A Novel LIBS Sensor for Sample Examinations on a Crime Scene.

In this work, we present a compact LIBS sensor developed for characterization of samples on a crime scene following requirements of law enforcement agencies involved in the project. The sensor operates both in a tabletop mode, for aside measurements of swabbed materials or taken fragments, and in handheld mode where the sensor head is pointed directly on targets at the scene. The sensor head is connected via an umbilical to an instrument box that could be battery-powered and contains also a color camera for sample visualization, illumination LEDs, and pointing system for placing the target in focus. Here we describe the sensor's architecture and functionalities, the optimization of the acquisition parameters, and the results of some LIBS measurements. On nano-plotted traces at silica wafer and in optimized conditions, for most of the elements the detection limits, in term of the absolute element masses, were found to be below 10 picograms. We also show results obtained on some representative materials, like fingerprints, swabbed soil and gunshot residue, varnishes on metal, and coated plastics. The last, solid samples were used to evaluate the depth profiling capabilities of the instrument, where the recognition of all four car paint layers was achieved.

Proximal Detection of Traces of Energetic Materials with an Eye-Safe UV Raman Prototype Developed for Civil Applications.

A new Raman-based apparatus for proximal detection of energetic materials on people, was developed and tested for the first time. All the optical and optoelectronics components of the apparatus, as well as their optical matching, were carefully chosen and designed to respect international eye-safety regulations. In this way, the apparatus is suitable for civil applications on people in public areas such as airports and metro or railway stations. The acquisition software performs the data analysis in real-time to provide a fast response to the operator. Moreover, it allows for deployment of the apparatus either as a stand alone device or as part of a more sophisticated warning system architecture made up of several sensors. Using polyamide as substrate, the apparatus was able to detect surface densities of ammonium nitrate (AN), 2-methyl-1,3,5-trinitrobenzene (TNT), 3-nitrooxy-2,2-bis(nitrooxymethyl)propyl] nitrate (PETN) and urea nitrate (UN) in the range of 100-1000 µg/cm² at a distance of 6.4 m using each time a single laser pulse of 3 mJ/cm². The limit of detection calculated for AN is 289 µg/cm². AN and UN provided the highest percentages of true positives (>82% for surface densities of 100-400 µg/cm² and fingerprints) followed by TNT and PETN (17%-70% for surface densities of 400-1000 µg/cm² and fingerprints).

A new eye-safe UV Raman spectrometer for the remote detection of energetic materials in fingerprint concentrations: Characterization by PCA and ROC analyzes.

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.