|
|
|
|
|
|
Micro Confocal Raman Spectroscopy Combined With Chemometrical Method for Forensic Differentiation of Electrostatic Copy Paper |
CHEN Wei-na1, GUO Zhong-zheng1, LI Kai-kai1, YANG Yu-zhu1, YANG Xu2* |
1. College of Investigation, People’s Public Security University of China, Beijing 100038, China
2. Academy of Forensic Science, Ministry of Justice, Shanghai 200063, China
|
|
|
Abstract The identification of electrostatic copy paper is an important work in forensic science physical examination. Establish the analysis method of microscopic confocal Raman spectroscopy combined with Chemometrics to examine different brands and models of copying paper, to achieve the non-destructive inspection and accurate identification of copy paper. The online shopping platform was used to collect 20 kinds of electrostatic copy paper of different brands and models. The Raman Spectra data of different paper samples were collected by using the laser wavelength of 785 nm semiconductor laser. The main characteristic peaks in each paper sample and their corresponding components were analyzed. The spectral data were classified by Wohlde hierarchical clustering analysis, and the discrimination results were evaluated by principal component analysis (PCA). It was found that the main characteristic peaks of different paper samples were concentrated in the range of 900~1 700 cm-1, respectively around 714,892,1 092,1 119,1 143,1 343,1 385,1 470,1 510 and 1 600 cm-1, and the main components were cellulose, lignin and calcium carbonate. Although the spectral curves of each paper sample overlap each other, there are some differences in peak intensity and peak area. The spectral data of paper samples can be classified and identified by cluster analysis and principal component analysis in Chemometrics. According to the tree diagram of the system cluster analysis and the scatter diagram drawn in light of the schedule Table, 20 kinds of copy paper samples in different brands and models can be divided into four categories. Among the four categories, 10 samples are included in ClassⅠ and 3 samples are included in ClassⅡ, ClassⅢ contains six samples and ClassⅣ contains only one sample. Then PCA of spectral data of paper samples in the range of 900~1 700 cm-1, the contribution of the first two principal components in 17 principal components reached 84%, which contained most of the spectral information. Based on the first two principal components, the principal component scores of the Raman Spectrum data of paper samples were drawn. It was found that the results of cluster analysis were well verified in the principal component scores. All the subclasses contained in Class Ⅰ-Class Ⅳ can be grouped and distinguished clearly. The results of classification and identification are accurate and reasonable. This method can not damage the paper samples when used, the operation process is simple, and the effect of identification is ideal. It can be applied to the examination and analysis of documents material evidence in forensic science, and it can provide clues and a basis for tracing the source of material evidence.
|
Received: 2021-03-09
Accepted: 2021-12-16
|
|
Corresponding Authors:
YANG Xu
E-mail: yangx@ssfjd.cn
|
|
[1] LI Ji-min, WANG Yan-ji, WANG Jing-han, et al(李继民,王彦吉,王景翰,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2009, 29(6): 1521.
[2] SHEN Si, LIU Meng, LI Yang-yong,et al(申 思,刘 猛,李杨勇,等). The Journal of Light Scattering(光散射学报), 2017, 29(3):257.
[3] CUI Lian-yi(崔连义). Journal of Analytical Science(分析科学学报), 2013, 29(2): 294.
[4] CUI Lian-yi(崔连义). China Pulp & Paper(中国造纸), 2021, 40(2): 37.
[5] CHEN Wei-na, LÜ Chen-chen, YANG Chun-song, et al(陈维娜,吕辰晨,杨春松,等). China Pulp & Paper(中国造纸), 2017, 36(10): 37.
[6] Causin V, Marega C, Marigo A, et al. Forensic Science International, 2010, 197(1-3): 70.
[7] MA Xiao, WANG Xiao-bin, WANG Xin-cheng(马 枭,王晓宾,王新承). Chemical Research and Application(化学研究与应用), 2020, 32(5): 873.
[8] GUO Zhong-zheng, CHEN Wei-na, WANG Xiao-bin, et al(国中正,陈维娜,王晓宾,等). Physical Testing and Chemical Analysis(Part B: Chemical Analysis)(理化检验-化学分册), 2020, 56(8): 878.
[9] NIU Fan, HUANG Jian-tong, HE Sen(牛 凡,黄建同,何 森). Physical Testing and Chemical Analysis(Part B: Chemical Analysis)(理化检验-化学分册), 2016, 52(12): 1478.
[10] LIU Bin, ZHAO Li, JIANG Yuan-long, et al(柳 彬,赵 丽,江沅龙,等). The Journal of Light Scattering(光散射学报), 2017, 29(2): 153.
|
[1] |
GE Deng-yun, XU Min-min, YUAN Ya-xian*, YAO Jian-lin*. Surface-Enhanced Raman Spectroscopic Investigation on the Effect of
Solution pH on Dehydroxylation of Hydroxythiophenol Isomers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 2076-2081. |
[2] |
XU Liang-ji1, 2, MENG Xue-ying2, WEI Ren2, ZHANG Kun2. Experimental Research on Coal-Rock Identification Method Based on
Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 2135-2142. |
[3] |
HE Xu1, 2, 3, HE Yi1, 2, 3*, ZHANG Li-feng1, 2, 3, CHEN Yi1, 2, 3, PU Hong-yu1, 2, 3, CHEN Bao-shan1, 2, 3. Spatio-Temporal Analysis of Land Subsidence in Beijing Plain Based on InSAR and PCA[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 2315-2324. |
[4] |
FENG Rui-jie1, CHEN Zheng-guang1, 2*, YI Shu-juan3. Identification of Corn Varieties Based on Bayesian Optimization SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1698-1703. |
[5] |
ZHU Xiang1, 2*, YUAN Chao-sheng1, CHENG Xue-rui1, LI Tao1, ZHOU Song1, ZHANG Xin1, DONG Xing-bang1, LIANG Yong-fu2, WANG Zheng2. Study on Performances of Transmitting Pressure and Measuring Pressure of [C4mim][BF4] by Using Spectroscopic Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1674-1678. |
[6] |
WANG Ming-xuan, WANG Qiao-yun*, PIAN Fei-fei, SHAN Peng, LI Zhi-gang, MA Zhen-he. Quantitative Analysis of Diabetic Blood Raman Spectroscopy Based on XGBoost[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1721-1727. |
[7] |
YOU Gui-mei1, ZHANG Wen-jie1, CAO Zhen-wei2, HAN Xiang-na1*, GUO Hong1. Analysis of Pigments of Colored Paintings From Early Qing-Dynasty Fengxian Dian in the Forbidden City[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1874-1880. |
[8] |
MIAO Shu-guang1, SHAO Dan1*, LIU Zhong-yu2, 3, FAN Qiang1, LI Su-wen1, DING En-jie2, 3. Study on Coal-Rock Identification Method Based on Terahertz
Time-Domain Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1755-1760. |
[9] |
LI Qing1, 2, XU Li1, 2, PENG Shan-gui1, 2, LUO Xiao1, 2, ZHANG Rong-qin1, 2, YAN Zhu-yun3, WEN Yong-sheng1, 2*. Research on Identification of Danshen Origin Based on Micro-Focused
Raman Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1774-1780. |
[10] |
TIAN Xue1, CHE Qian1, YAN Wei-min1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Discrimination of Millet Varieties and Producing Areas Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1841-1847. |
[11] |
MA Fang1, HUANG An-min2, ZHANG Qiu-hui1*. Discrimination of Four Black Heartwoods Using FTIR Spectroscopy and
Clustering Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1915-1921. |
[12] |
WANG Gan-lin1, LIU Qian1, LI Ding-ming1, YANG Su-liang1*, TIAN Guo-xin1, 2*. Quantitative Analysis of NO-3,SO2-4,ClO-4 With Water as Internal Standard by Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1855-1861. |
[13] |
HUANG Bin, DU Gong-zhi, HOU Hua-yi*, HUANG Wen-juan, CHEN Xiang-bai*. Raman Spectroscopy Study of Reduced Nicotinamide Adenine Dinucleotide[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1679-1683. |
[14] |
WANG Zhong, WAN Dong-dong, SHAN Chuang, LI Yue-e, ZHOU Qing-guo*. A Denoising Method Based on Back Propagation Neural Network for
Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1553-1560. |
[15] |
FU Qiu-yue1, FANG Xiang-lin1, ZHAO Yi2, QIU Xun1, WANG Peng1, LI Shao-xin1*. Research Progress of Pathogenic Bacteria and Their Drug Resistance
Detection Based on Surface Enhanced Raman Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1339-1345. |
|
|
|
|