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Study on EDXRF Method of Turquoise Composition |
LIU Ling1, YANG Ming-xing1, 2*, LU Ren1, Andy Shen1, HE Chong2 |
1. Gemmological Institue, China University of Geoscience, Wuhan 430074,China
2. Gem Testing Center, China University of Geoscience, Wuhan 430074,China |
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Abstract LA-ICP-MS was used to calibrate 26 turquoise samples with relatively clean and uniform color on each surface. We selected 9 points on each sample to test the homogeneity of their chemical composition. The results showed that the average error coefficients of Al, P, K, Cu, Fe, V, Cr and Zn in turquoise samples are below 5.4%, while the average error coefficients of CaO and SiO2 are 34.8% and 16.2% respectively, suggesting that the elements of Si and Ca in turquoise were heterogeneity. The turquoise working curve can be established by the energy dispersive X-ray fluorescence spectrometer (EDXRF). We used 21 samples as the standard sample for reference and 5 as unknown samples to determine the composition of turquoise. Results showed that the correlation coefficients of Al, P and Cu of the main element are between 92.3% and 94.3%, with an average relative error of 4.6%~9.7%. The correlation coefficients of Fe, Cr, Zn micro-elements are more than 0.990, while the correlation coefficients of both K and V elements are 0.939 and 0.972. And the average relative error of those five micro-elements ranges from 7.2% to 13.9%. However, the correlation coefficients of Si and Ca are 0.958 and 0.866, the average relative error of which is 348% and 27.8% in the five unknown turquoise samples. The high average relative errors of Si and Ca may be influenced by the low content and the heterogeneity of Si and Ca in turquoise, also related to the detection limit of this instrument method. The repeatability test showed that the relative standard deviations (RSDs) of Al, P, Cu, Fe, Zn elements are within 1%, suggesting that the accuracy of the test results is respectively high. While the RSDs of V, Cr, K, Ca, Si elements range from 1.34% to 10.17%. The study provides a new idea and method for determining the quantify of the elements of Al, P, Cu, Fe, Cr, Zn and V in turquoise quickly, accurately and losslessly, which can be applied to test and identify turquoise in laboratory.
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Received: 2017-06-26
Accepted: 2017-11-02
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Corresponding Authors:
YANG Ming-xing
E-mail: yangc@cug.edu.cn
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[1] SHE Ling-zhu, QIN Ying, LUO Wu-gan, et al(佘玲珠, 秦 颍, 罗武干, 等). Chinese Rare Earths (稀土), 2009,(5): 59.
[2] HE Xu, CHEN Lin, LI Qing-hui, et al(何 煦, 陈 林, 李青会, 等). Rock And Mineral Analysis(岩矿测试), 2011,(6): 709.
[3] Hull S, Fayek M, Mathien F J, et al. Journal of Archaeological Science, 2014, 45: 187.
[4] Alyson M Thibodeau, David J Killick, Sanl L Hedquist, et al. Geological Society of America Bulletin, 2015, 127(11-12): 1617.
[5] ZHOU Yan, QI Li-jian, DAI Hui, et al(周 彦, 亓利剑, 戴 慧, 等). Journal of Gems & Gemmology(宝石和宝石学杂志), 2013, 15(4): 37.
[6] CHEN Quan-li, ZHANG Yan(陈全莉, 张 琰). Journal of Gems & Gemmology(宝石和宝石学杂志), 2005, 7(4): 13.
[7] XUE Hong-qing, CHEN Pei-ran, LI Qing-hua(薛鸿庆, 陈沛然, 李清华). Journal of the Chinese Ceramic Society(硅酸盐学报), 1985, 13(2): 234.
[8] YAN Jun, LIU Xiao-bo, WANG Ju-an, et al(严 峻, 刘晓波, 王巨安, 等). Rock and Mineral Analysis(岩矿测试), 2015, 34(5): 544.
[9] SHI Zhen-rong, CAI Ke-qin(石振荣, 蔡克勤). Acta Petrologica et Mineralogica(岩石矿物学杂志), 2008, 27(2): 164.
[10] ZHANG Bei-li(张蓓莉). Syslematic Gemmology(系统宝石学). Beijing: Geological Publishing House(北京:地质出版社), 2006. 389.
[11] Liu Y, Hu Z C, Gao S, et al. Chemical Geology, 2008, 257(1-2): 34.
[12] Liu Y, Hu Z C, Zong K Q. Chinese Science Bulletin, 2010, 55(15): 1535.
[13] Eugene E Foord, Joseph E Taggart. Mineralogical Magazine, 1998, 62(1): 93.
[14] National Technical Supervision Bureau(国家技术监督局). JJF 1006—1994 Primary Standard Material Specification(JJF 1006—1994一级标准物质技术规范). Beijing: Chinese Metrology Press(北京:中国计量出版社), 1994. 12.
[15] LI Jin-hai(李金海). Error Theory and Measurement Uncertainty Evaluation(误差理论与测量不确定度评定). Beijing: Chinese Metrology Press(北京:中国计量出版社), 2003. 12. |
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