光谱学与光谱分析 |
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Determination of Chloride Salt Solution by NIR Spectroscopy |
ZHANG Bin, CHEN Jian-hong*, JIAO Ming-xing |
Faculty of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China |
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Abstract Determination of chloride salt solution by near infrared spectrum plays a very important role in Biomedicine. The near infrared spectrum analysis of Sodium chloride, potassium chloride, calcium chloride aqueous solution shows that the concentration change of chloride salt can affect hydrogen bond, resulting in the variation of near infrared spectrum of water. The temperature influence on NIR spectrum has been decreased by choosing reasonable wavelength range and the wavelength where the temperature effects are zero (isosbestic point). Chlorine salt prediction model was established based on partial least squares method and used for predicting the concentration of the chlorine ion. The impact on near infrared spectrum of the cation ionic radius, the number of ionic charge, the complex effect of ionic in water has also discussed in this article and the reason of every factor are analysed. Experimental results show that the temperature and concentration will affect the near-infrared spectrum of the solution, It is found that the effect of temperature plays the dominant role at low concentrations of chlorine salt; rather, the ionic dominates at high concentration. Chloride complexes are formed in aqueous solution, It has an effect on hydrogen bond of water combining with the cations in chlorine salt solution, Comparing different chloride solutions at the same concentration, the destruction effects of chloride complexes and catnions on the hydrogen bond of water increases in the sequences: CaCl2>NaCl>KCl. The modeling result shows that the determination coefficients (R2)=99.97%, the root mean square error of cross validation (RMSECV)=4.51, and the residual prediction deviation(RPD)=62.7, it meets the daily requirements of biochemical detection accuracy.
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Received: 2014-05-27
Accepted: 2014-08-28
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Corresponding Authors:
CHEN Jian-hong
E-mail: chenjianhong@xaut.edu.cn
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[1] YANG Dong-ying(杨东瑛). World Health Digest Medical Periodical, 2012, 9(44): 58. [2] DING Dong(丁 东). Near Infrared Spectroscopy Research and Application in Biomedicine, Jilin University, 2004 [3] Lin Jie, Zhou Jing, Chris W Beown. Applied Spectroscopy, 1996, 50(4): 444. [4] Ratcllffe C I, Irish D E. Journal of Phys. Chem., 1982, 86: 4897. [5] Frantz J D, Jean D, Bjorn M, Chemical Geology, 1993, 106(1): 9. [6] Ikushima Y, Arai M. Chem. Phys., 1998, 238(3): 455. [7] Buijs K,Choppin G R. The Journal of Chemical Physics,196(8):2035. [8] CHEN Jian-hong, ZHU Ling-jian, HUA Deng-xin(陈剑虹,朱凌建,华灯鑫). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2012, 32(4)):949. [9] ZHANG Xiang-lin(张祥麟). Chemical Complex(络合物化学). Beijing: Metallurgy Industry Press(北京:冶金工业出版社), 1979. 102. |
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