Fluorescence-based imaging applications have been benefiting greatly from donor-acceptor(D-A)/donor-π-acceptor(D-π-A)fluorescent probes owing to their intramolecular charge transfer(ICT)nature and self-assembly beha...Fluorescence-based imaging applications have been benefiting greatly from donor-acceptor(D-A)/donor-π-acceptor(D-π-A)fluorescent probes owing to their intramolecular charge transfer(ICT)nature and self-assembly behavior.In this study,we design and synthesize a hydrophilic D-A fluorescent probe,namely CHBA,which would self-assemble into interlaced textures down to nanoscale but disassemble by trace amount of water in fingertip area.Upon finger-pressing,it enables fingerprint imaging and covers level-1/2/3 fingerprint information,wherein the sweat pores can be mapped in both bright field model and fluorescence mode,capable of naked-eye-based similarity analysis for personal identity verification(PIV).Spectroscopic analysis and morphology study show that the working mechanism can be attributed to the selective water-erosion effect on the solid-liquid interphase under physical contact.The sweat pore information can be digitized by polar coordinate conversion,further allowing machine-learning-based analysis for PIV application.The final PIV accuracy reaches 100%for all the involved machine-learning models,with no erroneous judgements.A prototype of PIV system is constructed by integrating CHBA with artificial intelligence hardware,wherein the sweat pore imaging,data processing and the decisionmaking could be run in parallel,suggesting high feasibility in real-world application.展开更多
基金the financial support from National Natural Science Foundation of China(No.51703135)the technical support from Beijing Key Laboratory of Optical Materials and Photonic Devices。
文摘Fluorescence-based imaging applications have been benefiting greatly from donor-acceptor(D-A)/donor-π-acceptor(D-π-A)fluorescent probes owing to their intramolecular charge transfer(ICT)nature and self-assembly behavior.In this study,we design and synthesize a hydrophilic D-A fluorescent probe,namely CHBA,which would self-assemble into interlaced textures down to nanoscale but disassemble by trace amount of water in fingertip area.Upon finger-pressing,it enables fingerprint imaging and covers level-1/2/3 fingerprint information,wherein the sweat pores can be mapped in both bright field model and fluorescence mode,capable of naked-eye-based similarity analysis for personal identity verification(PIV).Spectroscopic analysis and morphology study show that the working mechanism can be attributed to the selective water-erosion effect on the solid-liquid interphase under physical contact.The sweat pore information can be digitized by polar coordinate conversion,further allowing machine-learning-based analysis for PIV application.The final PIV accuracy reaches 100%for all the involved machine-learning models,with no erroneous judgements.A prototype of PIV system is constructed by integrating CHBA with artificial intelligence hardware,wherein the sweat pore imaging,data processing and the decisionmaking could be run in parallel,suggesting high feasibility in real-world application.
