Issue 13, 2015

Silver nanoparticle aggregates on metal fibers for solid phase microextraction–surface enhanced Raman spectroscopy detection of polycyclic aromatic hydrocarbons

Abstract

Solid phase microextraction (SPME), a solvent free technique for sample preparation, has been successfully coupled with GC, GC-MS, and HPLC for environmental analysis. In this work, a method combining solid phase microextraction with surface enhanced Raman spectroscopy (SERS) is developed for detection of polycyclic aromatic hydrocarbons (PAHs). Silver nanoparticle aggregates were deposited on the Ag–Cu fibers via layer-by-layer deposition, which were modified with propanethiol (PTH). The SERS-active SPME fiber was immersed in water directly to extract PAHs and then detected using a portable Raman spectrometer. The pronounced valence vibration of the C–C bond at 1030 cm−1 was chosen as an internal standard peak for the constant concentration of PTH. The RSD values of the stability and the uniformity of the SERS-active SPME fiber are 2.97% and 5.66%, respectively. A log–log plot of the normalized SERS intensity versus fluoranthene concentration showed a linear relationship (R2 = 0.95). The detection limit was 7.56 × 10−10 M and the recovery rate of water samples was in the range of 95% to 115%. The method can also be applied to detection of PAH mixtures, and each component of the mixtures can be distinguished by Raman characteristic peaks. The SERS-active SPME fiber could be further confirmed by GC-MS.

Graphical abstract: Silver nanoparticle aggregates on metal fibers for solid phase microextraction–surface enhanced Raman spectroscopy detection of polycyclic aromatic hydrocarbons

Supplementary files

Article information

Article type
Paper
Submitted
25 Mar 2015
Accepted
06 May 2015
First published
07 May 2015

Analyst, 2015,140, 4668-4675

Silver nanoparticle aggregates on metal fibers for solid phase microextraction–surface enhanced Raman spectroscopy detection of polycyclic aromatic hydrocarbons

C. Liu, X. Zhang, L. Li, J. Cui, Y. Shi, L. Wang and J. Zhan, Analyst, 2015, 140, 4668 DOI: 10.1039/C5AN00590F

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