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Published on: October 10, 2013
Mapping human fingerprint beyond level-3 based on an amphiphilic aggregation-induced emission luminogen and the
Xinyi Zhao1, Zixuan Wang1, Haoran Liu1
1Department of Chemistry, Capital Normal University, Beijing, 100048, China.
Background:
Fluorescence imaging agents have been benefiting tremendously from tailor-made aggregation-induced emission (AIE) luminogens, owing to their high on-off ratio, large signal contrast, low background noise as well as the resistance to photobleaching. In the domain of fingerprint imaging, AIE luminogens are beginning to exhibit an advantage owing to the aforementioned superiorities.
Results:
We present an amphiphilic benzoic-acid salicylaldehyde AIE luminogen AIE-BASB, and outline its water sensitivity, self-assembly behavior as well as fingerprint imaging properties. AIE-BASB self-assembles into nanoscale textures when fabricated into a drop-casting film but undergoes a disassembly process in response to trace water on fingertip upon physical-contacting. Owing to the biological textures on the skin, fingerprint image can be clearly recorded by AIE-BASB film, which reveals detailed microscopic features of fingerprint information ranging from level-1 to level-3. Furthermore, it allows accurate measurements of the sizes, shapes, centroids, and areas of the sweat pores, which leads the fingerprint information into the next level. In addition, we develop an intelligent system based on AIE-BASB by integrating hardware and software modules, which is capable of recording and identifying fingerprint. After inputting fingerprint segments in trial operation, this intelligent system makes identification by calculation of the categorical probability, and successfully predicts the classification of the undefined fingerprint segments, implying 100 % accuracy in fingerprint identification.
Significance:
We predict that AIE-BASB may facilitate the development of new biometric technologies, which have broad applications in the domain of artificial intelligence, including machine tactility, target perception and object-machine interaction.

