Determination of diamond knife head composition by X-ray fluorescence spectrometry based on analysis software without standard sample
MA Chengxin1,2, SHI Xiaohua3, DING Youming1,2
1. Hubei Institute of Quality Supervision and Inspection Ezhou Branch, Ezhou 436000, China; 2. National Center for Quality Supervision and Inspection of Diamond Tools,Ezhou 436000, China; 3. Hubei Special Equipment Inspection Institute Ezhou Branch, Ezhou 436000, China
Abstract：The composition analysis of diamond knife head is of great significance for improving the production formula and enhancing the cutting efficiency and cutting life of diamond knife head. For different cutting objects, the diamond knife head with different properties is required, which leads to complex and changeable composition of diamond knife head. Moreover, due to the lack of standard samples, there are only few researches and reports. The skeleton elements (Fe, Cu, Zn and Sn) in diamond knife head were detected using the semiquantitative software without standard sample of X-ray fluorescence spectrometry (XRF). It solved the problems in conventional chemical methods such as time consuming, many steps and environmental pollution, and improved the detection efficiency. The function of boric acid tablets, error source analysis, spectral overlapping and and matrix effect correction were discussed. The precision experiments showed that the relative standard deviation (RSD) for Fe, Cu, Zn and Sn was 0.29%, 0.71%, 1.8% and 6.5%, respectively. The accuracy experiments showed that the semiquantitative results by proposed method were basically consistent with those obtained by traditional standard methods, which could meet the use requirements. The proposed method was applied for the rapid, accurate and simultaneous determination of multi-components in diamond knife head. The semi-quantitative results reached the degree of approximate quantification.
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MA Chengxin, SHI Xiaohua, DING Youming. Determination of diamond knife head composition by X-ray fluorescence spectrometry based on analysis software without standard sample. , 2021, 41(2): 30-33.
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