Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy
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...
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| Veröffentlicht in: | Computational intelligence and neuroscience 2022-02, Vol.2022, p.8330702-7 |
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| creator | Zhang, Qian Chen, Bowen Wahid, Fazli Feng, Wanyun Chen, Xuerou |
| description | 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. |
| doi_str_mv | 10.1155/2022/8330702 |
| format | Article |
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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.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2022/8330702</identifier><identifier>PMID: 35154308</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Analysis ; Anthracene ; Capillary electrophoresis ; Chemical fingerprinting ; Chromatography ; Efficiency ; Health aspects ; Humans ; Ions ; Mass spectrometry ; Methods ; Phenanthrene ; Pollutants ; Polycyclic Aromatic Hydrocarbons ; Polymers ; Raman spectra ; Raman spectroscopy ; Reproducibility ; Scientific imaging ; Selectivity ; Sensitivity ; Sensors ; Solvents ; Spectroscopy ; Spectrum Analysis, Raman</subject><ispartof>Computational intelligence and neuroscience, 2022-02, Vol.2022, p.8330702-7</ispartof><rights>Copyright © 2022 Qian Zhang et al.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Qian Zhang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Qian Zhang et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-6086198a552843707e507c4ba3a49ad4f4e16b8bf44e271694003f0080568bf73</citedby><cites>FETCH-LOGICAL-c476t-6086198a552843707e507c4ba3a49ad4f4e16b8bf44e271694003f0080568bf73</cites><orcidid>0000-0001-8912-260X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8828328/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8828328/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35154308$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ding, Baiyuan</contributor><contributor>Baiyuan Ding</contributor><creatorcontrib>Zhang, Qian</creatorcontrib><creatorcontrib>Chen, Bowen</creatorcontrib><creatorcontrib>Wahid, Fazli</creatorcontrib><creatorcontrib>Feng, Wanyun</creatorcontrib><creatorcontrib>Chen, Xuerou</creatorcontrib><title>Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy</title><title>Computational intelligence and neuroscience</title><addtitle>Comput Intell Neurosci</addtitle><description>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.</description><subject>Analysis</subject><subject>Anthracene</subject><subject>Capillary electrophoresis</subject><subject>Chemical fingerprinting</subject><subject>Chromatography</subject><subject>Efficiency</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Ions</subject><subject>Mass spectrometry</subject><subject>Methods</subject><subject>Phenanthrene</subject><subject>Pollutants</subject><subject>Polycyclic Aromatic Hydrocarbons</subject><subject>Polymers</subject><subject>Raman spectra</subject><subject>Raman spectroscopy</subject><subject>Reproducibility</subject><subject>Scientific imaging</subject><subject>Selectivity</subject><subject>Sensitivity</subject><subject>Sensors</subject><subject>Solvents</subject><subject>Spectroscopy</subject><subject>Spectrum 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| subjects | Analysis Anthracene Capillary electrophoresis Chemical fingerprinting Chromatography Efficiency Health aspects Humans Ions Mass spectrometry Methods Phenanthrene Pollutants Polycyclic Aromatic Hydrocarbons Polymers Raman spectra Raman spectroscopy Reproducibility Scientific imaging Selectivity Sensitivity Sensors Solvents Spectroscopy Spectrum Analysis, Raman |
| title | Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy |
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