2012 ©
             Publication
Journal Publication
Title of Article An effective strategy for the detection of tetracycline by N,S-doped carbon nanodots after preconcentration with a hybrid functional nanocomposite 
Date of Acceptance 26 September 2022 
Journal
     Title of Journal Microchemical Journal 
     Standard ISI 
     Institute of Journal Elsevier 
     ISBN/ISSN  
     Volume 2022 
     Issue 183 
     Month December
     Year of Publication 2022 
     Page 108025 
     Abstract Contamination with the antibiotic tetracycline (TC) used in animal husbandry is a serious problem in the food safety and environmental pollution fields and may cause severe diseases in humans. An effective strategy for detecting tetracycline at trace levels is therefore needed. Here, a combination of two effective strategies for enhancing the analytical performance of tetracycline detection, namely, a sensitive fluorescence method after a preconcentration step, was developed. Ultratrace tetracycline contamination was extracted with a hybrid functional nanocomposite of magnetic nanoparticles coated with a mixed metal hydroxide (MNPs@MMH), which were separated using a permanent magnet and transferred to a small volume of the eluting solution. Through the inner filter effect (IFE), the concentration of eluted tetracycline was effectively correlated with the decrease in emission intensity of the fluorescent probes (N,S-doped carbon nanodots; N,S-CDs). Under the optimal conditions, the detection range for tetracycline was 0.80 to 10 µM. The detection limit for TC sensing was 0.16 µM. This reported method was used to successfully detect tetracycline contamination in milk and water samples from an animal husbandry farm. 
     Keyword Fluorescent sensors, chemical sensors, inner filter effect, sample preparation, food safety, carbon nanodots, green extraction  
Author
607020035-3 Miss PRADTHANA SIANGLAM [Main Author]
Science Doctoral Degree

Reviewing Status มีผู้ประเมินอิสระ 
Status ตีพิมพ์แล้ว 
Level of Publication นานาชาติ 
citation false 
Part of thesis true 
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