Abstract：
The exploration of multifunctional materials and intelligent technologies used for fluorescence sensing and latent fingerprint (LFP) identification is a research hotspot of material science. In this study, an emerging crystalline luminescent material, Eu3+-functionalized hydrogen-bonded organic framework (Eu@HOF-BTB, Eu@1), is fabricated successfully. Eu@1 can emit purple red fluorescence with a high photoluminescence quantum yield of 36.82%. Combined with artificial intelligence (AI) algorithms including support vector machine, principal component analysis, and hierarchical clustering analysis, Eu@1 as a sensor can concurrently distinguish two carcinogens, roxarsone and aristolochic acid, based on different mechanisms. The sensing process exhibits high selectivity, high efficiency, and excellent anti-interference. Meanwhile, Eu@1 is also an excellent eikonogen for LFP identification with high-resolution and high-contrast. Based on an automatic fingerprint identification system, the simultaneous differentiation of two fingerprint images is achieved. Moreover, a simulation experiment of criminal arrest is conducted. By virtue of the Alexnet-based fingerprint analysis platform of AI, unknown LFPs can be compared with a database to identify the criminal within one second with over 90% recognition accuracy. With AI technology, HOFs are applied for the first time in the LFP identification field, which provides a new material and solution for investigators to track criminal clues and handle cases efficiently.
摘要：
探索用于荧光传感和潜在指纹(LFP)识别的多功能材料和智能技术是材料科学的研究热点。在这项研究中,一种新兴的晶体发光材料，Eu3+官能化氢键有机骨架(Eu@HOF-BTB，Eu@1)，制造成功。Eu@1能发出紫红色荧光,光致发光量子产率高达36.82%。结合包括支持向量机在内的人工智能(AI)算法,主成分分析，和层次聚类分析，Eu@1作为传感器可以同时区分两种致癌物，罗沙松和马兜铃酸，基于不同的机制。传感过程具有很高的选择性，效率高,和优秀的抗干扰。同时,Eu@1也是具有高分辨率和高对比度的LFP识别的优秀eikonogen。基于自动指纹识别系统，实现了两幅指纹图像的同时区分。此外，进行了刑事逮捕的模拟实验。借助AI基于Alexnet的指纹分析平台,可以将未知的LFP与数据库进行比较，以在一秒钟内以超过90％的识别准确率识别罪犯。借助AI技术,HOF首次在LFP标识字段中应用，这为侦查人员追踪犯罪线索和有效办案提供了新的材料和解决方案。
