Citation: WU Yin, TIAN Shi-Si, LI Wen-Jie, SUN Ling-Hui, SONG Xi-Lin, ZHAO Ya-Bin, LI Zhan-Ping. Personal Identification of Fingerprint Donors Based on Time-of-Flight Secondary Ion Mass Spectrometry[J]. Chinese Journal of Analytical Chemistry, ;2023, 51(4): 570-578. doi: 10.19756/j.issn.0253-3820.221258 shu

Personal Identification of Fingerprint Donors Based on Time-of-Flight Secondary Ion Mass Spectrometry

WU Yin ¹ ,
TIAN Shi-Si ¹ ,
LI Wen-Jie ¹ ,
SUN Ling-Hui ¹ ,
SONG Xi-Lin ¹ ,
ZHAO Ya-Bin ^1,, ,
LI Zhan-Ping ^2,3,,

1.
Academy of Forensic Science, People's Public Security University of China, Beijing 100038, China;
2.
Analysis Center, Tsinghua University, Beijing 100084, China;
3.
Key Laboratory of Organic Optoelectronics & Molecular Engineering of Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, China

Corresponding author: ZHAO Ya-Bin, LI Zhan-Ping,
Received Date: 23 May 2022
Revised Date: 18 November 2022

Fund Project: Supported by the National Key R&D Program of China (No. 2018YFA0702600) and the General Science and Technology Program of the Ministry of Public Security (No. 2021JSM01).

Fingerprints, as one of the most important evidences, contain numerous personal information and are used for individual identification in the field of forensic science. However, in real case scenes, traditional way of comparison and matching with patterns may not be effective, as the detected fingerprints are mostly fuzzy or incomplete. Additionally, the compositions of fingerprint substance are so complicated that it is quite difficult to characterize donors according to some specific compounds. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) can obtain the mass spectra of fingerprint substances and corresponding ion distribution images without destroying the patterns, which provides the possibility of identifying individuals based on fingerprint substances. In this study, the mass spectra of ten fingerprints from 5 volunteers were collected using TOF-SIMS to preliminarily explore the feasibility of identifying individuals based on ion signals of fingerprint substance. Firstly, 98 kinds of TOF-SIMS ion signals representing different fingerprint substances were screened out followed by the process of principal component analysis to reduce the dimension of intensity of ion signals. Afterwards, the newly saved variables after dimension reduction were input into different classifiers to compare the effects. The results showed that the effect of unsupervised hierarchical clustering was quite different from the actual classification, while supervised Fisher discriminant method could correctly discriminate 94% of the individuals and the accuracy of cross-validation also reached 90%. Meanwhile, more ideal results would be achieved when the data was input into the multi-layer perceptron neural network after multiple trainings. The individual classification and prediction models were established via various statistical analysis methods, which provided a new channel for improving the evidence value of fingerprints and laid the research foundation for further exploration of employing fingerprint substances to identify individuals.
- Time-of-flight secondary ion mass spectrometry,
- Fingerprint substance,
- Personal identification,
- Multivariate statistical analysis
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