Constructing fingerprint sweat pore database based on donor–acceptor luminescent materials for personal identification

Human sweat pores, as the level-3 fingerprint information, are important biometric traits used for authentication. The imaging of sweat pores is of great interest for multiple applications related to personal identification. In this work, we outline the synthesis, spectral analysis, quantum chemical calculation of a class of hydrophilic aggregation-induced emission (AIE) luminogens, i.e., hydroxybenzylidene aminobenzoic acids. They assemble into nanoscale textures with strong emission, while disassemble into disordered state in contact with liquid water, accompanied by emission quenching. With finger pressing, the self-assembly films selectively disassemble by trace amount of water in the physically-contacting region, yielding a fingerprint image covering level-1/2/3 characteristics, including sweat pore information. A “Vector-Triangle Anchoring” (VTA) method is proposed to collect the sweat pore information, wherein the location and distribution of the sweat pores can be digitized and encrypted using their relative distances and direction angles. In addition, an elementary sweat pore database is established, whereby machine-learning-based personal identification is performed, enabling high accuracy.