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Quantification of Mn in glass matrices using laser induced breakdown spectroscopy (LIBS) combined with chemometric approaches

机译:使用激光诱导击穿光谱(Libs)与化学计量方法相结合的玻璃基质中Mn的定量

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A Q-switched solid state Nd:YAG laser operating at a third harmonic (355 nm) wavelength and an echelle spectrograph coupled with an ICCD system were used to study the plasma on a glass target. The present work is mainly focused on the investigation of multivariate calibration methods like principal component regression (PCR) and partial least squares regression (PLSR) for the analysis of Mn in complex matrices like glass. The glass studied has Mn as an analyte of interest whose doping concentration in the matrix varies from 0.77% to 11.61%. The performance of univariate and multivariate methods has been presented in this paper through their figures of merit. Improved prediction accuracy, limit of detection (LOD) and regression coefficients (R2) have been reported when the data were analyzed using PCR and PLSR. The calibration curves of six emission lines of Mn have been analyzed using a univariate method that resulted in R2 values varying from 0.85 to 0.98. This method resulted in a correlation uncertainty of 10% and a LOD of 0.20 wt%. R2 values of 0.98 to 0.99 have been obtained for the multivariate calibration curves of Mn analyzed in three selected regions of the LIBS spectrum. The optimum LOD and root mean square error of prediction (RMSEP) using PCR and PLSR were found to be 0.02 wt% and 0.54 wt%, respectively. The significant improvement in the analytical performances of multivariate calibration methods for the investigation of LIBS data is evident from the aforementioned results. Finally, the results of PCR and PLSR were confirmed by PCA classification.
机译:在第三次谐波(355nm)波长下操作的Q开关固态Nd:YAG激光器和与ICCD系统耦合的呼应光谱仪用于研究玻璃靶标的等离子体。目前的作品主要集中在诸如主要成分回归(PCR)等中的多变量校准方法的研究,以便在玻璃中的复杂基质中分析Mn的分析。研究的玻璃具有Mn作为兴趣的分析物,其掺杂浓度在基质中的浓度为0.77%至11.61%。本文通过其优异数据提出了单变量和多变量方法的表现。当使用PCR和PLSR分析数据时,已经报告了改进的预测精度,检测极限(LOD)和回归系数(R2)。使用单变量的方法分析了Mn的六条发射线的校准曲线,该方法导致R2值从0.85到0.98变化。该方法导致相关不确定度为10%,距离为0.20wt%。已经获得了在LIBS谱的三个选定区域分析的MN的多元校准曲线的0.98至0.99的R2值。使用PCR和PLSR预测(RMSEP)的最佳LOD和均方格误差分别为0.02wt%和0.54wt%。从上述结果明显看出,对Libs数据进行调查的多元校准方法的分析性能的显着改善是明显的。最后,通过PCA分类证实了PCR和PLSR的结果。

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