The complex nature of laser-material interaction causes non-stoichiometric ablation of alloy samples.This is attributed to matrix effect, which reduces analyzing capability. To address this issue, the analytical perfo...The complex nature of laser-material interaction causes non-stoichiometric ablation of alloy samples.This is attributed to matrix effect, which reduces analyzing capability. To address this issue, the analytical performance of three different normalization methods, namely normalization with background, internal normalization and three point smoothing techniques at different parameter settings is studied for quantification of Ag and Zn by Laser induced breakdown spectroscopy(LIBS).The LIBS spectra of five known concentration of silver zinc binary composites have been investigated at various laser irradiances(LIs). Calibration curves for both Ag(I) line(4d^(10)5s^2S_(1/2)→4d^(10)5p^2P_(1/2) at 338.28 nm) and Zn(I) line(4s5s^3S_1→4s4p^3P_2 at 481.053 nm) have been determined at LI of 5.86?×?10^(10)W cm^(-2). Slopes of these calibration curves provide the valuation of matrix effect in the Ag–Zn composites. With careful sample preparation and normalization after smoothing at optimum parameter setting(OPS), the minimization of sample matrix effect has been successfully achieved. A good linearity has been obtained in Ag and Zn calibration curve at OPS when normalized the whole area of spectrum after smoothing and the obtained coefficients of determination values were R^2?=?0.995 and 0.998 closer to 1. The results of matrix effect have been further verified by analysis of plasma parameters. Both plasma parameters showed no change with varying concentration at OPS. However, at high concentration of Ag, the observed significant changes in both plasma parameters at common parameter setting PS-1 and PS-2 were the gesture of matrix effect. In our case, the better analytical results were obtained at smoothing function with optimized parameter setting that indicates it is more efficient than normalization with background and internal normalization method.展开更多
基金supported by National Natural Science Foundation of China (Nos. 11475039, 11705020, 11605023)Liaoning Provincial Natural Science Foundation of China (No. 20170540153)
文摘The complex nature of laser-material interaction causes non-stoichiometric ablation of alloy samples.This is attributed to matrix effect, which reduces analyzing capability. To address this issue, the analytical performance of three different normalization methods, namely normalization with background, internal normalization and three point smoothing techniques at different parameter settings is studied for quantification of Ag and Zn by Laser induced breakdown spectroscopy(LIBS).The LIBS spectra of five known concentration of silver zinc binary composites have been investigated at various laser irradiances(LIs). Calibration curves for both Ag(I) line(4d^(10)5s^2S_(1/2)→4d^(10)5p^2P_(1/2) at 338.28 nm) and Zn(I) line(4s5s^3S_1→4s4p^3P_2 at 481.053 nm) have been determined at LI of 5.86?×?10^(10)W cm^(-2). Slopes of these calibration curves provide the valuation of matrix effect in the Ag–Zn composites. With careful sample preparation and normalization after smoothing at optimum parameter setting(OPS), the minimization of sample matrix effect has been successfully achieved. A good linearity has been obtained in Ag and Zn calibration curve at OPS when normalized the whole area of spectrum after smoothing and the obtained coefficients of determination values were R^2?=?0.995 and 0.998 closer to 1. The results of matrix effect have been further verified by analysis of plasma parameters. Both plasma parameters showed no change with varying concentration at OPS. However, at high concentration of Ag, the observed significant changes in both plasma parameters at common parameter setting PS-1 and PS-2 were the gesture of matrix effect. In our case, the better analytical results were obtained at smoothing function with optimized parameter setting that indicates it is more efficient than normalization with background and internal normalization method.
基金supported by the Hunan Provincial Natural Science Foundation,China(No.2023JJ40626)Science and Technology Innovation Program of Hunan Province,China(No.2020RC2080)the National Natural Science Foundation of China(No.51971190)。
