Hydrogen-Bonded Organic Frameworks for Antibiotic Fluorescent Sensing Artificial Intelligence-Enhanced...

Area of Science:

• Materials Science
• Analytical Chemistry
• Nanotechnology

Background:

• Consumer safety is threatened by counterfeit products, necessitating robust anticounterfeiting solutions.
• Multistimulus responsive luminescent materials offer advanced security features for product authentication.
• Existing methods require enhancement for dynamic and multilayered security assurance.

Purpose of the Study:

• To synthesize a novel luminescent material, Eu/Tb@GC-3, for anticounterfeiting applications.
• To develop intelligent anticounterfeiting labels using multistimulus responsive luminescent fibers and inks.
• To integrate these labels with neural networks for improved authentication and consumer safety.

Main Methods:

• Postsynthetic modification was employed to synthesize the Eu/Tb@GC-3 material.
• Photoluminescent properties were characterized, showing emissions at 544 and 614 nm.
• Detection limits for Nitrofural and Enrofloxacin were determined using the synthesized material.
• Multistimulus responsive luminescent fibers and inks were fabricated.
• Back-propagation neural networks (BPNNs) were integrated for pattern recognition.

Main Results:

• The novel Eu/Tb@GC-3 material exhibits distinct photoluminescence at 544 and 614 nm.
• High sensitivity and selectivity were achieved in detecting Nitrofural (LOD 0.0122 μM) and Enrofloxacin (LOD 0.0280 μM).
• Intelligent anticounterfeiting labels were successfully developed using luminescent fibers and inks.
• Integration with BPNNs significantly improved pattern recognition and authentication accuracy.

Conclusions:

• The developed Eu/Tb@GC-3 material and intelligent labels provide an effective anticounterfeiting strategy.
• This approach enhances product safety and reliability, safeguarding consumers from counterfeit goods.
• The combination of advanced materials and AI offers a promising solution for combating product counterfeiting.