Improving data stability and prediction accuracy in laser-induced breakdown spectroscopy by utilizing a combined atomic and ionic line algorithm

Abstract

Improving data quality is important for accurate quantitative analysis in laser-induced breakdown spectroscopy for time and spatial integrated spectra. Based on the characteristics of atomic and ionic lines under various plasma conditions, an algorithm is proposed to reduce the signal fluctuation by combining an atomic line and an ionic line of an element. Using 29 brass alloy samples, the algorithm is verified by comparing the relative standard deviations of the intensities of two copper lines, Cu(I) 406.264 nm and Cu(II) 217.941 nm, to that of their combined intensity. The noticeable improvement suggests that the proposed algorithm can overcome the signal fluctuation caused by the varying plasma temperature and electron density. Furthermore, using the conventional linear calibration method, the relative standard deviation is reduced from 2.93% (Cu(I) 406.264 nm) and 2.13% (Cu(II) 217.941 nm) to 1.68% (combined intensity), and the root mean square error of prediction is significantly reduced from 2.24% (Cu(I) 406.264 nm) and 2.43% (Cu(II) 217.941 nm) to 1.40% (combined intensity).