Nanocomposites of Nitrogen/Zinc-Doped Carbon Dots@ Hydrotalcite with Highly Fluorescent in Solid-State for Visualization of Latent Fingerprints

作     者：Li, Dawu Zhang, Xing-Fu Ding, Bao-Hong Lv, Xiao-Sen 

作者机构：College of Forensic Science National Police University of China Liaoning Shenyang110035 China Key Laboratory of Impression Evidence Examination and Identification Technology Ministry of Public Security Liaoning Shenyang110035 China College of Petrochemical Engineering Liaoning Petrochemical University Fushun113001 China 

出 版 物：《SSRN》 

年 卷 期：2022年

核心收录：

主　　题：Nanocomposites 

摘      要：Herein, we report on the optical performances of a newly developed nanocomposite based on N-doped carbon dots with Zn-assisted modification (Zn/N-CDs) using hydrotalcite as the support (Zn/N-CDs@hydrotalcite) for the enhanced solid-state fluorescence in its application of the visualization of latent fingerprints (LFPs). The as-prepared Zn/N-CDs@hydrotalcite can interact with universal components of the LFPs residues through electrostatic interactions and physical adsorption. Good dispersion of the Zn/N-CDs on the surface of hydrotalcite overcomes aggregation-induced quenching effect, and emits the bright green fluorescence of 525 nm under the excitation of 365 nm ultraviolet light in solid states, providing a well-defined platform for the visualization of LFPs. The feasibility of the as-prepared Zn/N-CDs@hydrotalcite as a fluorescent label for the visualization of LFPs is tested. The results illustrate that the well-defined details of ridge patterns in level 2 and level 3 of the LFPs characteristics on various substrates (such as glass, aluminum foil, tiles, plastic packing of beer bottle, paper and leather) are clearly identified for individual identification using conventional powder dusting method. Green emission of the as-prepared Zn/N-CDs@hydrotalcite can provide sufficient contrast to background interferences of substrate surfaces. The as-prepared Zn/N-CDs@hydrotalcite with high sensitivity and wide applicability has great potential as a promising alternative for the visualization of LFPs. © 2022, The Authors. All rights reserved.