以线扫描进行激光剥蚀进样，采用激光剥蚀-电感耦合等离子体质谱(LA-ICP-MS)定量分析不锈钢中主、次和痕量元素。考察了激光剥蚀池载气及流量、激光脉冲频率、激光剥蚀孔径、激光输出能量密度对分析性能的影响，对激光剥蚀参数进行了优化。以基体57Fe为内标，校正了元素分馏和灵敏度漂移：以湿法分析用不锈钢屑状标准物质通过环氧树脂等固化剂镶嵌成集合式标准物质作为校准样品，建立了校准曲线。结果表明，除P和Pb校准曲线的线性相关系数分别为0.9782和0.9679外，其他各待测元素均达到0.99以上：各元素的检出限为0.02~39.71μg/g。将方法应用于不锈钢标准样品分析，测定值与认定值吻合，除样品BSCA316-4中Al和Pb外，其它各元素测定值的相对标准偏差(RSD，n=5)在10%以内，而Pb元素的含量本身较低，因此其RSD为10.3%也满足要求。
Abstract
Linear scanning mode ablation was used as sampling strategy, and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used for quantitative determination of major, minor and trace elements in stainless steels. The effect of carrier gas in laser ablation cell and its flow, the frequency of laser pulse, the aperture of laser ablation and the output energy density of laser on analytical properties were investigated. The parameters of laser ablation were optimized. The matrix 57Fe was used as internal standard to correct the elemental fractionation and sensitivity drifting. The stainless steel crumb certified reference materials for wet analysis were embedded in curing agent such as epoxy resin to prepare assemble-type reference sample as calibration samples. Accordingly, the calibration curve was established. The results showed that, except for P and Pb whose linear correlation coefficient of calibration curve was 0.978 2 and 0.967 9 respectively, the correlation coefficients of other elements were all higher than 0.99. Detection limit of elements was 0.02-39.71 μg/g. The proposed method was applied to the determination of stainless steel certified reference materials, and the results were consistent with the certified values. Except for Al and Pb in sample BS CA 316-4, the relative standard deviations (RSD, n=5) of elements were all less than 10%. Considering the low content of P, its RSD of 10.3% could meet the requirements.
关键词
激光剥蚀-电感耦合等离子体质谱法 /
不锈钢 /
内标校正 /
主、次和痕量元素
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Key words
laser ablation inductively coupled plasma mass spectrometry /
stainless steel /
internal standard correction /
major, minor and trace elements
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中图分类号：
O657.63
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参考文献
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脚注
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基金
科技部创新方法专项支持(2009IM032400)
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