氩气对基于激光诱导击穿光谱的有机物分类和鉴定的影响

IF 1 4区 工程技术 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Yeqiu Li, Jingyi Zhao, Mingyang Cai, Hao Duan, Qian Li, Qin Dai, Rina Wu
{"title":"氩气对基于激光诱导击穿光谱的有机物分类和鉴定的影响","authors":"Yeqiu Li,&nbsp;Jingyi Zhao,&nbsp;Mingyang Cai,&nbsp;Hao Duan,&nbsp;Qian Li,&nbsp;Qin Dai,&nbsp;Rina Wu","doi":"10.1002/mop.34340","DOIUrl":null,"url":null,"abstract":"<p>Organic matter is the material basis of life, which is widely present in people's products and lives. The rapid and accurate detection of organic matter can be applied to the identification of fake and inferior products, the traceability of the origin of agricultural products, and the early warning of explosives in antiterrorism. By combining laser-induced breakdown spectroscopy (LIBS) with argon, the spectral characteristics of five common organic compounds (nitroglycerin, metronidazole, polyformaldehyde, polypropylene, and phenolic resin), the plasma lifetime, the parameters of plasma thermodynamic state, and the distribution of three existing forms of the element C in two gas environments were compared, the influence of argon on organic LIBS results and the reasons for its enhancement were analyzed. The results indicate that argon makes the atomization of carbon chain structures in organic matter more complete, and reduce the interference of the element N in air on the organic LIBS results to a certain extent. The intensity differences of different organic substances are more obvious. support vector machine optimized by principal component analysis and particle swam optimization algorithm was used to classify five kinds of organic matter. The prediction accuracy of classification in air is 94.4%, and it improves to 100% in argon. This result provides a powerful method for high-precision, real-time in-situ, and rapid identification of organic substances, which has important scientific significance for the study of organic substances LIBS.</p>","PeriodicalId":18562,"journal":{"name":"Microwave and Optical Technology Letters","volume":"66 9","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effect of argon on classification and identification of organics based on laser-induced breakdown spectroscopy\",\"authors\":\"Yeqiu Li,&nbsp;Jingyi Zhao,&nbsp;Mingyang Cai,&nbsp;Hao Duan,&nbsp;Qian Li,&nbsp;Qin Dai,&nbsp;Rina Wu\",\"doi\":\"10.1002/mop.34340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Organic matter is the material basis of life, which is widely present in people's products and lives. The rapid and accurate detection of organic matter can be applied to the identification of fake and inferior products, the traceability of the origin of agricultural products, and the early warning of explosives in antiterrorism. By combining laser-induced breakdown spectroscopy (LIBS) with argon, the spectral characteristics of five common organic compounds (nitroglycerin, metronidazole, polyformaldehyde, polypropylene, and phenolic resin), the plasma lifetime, the parameters of plasma thermodynamic state, and the distribution of three existing forms of the element C in two gas environments were compared, the influence of argon on organic LIBS results and the reasons for its enhancement were analyzed. The results indicate that argon makes the atomization of carbon chain structures in organic matter more complete, and reduce the interference of the element N in air on the organic LIBS results to a certain extent. The intensity differences of different organic substances are more obvious. support vector machine optimized by principal component analysis and particle swam optimization algorithm was used to classify five kinds of organic matter. The prediction accuracy of classification in air is 94.4%, and it improves to 100% in argon. This result provides a powerful method for high-precision, real-time in-situ, and rapid identification of organic substances, which has important scientific significance for the study of organic substances LIBS.</p>\",\"PeriodicalId\":18562,\"journal\":{\"name\":\"Microwave and Optical Technology Letters\",\"volume\":\"66 9\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microwave and Optical Technology Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/mop.34340\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microwave and Optical Technology Letters","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mop.34340","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

有机物是生命的物质基础,广泛存在于人们的产品和生活中。快速准确地检测有机物可应用于假冒伪劣产品的鉴别、农产品的产地溯源、反恐中的爆炸物预警等方面。通过将激光诱导击穿光谱(LIBS)与氩气相结合,比较了五种常见有机化合物(硝酸甘油、甲硝唑、聚甲醛、聚丙烯和酚醛树脂)的光谱特性、等离子体寿命、等离子体热力学状态参数以及三种现有形式的 C 元素在两种气体环境中的分布,分析了氩气对有机 LIBS 结果的影响及其增强的原因。结果表明,氩气能使有机物中的碳链结构雾化得更彻底,并在一定程度上减少了空气中 N 元素对有机物 LIBS 结果的干扰。采用主成分分析法和粒子游标优化算法优化的支持向量机对五种有机物进行了分类。在空气中的分类预测准确率为 94.4%,在氩气中的分类预测准确率提高到 100%。该结果为高精度、实时、原位、快速识别有机物提供了有力的方法,对有机物 LIBS 研究具有重要的科学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect of argon on classification and identification of organics based on laser-induced breakdown spectroscopy

Organic matter is the material basis of life, which is widely present in people's products and lives. The rapid and accurate detection of organic matter can be applied to the identification of fake and inferior products, the traceability of the origin of agricultural products, and the early warning of explosives in antiterrorism. By combining laser-induced breakdown spectroscopy (LIBS) with argon, the spectral characteristics of five common organic compounds (nitroglycerin, metronidazole, polyformaldehyde, polypropylene, and phenolic resin), the plasma lifetime, the parameters of plasma thermodynamic state, and the distribution of three existing forms of the element C in two gas environments were compared, the influence of argon on organic LIBS results and the reasons for its enhancement were analyzed. The results indicate that argon makes the atomization of carbon chain structures in organic matter more complete, and reduce the interference of the element N in air on the organic LIBS results to a certain extent. The intensity differences of different organic substances are more obvious. support vector machine optimized by principal component analysis and particle swam optimization algorithm was used to classify five kinds of organic matter. The prediction accuracy of classification in air is 94.4%, and it improves to 100% in argon. This result provides a powerful method for high-precision, real-time in-situ, and rapid identification of organic substances, which has important scientific significance for the study of organic substances LIBS.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Microwave and Optical Technology Letters
Microwave and Optical Technology Letters 工程技术-工程:电子与电气
CiteScore
3.40
自引率
20.00%
发文量
371
审稿时长
4.3 months
期刊介绍: Microwave and Optical Technology Letters provides quick publication (3 to 6 month turnaround) of the most recent findings and achievements in high frequency technology, from RF to optical spectrum. The journal publishes original short papers and letters on theoretical, applied, and system results in the following areas. - RF, Microwave, and Millimeter Waves - Antennas and Propagation - Submillimeter-Wave and Infrared Technology - Optical Engineering All papers are subject to peer review before publication
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信