title: Forensic classification of counterfeit banknote paper by X-ray fluorescence and multivariate statistical methods.
abstract: Counterfeiting of banknotes is a crime and seriously harmful to economy. Examination of the paper, ink and toners used to make counterfeit banknotes can provide useful information to classify and link different cases in which the suspects use the same raw materials. In this paper, 21 paper samples of counterfeit banknotes seized from 13 cases were analyzed by wavelength dispersive X-ray fluorescence. After measuring the elemental composition in paper semi-quantitatively, the normalized weight percentage data of 10 elements were processed by multivariate statistical methods of cluster analysis and principle component analysis. All these paper samples were mainly classified into 3 groups. Nine separate cases were successfully linked. It is demonstrated that elemental composition measured by XRF is a useful way to compare and classify papers used in different cases.
authors.affiliation: Institute of Forensic Science, Ministry of Public Security, Muxidi South 17#, Xicheng District, Beijing, China. Electronic address: guohongling1234@163.com.
authors.forename: Hongling
authors.initials: H
authors.lastname: Guo
authors.affiliation: Institute of Forensic Science, Ministry of Public Security, Muxidi South 17#, Xicheng District, Beijing, China.
authors.forename: Baohua
authors.initials: B
authors.lastname: Yin
authors.affiliation: Beijing Children's Legal Aid and Research Center, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Institute of Forensic Science, Ministry of Public Security, Muxidi South 17#, Xicheng District, Beijing, China.
authors.forename: Yangke
authors.initials: Y
authors.lastname: Quan
authors.affiliation: Institute of Forensic Science, Ministry of Public Security, Muxidi South 17#, Xicheng District, Beijing, China.
authors.forename: Gaojun
authors.initials: G
authors.lastname: Shi
keywords: Counterfeit banknote paper; Linking; Multivariate analysis; XRF