Classical univariate calibration and partial least squares for quantitative analysis of brass samples by laser-induced breakdown spectroscopy

In this work we compare the analytical results obtained by traditional calibration curves (CC) and multivariate Partial Least Squares (PLS) algorithm when applied to the LIBS spectra obtained from ten brass samples (nine standards of known composition and one ‘unknown’). Both major (Cu and Zn) and trace (Sn, Pb, Fe) elements in the sample matrix were analyzed. After the analysis, the composition of the ‘unknown’ sample, measured by X-ray Fluorescence (XRF) technique, was revealed. The predicted concentrations of major elements obtained by rapid PLS algorithms are in very good agreement with the nominal concentrations, as well as with those obtained by the more time-consuming CC approach. A discussion about the possible effects leading to discrepancies of the results is reported. The results of this study open encouraging perspectives towards the development of cheap LIBS instrumentation which would be capable, despite the limitations of the experimental apparatus, to perform fast and precise quantitative analysis on complex samples.