Fabrication of surface-enhanced Raman scattering sensors to detect antibiotic residues in muscle foods using gold nanoparticles

Subject Areas : Journal of Optoelectronical Nanostructures

Mehran Behvarmanesh ¹ , Gholamhasan Asadi ² , Rasoul Malekfar ³ , Seyed Masoud Etezad ⁴

1 - Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - Department of Physics, Faculty of Basic Sciences, Tarbiat Modares University, Tehran, Iran
4 - Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran

Received: 2023-04-15 Accepted : 2023-09-01 Published : 2023-11-01

Keywords: Gold Nanoparticles, Surface-enhanced Raman scattering, SERS sensors, Raman substrates, antibiotic residues,

Abstract :

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 50 to 80 nm were synthesized and deposited onto glass slides to create a uniform and rough substrate. To stabilize the gold nanoparticles, a sulfur compound called "1-dodecanethiol" was selected, increasing the contact angle of the sample to 45° 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 = 8.44%). Further experiments conducted on different slides confirmed the consistency of the results (RSD = 7.90%). Finally, the reliability of the results was confirmed through spectrum acquisitions over various time intervals (RSD = 1.26%).

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