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土壤中铜的单脉冲LIBS定标方法研究 被引量:3

Research on the Method of Calibration of Cu in Soil by Single Pulse Laser-Induced Breakdown Spectroscopy
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摘要 定标法对激光诱导击穿光谱(LIBS)技术的定量分析精度有着重要影响。在利用激光诱导击穿光谱技术探测土壤样品中铜元素的过程中,采用外标法与不同的内标法定标曲线对土壤样品中的铜元素进行了定量分析。在以ca作为内标元素的分析中,通过Voigt拟合对分析谱线与内标元素谱线轮廓进行预处理,提取光谱净强度值,然后根据分析线与内标线净强度之比建立定标曲线,所得的线性系数为0.998,通过循环反演得到的平均相对偏差为2.28%且相对偏差波动很小,具有不错的稳定性。以Cu324.754nm的峰值强度与谱图在323~326nm处的面积之比建立定标曲线,得到定标曲线的线性系数为0.997,通过循环反演得到的平均相对偏差为2.23%,稳定性略低于前一种内标法。采用外标法直接用样品中Cu浓度与Cu324.754nm处峰值强度建立的定标曲线的线性系数为0.972,通过循环反演得到的平均相对偏差为13%且波动较大,可靠性较差。 Calibration method has an important impact on the accuracy of quantitative analysis of laser-induced breakdown spectroscopy (LIBS). In the process of using LIBS to detect copper in soil samples, different calibration curves are used in order to do quantitative analysis, including exterior standard method and different internal standard methods. Using Voigt fitting function to the spectral line at Cu 324. 754 nm and Ca 317.9 nm to obtain the net intensity values, the net intensity ratio between Cu and Ca is then sought as internal standard to get calibration curve, which has the correlation coefficient up to 0. 998. Through the cyclic inversion, the average relative error is 2.28% and the volatility is very small, so this method has good stability. Using the ratio between the spectra line intensity of Cu 324. 754 nm and the area from 323 nm to 326 nm to establish the calibration curve, the correlation coefficient is 0. 997 and the average relative error by cyclic inversion is 2.23%, but the stability is slightly lower than the former one. Directly using the Cu concentration and spectra line intensity to establish the calibration curve, the correlation coefficient is 0. 972 and the average relative error by cyclic inversion is 13%, showing large fluctuations and less reliability.
出处 《激光与光电子学进展》 CSCD 北大核心 2013年第12期214-220,共7页 Laser & Optoelectronics Progress
基金 国家863计划(2009AA063002) 四川省科技支撑计划(2011GZ0249)
关键词 光谱学 激光诱导击穿光谱 拟合度 相对偏差 定标曲线 循环反演 spectroscopy laser-induced breakdown spectrascopy fitting degree relative deviation calibrationcurve cyclic inversion
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