On-site SERS analysis and intelligent multi-identification of fentanyl class substances by deep machine learning

Qiao-Yan Jiang; Yuan Zhang; Yang Sun; Li-Xiang Wang; Zhengsheng Mao; Cong Pian; Ping Huang; Feng Chen; Yue Cao

doi:10.1016/j.saa.2024.125090

On-site SERS analysis and intelligent multi-identification of fentanyl class substances by deep machine learning

Spectrochim Acta A Mol Biomol Spectrosc. 2025 Jan 15:325:125090. doi: 10.1016/j.saa.2024.125090. Epub 2024 Sep 5.

Authors

Qiao-Yan Jiang¹, Yuan Zhang², Yang Sun³, Li-Xiang Wang³, Zhengsheng Mao³, Cong Pian⁴, Ping Huang⁵, Feng Chen⁶, Yue Cao⁷

Affiliations

¹ Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, China (Academy of Forensic Science), Shanghai 200063, China; Department of Pathology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou 317000, Zhejiang, China.
² College of Sciences, Nanjing Agricultural University, Nanjing 210095, China.
³ Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, China.
⁴ School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, Jiangsu, China. Electronic address: piancong@njau.edu.cn.
⁵ Institute of Forensic Science, Fudan University, 200433, China.
⁶ Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, China. Electronic address: fchen@njmu.edu.cn.
⁷ Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, China (Academy of Forensic Science), Shanghai 200063, China; Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, China. Electronic address: ycao@njmu.edu.cn.

PMID: 39260236
DOI: 10.1016/j.saa.2024.125090

Abstract

As the types of fentanyl class substances continue to grow, a universal SERS sensor is essential for the application of discriminant detection of fentanyl substances. A new nanomaterial SERS sensor-Ag@Au NPs-paper was developed. The SERS sensitivity and stability of Ag@Au NPs-paper were investigated by using R6G molecule, and the results showed that Ag@Au NPs-paper has excellent performance. In combination with visual analysis and machine learning methods, Ag@Au NPs-paper has been successfully applied to the analysis of fentanyl class substances and the component identification of binary fentanyl mixtures, and thus it can be effectively used in food safety, environmental toxicants and other fields.

Keywords: Ag@Au NPs-paper; Fentanyl class substances; Machine learning.

MeSH terms

Deep Learning
Fentanyl* / analysis
Gold* / chemistry
Metal Nanoparticles* / chemistry
Silver* / chemistry
Spectrum Analysis, Raman* / methods

Substances

Fentanyl
Silver
Gold