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激光拉曼光谱技术在火炸药分析检测中的应用研究进展
引用本文:高凤,刘文芳,孟子晖,薛敏,苏鹏飞,胡岚.激光拉曼光谱技术在火炸药分析检测中的应用研究进展[J].含能材料,2018,26(2):185-196.
作者姓名:高凤  刘文芳  孟子晖  薛敏  苏鹏飞  胡岚
作者单位:北京理工大学化学与化工学院, 北京 102488,北京理工大学化学与化工学院, 北京 102488,北京理工大学化学与化工学院, 北京 102488,北京理工大学化学与化工学院, 北京 102488,西安近代化学研究所, 陕西 西安 710065,西安近代化学研究所, 陕西 西安 710065
摘    要:激光拉曼光谱是一种原位无损快速检测技术,在火炸药分析检测领域具有重要的应用前景。综述了普通激光拉曼光谱以及在此基础上发展起来的傅里叶变换拉曼、共焦显微拉曼、表面增强拉曼、便携式拉曼以及远程拉曼技术在火炸药分析检测领域的应用研究进展,分析了不同类型激光拉曼光谱技术的优点和局限性,比较了三硝基甲苯(TNT)、六硝基六氮杂异伍兹烷(CL-20)、奥克托今(HMX)、太安(PETN)、黑索今(RDX)等典型炸药的激光拉曼光谱数据。认为建立火炸药的拉曼定量分析方法、制备性能优异的表面增强拉曼的基底材料及进一步发展便携式拉曼是未来的研究重点。

关 键 词:激光拉曼光谱    火炸药    分析    检测
收稿时间:2017/9/9 0:00:00
修稿时间:2018/1/15 0:00:00

Review on Application of Laser Raman Spectroscopy in Analysis and Detection of Explosives
GAO Feng,LIU Wen-fang,MENG Zi-hui,XUE Min,SU Peng-fei and HU Lan.Review on Application of Laser Raman Spectroscopy in Analysis and Detection of Explosives[J].Chinese Journal of Energetic Materials,2018,26(2):185-196.
Authors:GAO Feng  LIU Wen-fang  MENG Zi-hui  XUE Min  SU Peng-fei and HU Lan
Abstract:Laser Raman spectroscopy is an in-situ non-destructive fast detection technology, which has significant application prospects in the field of explosives analysis and detection. Research progress on the applications of conventional laser Raman spectroscopy and its derivative techniques including Fourier transform Raman spectroscopy (FT-Raman), confocal micro Raman, surface enhanced Raman scattering(SERS), portable Raman and remote Raman in the field of explosives analysis were reviewed. The advantages and limitations of different type of laser Raman spectroscopic techniques were analyzed. The laser Raman spectra data of several typical explosives such as TNT, CL-20, HMX, PETN and RDX were compared. It is considered that the future research should focus on the establishment of Raman quantitative analysis methods for explosives, the preparation of high-performance substrate materials for surface enhanced Raman and the improvement of portable Raman spectroscopy.
Keywords:Laser Raman spectroscopy  explosives  analysis  detection
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