Progress on Fluorescent Detection Of Nerve Agents Based On Defective-Engineering Modulation Of Metal-Organic Frameworks (MOFs)
Editor: | Mar 12,2025
Nerve agents are chemical warfare agents that could block the acetylcholinesterase (AChE) enzyme in the nervous system, leading to seizures, asphyxiation, and even death. Owning to the terrible lethality even fast within minutes, timely and accurately probing trace nerve agents is critical for reducing or potentially stemming their damage to human life and health. Currently, detection methods for nerve agents mainly include liquid chromatography-mass spectrometry (LC-MS), ion mobility chromatography, broadband photoacoustic spectroscopy, colorimetry and fluorescence, etc. Among these, fluorescence sensing technology stands out for its unique on-site applicability, such as intuitive results, ease of integration, and good operability. At present, fluorescent recognition strategies for nerve agents mainly focus on two aspects: (i) phosphorylation of nerve agents or their analogs, and (ii) protonation of hydroxyl, amino, or pyridyl groups of probe molecules by hydrolysis products of nerve agents or their analogs. However, some challenges remain in resisting environmental interferences, such as susceptibility to acidic substances, structurally similar compounds, and potential co-existing fluorescent substances (e.g., dust and fibers). Therefore, there is an urgent need to develop a rapid, sensitive, and reliable fluorescent sensing method for early warning of trace nerve agents.
To address these issues, based on the unique structural feature of phosphonyl fluoride nerve agents, Prof. Xincun DOU’s team of the Xinjiang Technical Institute of Physics and Chemistry, has proposed a novel chemical activity-molecular dimension dual-sieving strategy for detecting phosphonyl fluoride nerve agents.
Specifically, the team applied a zirconium-based metal-organic framework (MOF) as the sensing material, MOF-525, which has high stability and acid-base resistance, with porphyrin as the ligand and zirconium clusters as the metal nodes. By gradient regulation of the modulator amount, a series of MOF-525 materials with different defect levels were synthesized. Optimization of the modulator amount resulted in a relatively high defective level (~60% defect rate) and weak background fluorescence in the framework structure, providing internal pore sieving capability for the specific size of target phosphonyl fluoride nerve agents. When the defective MOF-525 coordinated and recognized phosphonyl fluoride nerve agents, triggering red fluorescence signal. Leveraging the synergistic sieving effect of molecular size and chemical activity, MOF-525 with a 60% defective level effectively distinguished phosphonyl fluoride nerve agents from structurally similar compounds, demonstrating high sensitivity (0.96 nm/3.8 ppb), rapid response (<1 s), and strong resistance to interferences from acidic substances, humid environments, and common fluorescent materials. This study not only revealed how defect-engineering in MOFs affects their optical property but also opened a new pathway for sensing and recognizing trace nerve agents.
The research finding was published in journal Advanced Functional Materials entitled as “Defect Engineering Zr-MOF-Endowed Activity-Dimension Dual-Sieving Strategy for Anti-acid Recognition of Real Phosphoryl Fluoride Nerve Agents”. Master students Runqiang ZANG from Shihezi University and Yihang WANG from the University of Chinese Academy of Sciences are the co-first authors. Prof. Xincun DOU and Prof. Yuan LIU from Xinjiang Technical Institute of Physics and Chemistry, associate Prof. Xiaowei MA from Shihezi University, and Dr. Molin QIN from State Key Laboratory of NBC Protection for Civilian, are the co-corresponding authors.This work was supported by the National Key Research and Development Program of China and Tianshan Innovation Team Plan.
Figure: Defect Engineering Zr-MOF-Endowed Activity-Dimension Dual-Sieving Strategy for Anti-acid Recognition of Real Phosphoryl Fluoride Nerve Agents (Image by Prof. Xincun DOU’s group)
附件下载: