A Novel Strategy for High‐Sensitivity Detection of Sulfadiazine Using Green Silicon Quantum Dots Based Fluorescent Molecularly Imprinted Sensors

ABSTRACT The issue of pharmaceutical residues in the environment has become increasingly severe, with the detection of sulfonamide antibiotics emerging as a research hotspot in environmental monitoring. Herein, we present a method for detecting sulfadiazine based on a silicon quantum dots (SiQDs)‐based fluorescent molecularly imprinted sensor. SiQDs, synthesized using an aqueous phase method, exhibit remarkable fluorescent properties, such as a broad excitation spectrum, tunable emission wavelengths, and high fluorescence stability, offering significant advantages in pharmaceutical detection. By integrating amino‐functionalized silica nanospheres (NH 2 ‐SiO 2 ) and tetraethyl orthosilicate, SiQDs were surface‐functionalized to construct SiQDs@NH 2 ‐SiO 2 @MIPs composite materials. The modified fluorescent molecularly imprinted polymers not only exhibited high selectivity and affinity for the target molecule SDZ, but also demonstrated excellent stability and resistance to interference in complex environments. Experimental results revealed that the sensor displayed a strong linear correlation within the concentration range of 40–100 μmol·L −1 , with a detection limit of 0.036 ng·mL −1 , demonstrating high sensitivity and excellent selectivity. In real sample applications, the recovery rate ranged from 97.88% to 100.74%, with a relative standard deviation of less than 5.37%. These findings emphasize the wide potential applications of this sensor, especially in water quality monitoring, environmental protection, and pharmaceutical detection.

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Publication Details

Journal
Polymers for Advanced Technologies
Published
2025-02-01
DOI
https://doi.org/10.1002/pat.70108
Citations
3
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
2.02

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article

A Novel Strategy for High‐Sensitivity Detection of Sulfadiazine Using Green Silicon Quantum Dots Based Fluorescent Molecularly Imprinted Sensors

Hongjie Lu, Wenming Yang, Wei-Hong Huang, Wanzhen Xu et al.
3 citations
Polymers for Advanced Technologies
Biosensors and Analytical Detection
2.02
article

A Novel Strategy for High‐Sensitivity Detection of Sulfadiazine Using Green Silicon Quantum Dots Based Fluorescent Molecularly Imprinted Sensors

Hongjie Lu, Wenming Yang, Wei-Hong Huang, Wanzhen Xu, Xiaoqiang Chen
article en
3 citations

Abstract

ABSTRACT The issue of pharmaceutical residues in the environment has become increasingly severe, with the detection of sulfonamide antibiotics emerging as a research hotspot in environmental monitoring. Herein, we present a method for detecting sulfadiazine based on a silicon quantum dots (SiQDs)‐based fluorescent molecularly imprinted sensor. SiQDs, synthesized using an aqueous phase method, exhibit remarkable fluorescent properties, such as a broad excitation spectrum, tunable emission wavelengths, and high fluorescence stability, offering significant advantages in pharmaceutical detection. By integrating amino‐functionalized silica nanospheres (NH 2 ‐SiO 2 ) and tetraethyl orthosilicate, SiQDs were surface‐functionalized to construct SiQDs@NH 2 ‐SiO 2 @MIPs composite materials. The modified fluorescent molecularly imprinted polymers not only exhibited high selectivity and affinity for the target molecule SDZ, but also demonstrated excellent stability and resistance to interference in complex environments. Experimental results revealed that the sensor displayed a strong linear correlation within the concentration range of 40–100 μmol·L −1 , with a detection limit of 0.036 ng·mL −1 , demonstrating high sensitivity and excellent selectivity. In real sample applications, the recovery rate ranged from 97.88% to 100.74%, with a relative standard deviation of less than 5.37%. These findings emphasize the wide potential applications of this sensor, especially in water quality monitoring, environmental protection, and pharmaceutical detection.

Polymers for Advanced TechnologiesVol. 36(2)
Jiangsu University (CN), Changzhou Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 16%
Biosensors and Analytical Detection
2.02
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