Abstract:A method for detecting trace impurities in high concentration matrix by ICP-AES based on partial least squares (PLS) was established. The research showed that PLS could effectively correct the interference caused by high level of matrix concentration error and could withstand higher concentrations of matrix than multicomponent spectral fitting (MSF). When the mass ratios of matrix to impurities were from 1 000∶1 to 20 000∶1, the recoveries of standard addition were between 95% and 105% by PLS. For the system in which interference effect has nonlinear correlation with the matrix concentrations, the prediction accuracy of normal PLS method was poor, but it can be improved greatly by using LIN-PPLS, which was based on matrix transformation of sample concentration. The contents of Co,Pb and Ga in stream sediment (GBW07312) were detected by MSF, PLS and LIN-PPLS respectively. The results showed that the prediction accuracy of LIN-PPLS was better than PLS, and the prediction accuracy of PLS was better than MSF.
Key words:ICP-AES;Partial least squares;High concentration;Matrix;Interference effects
王衍鹏,龚 琦*,喻盛容,刘幽燕 . ICP-AES测定高浓度基体下杂质元素的偏最小二乘法研究[J]. 光谱学与光谱分析, 2012, 32(04): 1098-1102.
WANG Yan-peng, GONG Qi*, YU Sheng-rong, LIU You-yan . Research on Partial Least Squares for Determination of Impurities in the Presence of High Concentration of Matrix by ICP-AES . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(04): 1098-1102.
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