Non-destructive Electromagnetic Wave Sensor for Hazardous Biological Materials

K. H. Teng, Ibijoke A. Idowu, P. Kot, A. Shaw, M. Muradov
{"title":"Non-destructive Electromagnetic Wave Sensor for Hazardous Biological Materials","authors":"K. H. Teng, Ibijoke A. Idowu, P. Kot, A. Shaw, M. Muradov","doi":"10.1109/DeSE.2019.00122","DOIUrl":null,"url":null,"abstract":"A novel non-destructive electromagnetic wave (EM) sensor for rapid identification of biological material is presented in this paper. Biological treats could be defined as biological agents such as bacteria spores, viruses and toxins. Spores can disable or kill people, animals and crops. Therefore, it is important to identify the hazard in rapid and nondestructive manner to make a safer environment. In this research, a 2.45 GHz microwave resonator was used to detect the dipliconic acid (DPA), which is the bio-maker of bacillus spores. A promising results were obtained by detecting the DPA from 0.001M – 0.3M concentration at frequency of 2.4 GHz, which are the fundamental mode (TM101) of the designed cavity. In addition, different species of bacillus spores was detected at frequency approximate at 2.36 GHz. The results concluded that electromagnetic wave sensors may have the potential for use as a non-destructive and real time sensor to detect bacillus spores. The EM principle could be extended to detect different hazardous biological materials by identify the “finger print” of specific biological materials on different surfaces.","PeriodicalId":6632,"journal":{"name":"2019 12th International Conference on Developments in eSystems Engineering (DeSE)","volume":"11 1","pages":"651-655"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th International Conference on Developments in eSystems Engineering (DeSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DeSE.2019.00122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

A novel non-destructive electromagnetic wave (EM) sensor for rapid identification of biological material is presented in this paper. Biological treats could be defined as biological agents such as bacteria spores, viruses and toxins. Spores can disable or kill people, animals and crops. Therefore, it is important to identify the hazard in rapid and nondestructive manner to make a safer environment. In this research, a 2.45 GHz microwave resonator was used to detect the dipliconic acid (DPA), which is the bio-maker of bacillus spores. A promising results were obtained by detecting the DPA from 0.001M – 0.3M concentration at frequency of 2.4 GHz, which are the fundamental mode (TM101) of the designed cavity. In addition, different species of bacillus spores was detected at frequency approximate at 2.36 GHz. The results concluded that electromagnetic wave sensors may have the potential for use as a non-destructive and real time sensor to detect bacillus spores. The EM principle could be extended to detect different hazardous biological materials by identify the “finger print” of specific biological materials on different surfaces.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
有害生物材料无损电磁波传感器
提出了一种用于生物材料快速识别的新型无损电磁波传感器。生物制剂可定义为细菌、孢子、病毒和毒素等生物制剂。孢子可以使人、动物和庄稼丧失能力或死亡。因此,以快速和非破坏性的方式识别危险对于创造更安全的环境至关重要。本研究利用2.45 GHz微波谐振器对芽孢杆菌孢子的生物制造者二倍体酸(DPA)进行了检测。通过在2.4 GHz频率下检测浓度为0.001M ~ 0.3M的DPA,获得了令人满意的结果,该频率为设计腔的基模(TM101)。此外,在大约2.36 GHz的频率上检测到不同种类的芽孢杆菌孢子。结果表明,电磁波传感器有可能作为一种无损的实时传感器来检测芽孢杆菌孢子。EM原理可以扩展到通过识别不同表面上特定生物材料的“指纹”来检测不同的有害生物材料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Fresh and Mechanical Properties of Self-Compacting Lightweight Concrete Containing Ponza Aggregates LPLian: Angle-Constrained Path Finding in Dynamic Grids The Sentiment Analysis of Unstructured Social Network Data Using the Extended Ontology SentiWordNet Investigation of IDC Structures for Graphene Based Biosensors Using Low Frequency EIS Method Comparing Unsupervised Layers in Neural Networks for Financial Time Series Prediction
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1