Methods for rapid identification of explosives and their associated compounds at trace level quantities are needed for security screening applications. In this paper, we apply the surface-enhanced Raman spectroscopy (SERS) to detect and identify traces (as low as tens of pg) of pentaerythritol tetranitrate (PETN), ethylene glycol dinitrate (EGDN), cyclotrimethylene- trinitramine (RDX) and trinitrotoluene (TNT) using commercially available substrates (Klarite®, Renishaw diagnostics). High quality spectra were achieved within 10 s with a compact Raman spectrometer. Principal component analysis (PCA) of the data was performed to understand what factors affected the spectral variation across the samples. It was found that 76% of the spectral variation was explained by the first three PCs. Score plots for these components showed that the energetic materials can be clearly classified on the basis of SERS spectra also at trace level quantity. Our measurements further demonstrate the potential for using SERS as fast, in situ analytical tool for safety devices, with a sensitivity which competes and, in some cases, overcomes other techniques. Copyright © 2013 John Wiley & Sons, Ltd.
Trace level detection and identification of nitro-based explosives by surface-enhanced Raman spectroscopy
Rufoloni, A.;Puiu, A.;Palucci, A.;Cantarini, L.;Almaviva, S.;Botti, S.
2013-01-01
Abstract
Methods for rapid identification of explosives and their associated compounds at trace level quantities are needed for security screening applications. In this paper, we apply the surface-enhanced Raman spectroscopy (SERS) to detect and identify traces (as low as tens of pg) of pentaerythritol tetranitrate (PETN), ethylene glycol dinitrate (EGDN), cyclotrimethylene- trinitramine (RDX) and trinitrotoluene (TNT) using commercially available substrates (Klarite®, Renishaw diagnostics). High quality spectra were achieved within 10 s with a compact Raman spectrometer. Principal component analysis (PCA) of the data was performed to understand what factors affected the spectral variation across the samples. It was found that 76% of the spectral variation was explained by the first three PCs. Score plots for these components showed that the energetic materials can be clearly classified on the basis of SERS spectra also at trace level quantity. Our measurements further demonstrate the potential for using SERS as fast, in situ analytical tool for safety devices, with a sensitivity which competes and, in some cases, overcomes other techniques. Copyright © 2013 John Wiley & Sons, Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
