拉曼光谱法鉴别常见炸药

目的建立一种识别炸药的方法。方法使用激光显微拉曼光谱法对17种常见炸药粉末进行了分析。结果17种常见炸药均有丰富的拉曼位移峰,可以通过其位移峰峰位的不同区分不同成分的炸药。结论拉曼光谱法适用于快速准确地识别炸药。     

傅里叶变换拉曼光谱法分析微量洗衣粉

傅里叶变换拉曼光谱法是一种快速高效、无损检材的检验方法。利用傅里叶变换拉曼光谱仪对市场上常见洗衣粉进行分析,可以对不同品牌、不同产地的洗衣粉进行一定程度的区分。该方法能够为相关案件的检验鉴定工作提供依据和参考。     

显微红外光谱仪与显微拉曼光谱仪对纺用无色单根纤维的检测

目的研究常见纺用单根无色纤维的有效鉴别方法。方法使用显微红外光谱仪、显微激光拉曼光谱仪研究7大类纺用单根无色纤维的分子光谱。结果显微红外光谱仪、显微激光拉曼光谱仪能有效区分包括棉、粘胶、羊毛、丝、聚酰胺、聚丙烯腈和聚酯在内的7种纤维,是检测单根纤维的有效手段。785nm激发光源是显微激光拉曼光谱仪研究这7类纤维的最佳波长。但由于纺用纤维生产过程的标准化,仅依据红外或者拉曼的峰位置区分同种类、不同产地纤维的效果一般。结论显微红外光谱仪、显微激光拉曼光谱仪是鉴别常见纺用单根无色纤维的有效方法。     

显微红外光谱仪与显微拉曼光谱仪对纺用无色单根纤维的检测

目的研究常见纺用单根无色纤维的有效鉴别方法。方法使用显微红外光谱仪、显微激光拉曼光谱仪研究7大类纺用单根无色纤维的分子光谱。结果显微红外光谱仪、显微激光拉曼光谱仪能有效区分包括棉、粘胶、羊毛、丝、聚酰胺、聚丙烯腈和聚酯在内的7种纤维,是检测单根纤维的有效手段。785nm激发光源是显微激光拉曼光谱仪研究这7类纤维的最佳波长。但由于纺用纤维生产过程的标准化,仅依据红外或者拉曼的峰位置区分同种类、不同产地纤维的效果一般。结论显微红外光谱仪、显微激光拉曼光谱仪是鉴别常见纺用单根无色纤维的有效方法。     

红外光谱在毒药物检验中的应用

目的　建立毒药物检验的红外光谱测定方法。　方法　用液液萃取法提取检材中的安眠药、精神药品、农药、杀鼠剂和无机毒物 ,然后应用红外光谱法进行定性分析。　结果　常见毒药物均有其特征红外吸收峰 ,通过其特征吸收峰可以区分不同毒药物。　结论红外光谱法快速、准确 ,适用于干扰较轻检材中毒药物的定性分析。     

显微共焦拉曼光谱技术区分喷墨打印机打印的彩色图文墨迹

目的建立显微共焦拉曼光谱法区分喷墨打印机打印的彩色图文墨迹的方法。方法利用显微共焦拉曼光谱技术所具有微量、微区、原位分析及非破坏性等特点,对24种常见彩色墨水墨迹分别进行检验。结果品红色墨点墨迹成分归类区分效果最好,其次是黄色墨点,最后是蓝色墨点。结论采用显微共焦拉曼光谱技术对彩色打印墨迹进行不同颜色单点分析可大大提高喷墨打印机厂家型号的识别率,是一种有效的检测手段。     

黑色墨迹的拉曼光谱分析

目的对常见的黑色墨迹进行初步筛选,为墨迹的进一步检验提供依据。方法依据黑色墨迹的同色异谱特征,利用显微共焦激光拉曼光谱仪对19种黑色墨迹进行分析检验。结果根据不同墨迹的拉曼谱图,19种黑色墨迹可以分为3大类,即:未检出拉曼峰的墨迹,只检出碳物质的墨迹,以及主体色料为染料的墨迹。结论拉曼光谱可用于区分不同种类黑色墨迹,从而为选择合适的方法对黑色墨迹进一步进行检验奠定基础。     

激光显微共聚焦拉曼光谱仪对红色墨迹的研究

目的利用激光显微共聚焦拉曼光谱仪对文书中常见的红色墨迹材料进行表征,研究该方法对红色墨迹材料的区分能力。方法在785nm激发波长,50倍物镜条件下,对49种红色印文,以及9种彩色喷墨打印和13种彩色激光打印的红色墨迹材料进行拉曼光谱表征。结果通过对71种墨迹样品的谱图进行分析,可以发现,红色印文墨迹、喷墨打印红色墨迹及激光打印红色墨迹的拉曼光谱间均存在差异,同时,拉曼光谱可将这三种墨迹材料分别进一步区分。结论显微共聚焦激光拉曼光谱可对红色墨迹材料进行有效表征和区分。这一方法可对红色印文墨迹进行识别,并且可实现对伪造印文文件的鉴别。     

表面增强拉曼光谱对黑色圆珠笔快速鉴别的检测研究

目的 建立圆珠笔油墨的表面增强拉曼光谱分析方法,实现更加有效的圆珠笔样品种类区分。方法 选用纳米银胶体作为增强试剂,在785、633、514 nm 3种激发光波长下,分析检测市场上55支黑色圆珠笔的表面增强拉曼光谱,并通过将各激发光波长下的数据相结合来综合分析种类区分信息。结果 根据表面增强拉曼光谱图可有效区分出不同品牌圆珠笔油墨之间的差异。与增强前的拉曼光谱相比,增强之后的谱峰信号更强,在进行种类区分时更具说服力。785、633、514 nm 3种激发光波长的谱图信息相结合可获取更多有效的区分信息。结论 该方法能够有效鉴别不同品牌同一颜色的圆珠笔油墨,为司法鉴定中油墨成分的快速鉴别提供新思路。     

激光拉曼光谱区分黑色圆珠笔字迹初探

针对现在广泛使用的薄层色谱分析技术带有破坏检材的缺点,提取采用激光拉曼光谱法进行无损检验,通过对收集的5个国家10种牌号样品进行初步比对分析,区分率达90%以上.     

常见阔叶木木屑浸提物的紫外光谱分析

利用紫外光谱法和一阶导数光谱法对不同树种及同种树不同产地的阔叶木木屑的浸提分进行了分析。结果表明．不同树种、同树种不同产地阔叶木木屑浸提物的紫外光谱图中。吸收峰的峰数、峰形有一定的差异：一阶导数光谱图中。正、负峰的峰数、峰位、峰形及振幅值的比值差异显著．据此可对阔叶木木屑进行种类的鉴别。     

激光拉曼光谱对苯骈杂氮（堇）类药物的定性检测

目的 建立用拉曼光谱检测苯骈杂氮革类药物的定性方法.方法 利用激光拉曼光谱仪对10种苯骈杂氮革类药物进行检验.结果 10种苯骈杂氮（萆）类药物的主成分均能被拉曼准确检出.结论 该法能较好地对苯骈杂氮革类药物固体样品快速定性分析.     

显微激光拉曼光谱技术区分喷墨打印墨迹研究

目的运用激光显微共聚焦拉曼光谱仪对打印墨水的墨迹样品进行检验。方法采用514nm激发波长,测得EPSON、HP、CANON等3个品牌21种型号墨迹样品的拉曼光谱。结果根据拉曼峰位的异同,可将21种型号墨迹样品分为8大类。结论该方法可以快速区分常见不同种类打印墨水墨迹,为印刷文件的检验鉴定提供方法参考。     

Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy

Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.     

Raman Spectroscopic Differences between Ephedrine and Pseudoephedrine

Ephedrine (EPH) and pseudoephedrine (PSE) were studied by micro‐Raman spectroscopy and UV resonance Raman spectroscopy excited at 785 and 360 nm, respectively. Raman bands at approximately 245 and 410 cm^?1 for ephedrine have apparent differences from the same bands at approximately 215, 265, 350, 450, and 555 cm^?1 for pseudoephedrine, and these differences can be applied to distinguish between EPH and PSE. Additionally, density functional theory was used for the Raman calculations to obtain results identical to the experimental spectra. This work is expected to expand the applications of Raman spectroscopy in forensic science.     

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.     

拉曼光谱快速定性分析合成毒品

目的快速定性检测合成毒品;方法利用激光拉曼光谱仪对合成毒品进行检验;结果合成毒品苯丙胺、甲基苯丙胺、氯胺酮、麻黄碱、甲基麻黄碱均能被拉曼准确检出;结论激光拉曼光谱能对合成毒品快速定性分析。