An Intelligent Photocatalytic Self-Cleaning SERS Platform with Machine Learning for On-Site Detection of Multiple Antibiotics

Key Points

• The aim is to develop an intelligent, self-cleaning SERS platform for on-site detection of antibiotic residues in aquatic environments.
• Validation with real environmental samples including lake water, river water, and shrimp.
• Measured recovery rates ranging from 92.49% to 107.10% and precision with RSD below 8.76%.
• Evaluated resistance to matrix interference.
• Achieved high accuracy in detecting multiple antibiotic residues.
• Demonstrated support for practical applications in environmental surveillance and food safety.
• Established significant resistance to matrix interference in various aquatic samples.