Open AccessThin silica shell coated Ag assembled nanostructures for expanding generality of SERS analytes
Author(s) -
Myeong Geun,
Hyungmo Kim,
Yoo-Lee Kang,
Minwoo Lee,
Homan Kang,
Jaehi Kim,
XuanHung Pham,
Tae Han Kim,
Eunil Hahm,
Jun Young Lee,
Dae Hong Jeong,
BongHyun Jun
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0178651
Subject(s) - analyte , raman scattering , detection limit , materials science , nanotechnology , discrete dipole approximation , nanoparticle , molecule , nanostructure , aniline , chemistry , raman spectroscopy , chromatography , dipole , organic chemistry , physics , optics
Surface-enhanced Raman scattering (SERS) provides a unique non-destructive spectroscopic fingerprint for chemical detection. However, intrinsic differences in affinity of analyte molecules to metal surface hinder SERS as a universal quantitative detection tool for various analyte molecules simultaneously. This must be overcome while keeping close proximity of analyte molecules to the metal surface. Moreover, assembled metal nanoparticles (NPs) structures might be beneficial for sensitive and reliable detection of chemicals than single NP structures. For this purpose, here we introduce thin silica-coated and assembled Ag NPs (SiO 2 @Ag@SiO 2 NPs) for simultaneous and quantitative detection of chemicals that have different intrinsic affinities to silver metal. These SiO 2 @Ag@SiO 2 NPs could detect each SERS peak of aniline or 4-aminothiophenol (4-ATP) from the mixture with limits of detection (LOD) of 93 ppm and 54 ppb, respectively. E-field distribution based on interparticle distance was simulated using discrete dipole approximation (DDA) calculation to gain insight into enhanced scattering of these thin silica coated Ag NP assemblies. These NPs were successfully applied to detect aniline in river water and tap water. Results suggest that SiO 2 @Ag@SiO 2 NP-based SERS detection systems can be used as a simple and universal detection tool for environment pollutants and food safety.