences are ubiquitous. Herein, the ultra‐selective recognition of a nerve agent simulant, diethylchlorophosphate (DCP) is demonstrated, in complex environments with a novel dual‐response fluorescence system using COF‐based materials. The fluorescence system comprises two key sensing components: a fluorescent covalent organic framework ( COF ) and a fluorescent small organic molecule ( M1 )‐encapsulated COF ( M1@COF ). It exhibits the ultra‐selectivity for DCP vapor by two differential responsive signals, in which COF exhibits a turn‐on response and M1@COF displays a turn‐off response. Both materials demonstrate high sensitivity at 13 ppb and an ultra‐fast response time of 1.1 s. Remarkably, the system maintains excellent selectivity even under the presence of car exhaust and shower gel vapor, demonstrating its strong potential for practical applications. Mechanistic studies reveal that competing intermolecular interactions‐including hydrogen bonding between DCP and COF and covalent interactions between DCP and M1 ‐underlie the high selectivity of the system. This study highlights the promising potential of COF‐based materials for hazardous vapor recognition and paves the way for the development of high‐performance portable devices suitable for complex environments.

Advanced Functional MaterialsVol. 36(25)
Qilu University of Technology (CN), Shandong University (CN), Chinese Academy of Sciences (CN), Beijing National Laboratory for Molecular Sciences (CN), Shandong Academy of Sciences (CN)
Openalex Percentile: Top 30%
Covalent Organic Framework Applications
0.52
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