Almaviva Salvatore, Chirico Roberto, Nuvoli Marcello, Palucci Antonio, Schnürer Frank, Schweikert Wenka
ENEA, Diagnostics and Metrology Laboratory, UTAPRAD-DIM, Via E. Fermi 45, 00044 Frascati, Italy.
Fraunhofer Institute for Chemical Technology, ICT, Joseph-von-Fraunhofer Strasse 7, Pfinztal 76327, Germany.
Talanta. 2015 Nov 1;144:420-6. doi: 10.1016/j.talanta.2015.06.075. Epub 2015 Jun 30.
We report the results of proximal Raman investigations at a distance of 7 m, to detect traces of explosives (from 0.1 to 0.8 mg/cm(2)) on common clothes with a new eye-safe apparatus. The instrument excites the target with a single laser shot of few ns (10(-9)s) in the UV range (laser wavelength 266 nm) detecting energetic materials like Pentaerythritol tetranitrate (PETN), Trinitrotoluene (TNT), Urea Nitrate (UN) and Ammonium Nitrate (AN). Samples were prepared using a piezoelectric-controlled plotter device to realize well-calibrated amounts of explosives on several cm(2). Common fabrics and tissues such as polyester, polyamide and leather were used as substrates, representative of base-materials used in the production of jackets or coats. Other samples were prepared by touching the substrate with a silicon finger contaminated with explosives, to simulate a spot left by contaminated hands on a jacket or bag during the preparation of an improvised explosive device (IED) by a terrorist. The observed Raman signals showed some peculiar molecular bands of the analyzed compounds, allowing us to identify and discriminate them with high sensitivity and selectivity, also in presence of the interfering signal from the underlying fabric. A dedicated algorithm was developed to remove noise and fluorescence background from the single laser shot spectra and an automatic spectral recognition procedure was also implemented, evaluating the intensity of the characteristic Raman bands of each explosive and allowing their automatic classification. Principal component analysis (PCA) was used to show the discrimination potentialities of the apparatus on different sets of explosives and to highlight possible criticalities in the detection. Receiver operating characteristic (ROC) curves were used to discuss and quantify the sensitivity and the selectivity of the proposed recognition procedure. To our knowledge the developed device is at the highest sensitivity nowadays achievable in the field of eye-safe, Raman devices for proximal detection.
我们报告了使用一种新型人眼安全设备在7米距离处进行近端拉曼研究的结果,以检测普通衣物上的爆炸物痕迹(0.1至0.8毫克/平方厘米)。该仪器在紫外波段(激光波长266纳米)用单个几纳秒(10⁻⁹秒)的激光脉冲激发目标,检测季戊四醇四硝酸酯(PETN)、三硝基甲苯(TNT)、硝酸脲(UN)和硝酸铵(AN)等含能材料。使用压电控制绘图仪设备制备样品,以在几平方厘米上实现校准良好的爆炸物量。聚酯、聚酰胺和皮革等普通织物和组织用作基材,代表夹克或外套生产中使用的基础材料。其他样品通过用被爆炸物污染的硅手指触摸基材来制备,以模拟恐怖分子制造简易爆炸装置(IED)时被污染的手在夹克或袋子上留下的痕迹。观察到的拉曼信号显示了所分析化合物的一些独特分子带,使我们能够在存在来自下层织物的干扰信号的情况下,以高灵敏度和选择性识别和区分它们。开发了一种专用算法以从单个激光脉冲光谱中去除噪声和荧光背景,还实施了自动光谱识别程序,评估每种爆炸物特征拉曼带的强度并实现其自动分类。主成分分析(PCA)用于展示该仪器对不同爆炸物组的区分潜力,并突出检测中可能存在的关键问题。使用接收者操作特征(ROC)曲线来讨论和量化所提出识别程序的灵敏度和选择性。据我们所知,在人眼安全的近端检测拉曼设备领域,所开发的设备目前具有最高的灵敏度。