Au-Ag Core-Shell Nanospheres for Surface-Enhanced Raman Scattering Detection of Sudan I and Sudan II in Chili Powder

Au-Ag core-shell (Au@Ag) bimetallic nanospheres synthesized by a facile seed-growth method are proposed as a substrate for surface-enhanced Raman spectroscopy (SERS) to detect azo-group dyes including Sudan I and Sudan II. Au@Ag nanospheres with a series of particle sizes (diameter: 30–120 nm) and s...

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Bibliographic Details
Published in:Journal of nanomaterials 2015-01, Vol.2015 (2015), p.1-8
Main Authors: Huang, Yiqun, Fan, Yuxia, Yu, Wansong, Ou, Yiming, Pei, Lu, Lai, Keqiang
Format: Article
Language:English
Subjects:
Aqueous solutions
Bans
Chromatography
Food
Foods
Infrared
Methods
Nanomaterials
Nanospheres
Optical properties
Particle size
Principal components analysis
Raman scattering
Raman spectroscopy
Silver
Spectrum analysis
Studies
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Summary:Au-Ag core-shell (Au@Ag) bimetallic nanospheres synthesized by a facile seed-growth method are proposed as a substrate for surface-enhanced Raman spectroscopy (SERS) to detect azo-group dyes including Sudan I and Sudan II. Au@Ag nanospheres with a series of particle sizes (diameter: 30–120 nm) and silver shell thicknesses (6–51 nm) were synthesized and compared for their morphological and optical properties to obtain optimum enhancement effect. Normal Raman, SERS, infrared, and ultraviolet-visible were used to investigate the optical absorption properties of Sudan I and Sudan II as well as the enhancement mechanism of Au@Ag substrates. The nanospheres with particle size of 73 ± 6 nm in diameter and silver layer of 27 ± 2 nm resulted in the highest enhancement effect and could be used to detect Sudan I and Sudan II standard solutions at levels as low as 0.4 and 0.1 mg/L, respectively. Moreover, Sudan I and Sudan II in chili powder could be detected at 0.6 and 0.4 mg/kg, respectively. Sudan I and Sudan II with similar structures in complicated food matrices could be distinguished through applying principal component analysis, indicating good selectivity of the SERS method for detection of banned additives in food stuffs at trace levels.
ISSN:1687-4110
1687-4129
DOI:10.1155/2015/430925