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.
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