Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387244598> ?p ?o ?g. }
- W4387244598 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." @default.
- W4387244598 created "2023-10-03" @default.
- W4387244598 creator A5021784577 @default.
- W4387244598 creator A5079294349 @default.
- W4387244598 date "2023-01-01" @default.
- W4387244598 modified "2023-10-12" @default.
- W4387244598 title "Multifunctional Eu(III) Modified HOFs: Roxarsone and Aristolochic Acid Carcinogen Monitoring and Latent Fingerprint Identification Based on Artificial Intelligence" @default.
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- W4387244598 doi "https://doi.org/10.1039/d3mh01253k" @default.
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- W4387244598 hasPublicationYear "2023" @default.
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