Versatile core–shell magnetic fluorescent mesoporous microspheres for multilevel latent fingerprints magneto-optic information recognition

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Abstract

Latent fingerprints are extremely vital for personal identification and criminal investigation, and potential information recognition techniques have been widely used in the fields of information and communication electronics. Although physical powder dusting methods have been frequently employed to develop latent fingerprints and most of them are carried out by using single component powders of micron-sized fluorescent particles, magnetic powders, or metal particles, there is still an enormous challenge in producing high-resolution image of latent fingerprints at different backgrounds or substrates. Herein, a novel and effective nanoimpregnation method is developed to synthesize bifunctional magnetic fluorescent mesoporous microspheres for latent fingerprints visualization by growth of mesoporous silica (mesoSiO2) on magical Fe3O4 core and then deposition of fluorescent YVO4:Eu3+ nanoparticles in the mesopores. The obtained Fe3O4@mesoSiO2@YVO4:Eu3+ microspheres possess spatially isolated magnetic core and fluorescent shell which were insulated by mesoporous silica layer. Due to their small particle size of submicrometer scale, high magnetization and low magnetic remanence as well as the combined magnetic and fluorescent properties, the microspheres show superior performance in visual latent fingerprint recognition with high contrast, high anti-interference, and sensitivity as well as good retention on multifarious substrates regardless of surface permeability, roughness, refraction, colorfulness, and background fluorescence interference, and it makes them ideal candidates for practical application in fingerprint visualization and even magneto-optic information storage. (Figure presented.).

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Yu, B., Liu, S., Xie, W., Pan, P., Zhou, P., Zou, Y., … Deng, Y. (2022). Versatile core–shell magnetic fluorescent mesoporous microspheres for multilevel latent fingerprints magneto-optic information recognition. InfoMat, 4(5). https://doi.org/10.1002/inf2.12289

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