Rapid Identification and Quantification of Aqueous Antibiotics over a Machine Learning-Integrated Raman Sensor Array
Abstract
up to 0.99 with markedly reduced prediction errors. The method is validated in river water, lake water, and municipal wastewater secondary effluent, yielding recoveries of 75.5-116% (median 97.5%), with 23/27 measurements within 80-110%, and an overall turnaround of ∼30 min from sample preparation to readout. Through coupling the dual-mode responsive Raman sensor array with data-driven modeling, this work provides a paradigm of rapid and multianalyte SERS analysis of structurally similar pollutants for on-site environmental monitoring.
Fields of Study & Subjects
Spectroscopy Techniques in Biomedical and Chemical Research
Gold and Silver Nanoparticles Synthesis and Applications
Advanced Chemical Sensor Technologies
Publication details
- Journal / source
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Volume
- 60
- Issue
- 14
- Pages
- 10861–10870
- Publication date
- 2 April 2026
- Language
- EN