指纹(计算)
聚类分析
人工智能
主成分分析
发光
材料科学
计算机科学
鉴定(生物学)
模式识别(心理学)
光电子学
植物
生物
出处
期刊:Materials horizons
[The Royal Society of Chemistry]
日期:2023-01-01
卷期号:10 (12): 5782-5795
被引量:6
摘要
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.
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