ABSTRACT
Nanosecond laser-induced breakdown spectroscopy has been examined for the analysis of suspended matter in a free stream of air. The real-time monitoring of this scenario poses major challenges for an accurate categorization due to its changing characteristics such as composition, size, and density of particles. The effects of particle size and matrix in the optical emission responses registered from such scenarios have been evaluated. Distant (10 m) plasmas of saline solutions, containing either NaCl or Na2SO4 at different concentrations, have been induced by nanosecond laser pulses at a wavelength of 1064 nm. The effects of the droplet size and its concentration on differences in the laser-induced breakdown probability, the intensity of the characteristic lines, and the plasma emission continuum have been discussed. The quantification of sodium in distant water droplets has been proved. However, an initial knowledge on the average droplet size is required. The average droplet size could be determined from the slope of H I and O I lines versus the continuum plasma emission, which is only weakly influenced by the salt content in the droplets.
ABSTRACT
Data fusion is the process of combining data gathered from two or more sensors to produce a more specific, comprehensive and unified dataset of the inspected target. On this basis, much has been said about the possible benefits resulting from the use of molecular and atomic information for the detection of explosives. The orthogonal nature of the spectral and compositional information provided by Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) makes them suitable candidates for an optimal combination of their data, thus achieving inferences that are not feasible using a single sensor. The present manuscript evaluates several architectures for the combination of spectral outputs from these two sensors in order to compare the benefits and drawbacks of data fusion for improving the overall identification performance. From the simple assembling (concatenation or addition) of Raman and LIBS spectra to signals' processing on the basis of linear algebra (either the outer product or the outer sum), different identification patterns of several compounds (explosives, potential confusants and supports) have been built. The efficiency on target differentiation by using each of the architectures has been evaluated by comparing the identification yield obtained for all the inspected targets from correlation and similarity measurements. Additionally, a specific code integrated by several of these patterns to identify each compound has also been evaluated. This approach permits to obtain a better knowledge about the identity of an interrogated target, mainly in those decisive cases in which LIBS or Raman cannot be effective separately to reach a decision.
