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《化学分析计量》 2020年第06期
DOI:10.3969/j.issn.1008-6145.2020.06.008
微流控芯片-表面增强拉曼光谱法快速测定污水中氯胺酮
常颖,赵阳,高利生
公安部物证鉴定中心,北京 100038 
Rapid determination of ketamine in sewage by microfluidic chip-surface enhanced Raman spectroscopy
CHANG Ying, ZHAO Yang, GAO Lisheng
Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China 
摘要:建立污水中氯胺酮的微流控芯片-表面增强拉曼光谱快速筛查方法。在碱性条件下,选取乙酸乙酯为提取试剂,盐酸为萃取试剂,利用拉曼表面增强试剂对样品中氯胺酮的拉曼光谱信号进行增强,进而对环境样品中的氯胺酮进行检测。氯胺酮的质量浓度在500~10 000 ng/mL范围内与拉曼峰特征强度具有良好的线性关系,相关系数为0.996 3,检出限为250 ng/mL。样品加标回收率为95.8%,测定结果的相对标准偏差为3.3%(n=6)。该方法检出限低,分析范围广,操作简便、快速,适用于污水、地表水、河道水等环境样品中低浓度违禁氯胺酮的检测。  
Abstract:A rapid screening method of ketamine in sewage by microfluidic chip-surface enhanced Raman spectroscopy was established. Under the alkaline condition, ethyl acetate was selected as the extraction reagent, hydrochloric acid was used as the extraction reagent, Raman surface enhancement reagent was used to enhance the spectral signal of ketamine in the sample, and then the ketamine in the environmental sample was detected. The mass concentration of ketamine had a good linear relationship with the characteristic strength of Raman peak in the range of 500-10 000 ng/mL, the correlation coefficient was 0.996 3, and the detection limit was 250 ng/mL. The standard addition recovery was 95.8%, and the relative standard deviation of the detection results was 3.3%(n=6). The method has the advantages of low detection limit, wide analysis range, simple and rapid operation, which is suitable for the detection of low concentrations of banned ketamine in environmental samples such as sewage, surface water and river water.  
关键词:氯胺酮;污水;微流控芯片;表面增强拉曼光谱 
Keywords:ketamine; sewage; microfluidic chip; surface enhanced Raman spectroscopy 
基金:公安部技术研究计划重点项目(2018JSYJA04);公安部技术研究计划项目(2018JSYJC09) 
本文引用格式:
常颖,赵阳,高利生.微流控芯片-表面增强拉曼光谱法快速测定污水中氯胺酮[J].化学分析计量,2020,29(6):33-37.
CHANG Y,ZHAO Y,GAO L S. Rapid determination of ketamine in sewage by microfluidic chip-surface enhanced Raman spectroscopy[J]. Chemical analysis and meterage,2020,29(6):33-37. 

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