Standoff femtosecond filament-induced breakdown spectroscopy for classification of geological materials†
Abstract
Femtosecond (fs) filaments delivering substantial peak intensities at remote locations are being exploited in several practical applications together with in situ remote/standoff (ST) investigations. The optical emissions produced during the filament interaction were analyzed to study the composition of distant targets. In this article, we present the comparative results obtained from qualitative studies of territorial rocks (collected from the central Dharwar craton, South India) in the near-field and in the standoff mode with fs laser induced breakdown spectroscopy (fs LIBS) and fs filament induced breakdown spectroscopy (fs FIBS) techniques. The granitoids possessing distinct mineralogical and chemical characteristics were analyzed in their original form in ambient air from a distance of (i) ∼15 cm with tightly focused fs pulses in near-field configuration and (ii) ∼6.5 m using fs filaments in standoff configuration. Various atomic emission lines belonging to major elements such as Ca, K, Na, Al, Fe and Mg were identified and labelled from both fs LIBS and fs FIBS spectra of each sample. Few spectral lines corresponding to trace elements such as Ba, Ti and V were also identified. Furthermore, Mg/Ca, Fe/Ca, Mg/Al, Ca/Al, Mg/Si and Fe/Si ratios were considered to highlight the differences that could serve for the classification of these granitoids. A good correlation of constituent element spectral line intensities, especially in the standoff mode, was observed with weight percentage of their oxides obtained from X-ray fluorescence (XRF) data. The overall change in relative standard deviation (RSD%) of major spectral intensities for a sample was observed to be lower (5–25%) in the standoff case in comparison to that of the near-field configuration (16–38%). Furthermore, the results from the principal component analysis (PCA) employed in tandem with normalized/unnormalized fs ST-FIBS data of these geological rock samples demonstrated a high degree of qualitative classification in comparison to normalized/unnormalized fs LIBS data. Therefore, we firmly believe that the results from the present work clearly extend the application of fs filaments to standoff analysis of geological beds and mineral ores under the ambient atmospheric conditions intended for unpleasant environment detection.