文章基本信息

标题：Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy
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作者：Qian Zhang ; Bowen Chen ; Fazli Wahid 等
期刊名称：Computational Intelligence and Neuroscience
印刷版ISSN：1687-5265
电子版ISSN：1687-5273
出版年度：2022
卷号：2022
DOI：10.1155/2022/8330702
语种：English
出版社：Hindawi Publishing Corporation
摘要：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.