A Multivariate Nonlinear Model for Quantitative Analysis in Laser-Induced Breakdown Spectroscopy
CHEN Xing-long1, 2, FU Hong-bo2, WANG Jing-ge2, NI Zhi-bo2, HE Wen-gan2, XU Jun4, RAO Rui-zhong1, 2, DONG Feng-zhong2, 3*
1. School of Instrument Science & Opto-electronic Engineering,Hefei University of Technology,Hefei 230009,China 2. Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Hefei 230031,China 3. School of Environment Science and Optoelectronic Technology,University of Science and Technology of China,Hefei 230026, China 4. Shanghai Institute of Satellite Equipment,Shanghai 200240, China
Abstract:Most quantitative models used in laser-induced breakdown spectroscopy (LIBS) are based on the hypothesis that laser-induced plasma approaches the state of local thermal equilibrium (LTE). However, the local equilibrium is possible only at a specific time segment during the evolution. As the populations of each energy level does not follow Boltzmann distribution in non-LTE condition, those quantitative models using single spectral line would be inaccurate. A multivariate nonlinear model, in which the LTE is not required, was proposed in this article to reduce the signal fluctuation and improve the accuracy of quantitative analysis. This multivariate nonlinear model was compared with the internal calibration model which is based on the LTE condition. The content of Mn in steel samples was determined by using the two models, respectively. A minor error and a minor relative standard deviation (RSD) were observed in multivariate nonlinear model. This result demonstrates that multivariate nonlinear model can improve measurement accuracy and repeatability.
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