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A highly sensitive and selective chemosensor for Pb2+ based on quinoline-coumarin.
Xianjiao Meng1, Duanlin Cao1, Zhiyong Hu1,2
1School of Chemical Engineering and Technology, North University of China Taiyuan 030051 P. R. China mawenbing@nuc.edu.cn.
RSC Advances
|May 13, 2022
Summary
A novel fluorescent chemosensor was developed for detecting lead ions (Pb2+). This sensor demonstrates high sensitivity and selectivity, offering a reliable method for environmental and biological monitoring of lead contamination.
Area of Science:
- Analytical Chemistry
- Materials Science
- Environmental Science
Background:
- Lead (Pb2+) is a toxic heavy metal pollutant with significant environmental and health implications.
- Accurate and sensitive detection methods for Pb2+ are crucial for monitoring and remediation efforts.
- Fluorescent chemosensors offer advantages in sensitivity and selectivity for ion detection.
Purpose of the Study:
- To synthesize and characterize a novel fluorescent chemosensor for the selective detection of lead ions (Pb2+).
- To evaluate the sensing performance, including sensitivity, selectivity, and optimal detection conditions.
Main Methods:
- Synthesis of ethyl(E)-2-((2-((2-(7-(diethylamino)-2-oxo-2H-chromene-3-carbonyl)hydrazono)methyl)quinolin-8-yl)oxy)acetate (1).
- Characterization using spectroscopic techniques (1H NMR, 13C NMR) and mass spectrometry (ESI-MS).
- Fluorescence spectroscopy was employed to study the response to Pb2+ in a CH3CN/HEPES buffer medium.
Main Results:
- The synthesized sensor (1) exhibited a highly sensitive and selective "on-off" fluorescence response to Pb2+.
- A binding stoichiometry of 1:1 between the sensor and Pb2+ was established.
- The sensor demonstrated a low detection limit of 0.5 μM for Pb2+ within a stable pH range of 4 to 8.
Conclusions:
- The developed fluorescent chemosensor provides a promising tool for the sensitive and selective detection of lead ions.
- The sensor's performance characteristics make it suitable for potential applications in environmental monitoring and biological sample analysis.
- Further research could explore its application in real-world sample matrices.
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