Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy

Abstract

Cycloaromatic hydrocarbons are a type of potentially hazardous chemicals that are widely present in the environment and pose a serious threat to human health. However, the traditional research methods for their detection process are cumbersome, the detection cycle is long, and the sensitivity is low. In response to the above problems, this article combines the molecular fingerprint information characteristics of surface-enhanced Raman scattering technology to simulate the four polycyclic aromatic hydrocarbons of pyrene, anthracene, phenanthrene, and trichenium and quantitative detection of cyclic aromatic hydrocarbons and four kinds of polycyclic aromatic hydrocarbon mixtures. The experimental results show that the PAHs based on SERS have the advantages of higher sensitivity and high selectivity, which verifies the accuracy and feasibility of the method in this article.