Fabrication of surface-enhanced Raman scattering sensors to detect antibiotic residues in muscle foods using gold nanoparticles
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 94
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شناسه ملی سند علمی:
JR_JOPN-8-3_003
تاریخ نمایه سازی: 25 بهمن 1402
چکیده مقاله:
The surface-enhanced Raman scattering (SERS) method is a widely used technique for molecular structure analysis. This method relies on the enhancement of the Raman signal through the use of plasmonic nanostructures, such as gold and silver, which serve as substrate sensors. The use of pre-made sensors can effectively enhance the efficiency and cost-effectiveness of SERS. In this study, we used a fast, simple, and cost-effective method to create a suitable substrate for SERS analysis. Initially, gold colloidal nanoparticles with dimensions ranging from ۵۰ to ۸۰ nm were synthesized and deposited onto glass slides to create a uniform and rough substrate. To stabilize the gold nanoparticles, a sulfur compound called "۱-dodecanethiol" was selected, increasing the contact angle of the sample to ۴۵° on the glass slide. Florfenicol, one of the most common antibiotic residues in muscle foods, was selected as an analyte. Spectrum acquisitions at various points on a single slide demonstrated acceptable substrate uniformity (RSD = ۸.۴۴%). Further experiments conducted on different slides confirmed the consistency of the results (RSD = ۷.۹۰%). Finally, the reliability of the results was confirmed through spectrum acquisitions over various time intervals (RSD = ۱.۲۶%).
کلیدواژه ها:
نویسندگان
Mehran Behvarmanesh
Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran
Gholamhasan Asadi
Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran
Rasoul Malekfar
Department of Physics, Faculty of Basic Sciences, Tarbiat Modares University, Tehran, Iran
Seyed Masoud Etezad
Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran
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