A.H.M. Iftekharul Ferdous , Md. Safiul Islam , Abdullah Al Mamun , Md. Hanif Reza , Md. Jakir Hossen , Md. Shamim Anower
{"title":"用于爆炸探测的太赫兹PCF传感器:硝化甘油和皇家爆破分析的机器学习方法","authors":"A.H.M. Iftekharul Ferdous , Md. Safiul Islam , Abdullah Al Mamun , Md. Hanif Reza , Md. Jakir Hossen , Md. Shamim Anower","doi":"10.1016/j.hazadv.2025.100886","DOIUrl":null,"url":null,"abstract":"<div><div>This article presents a square hollow core Photonic Crystal Fiber (PCF) sensor developed for high relative sensitivity detection of explosives (Nitroglycerin and Royal Demolition Explosive (RDX)) in the terahertz region (1 THz to 2.8 THz). The numerical sensing capabilities are assessed utilizing the finite element technique(FEM). We have attained enhanced relative sensitivity with negligible loss for detecting Nitroglycerine and RDX through the optimization of structural factors. The maximum relative sensitivity achieved is 98.09 % for Nitroglycerine and 88.25 % for RDX at 2 THz. Additionally, we have achieved little effective material loss (EML) and an extensive effective area. The proposed sensor design is compatible with current fabrication technologies, ensuring practical feasibility. Furthermore, the prediction was conducted with the Random Forest Regressor. We have attained optimal accuracy of prediction with a unity R<sup>2</sup> score, and this model may be utilized for predicting much behaviour, including relative sensitivity and EML for frequency.</div></div>","PeriodicalId":73763,"journal":{"name":"Journal of hazardous materials advances","volume":"20 ","pages":"Article 100886"},"PeriodicalIF":7.7000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Terahertz PCF sensor for explosive detection: A machine learning approach to nitroglycerine and royal demolition analysis\",\"authors\":\"A.H.M. Iftekharul Ferdous , Md. Safiul Islam , Abdullah Al Mamun , Md. Hanif Reza , Md. Jakir Hossen , Md. Shamim Anower\",\"doi\":\"10.1016/j.hazadv.2025.100886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article presents a square hollow core Photonic Crystal Fiber (PCF) sensor developed for high relative sensitivity detection of explosives (Nitroglycerin and Royal Demolition Explosive (RDX)) in the terahertz region (1 THz to 2.8 THz). The numerical sensing capabilities are assessed utilizing the finite element technique(FEM). We have attained enhanced relative sensitivity with negligible loss for detecting Nitroglycerine and RDX through the optimization of structural factors. The maximum relative sensitivity achieved is 98.09 % for Nitroglycerine and 88.25 % for RDX at 2 THz. Additionally, we have achieved little effective material loss (EML) and an extensive effective area. The proposed sensor design is compatible with current fabrication technologies, ensuring practical feasibility. Furthermore, the prediction was conducted with the Random Forest Regressor. We have attained optimal accuracy of prediction with a unity R<sup>2</sup> score, and this model may be utilized for predicting much behaviour, including relative sensitivity and EML for frequency.</div></div>\",\"PeriodicalId\":73763,\"journal\":{\"name\":\"Journal of hazardous materials advances\",\"volume\":\"20 \",\"pages\":\"Article 100886\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2025-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of hazardous materials advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772416625002979\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of hazardous materials advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772416625002979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Terahertz PCF sensor for explosive detection: A machine learning approach to nitroglycerine and royal demolition analysis
This article presents a square hollow core Photonic Crystal Fiber (PCF) sensor developed for high relative sensitivity detection of explosives (Nitroglycerin and Royal Demolition Explosive (RDX)) in the terahertz region (1 THz to 2.8 THz). The numerical sensing capabilities are assessed utilizing the finite element technique(FEM). We have attained enhanced relative sensitivity with negligible loss for detecting Nitroglycerine and RDX through the optimization of structural factors. The maximum relative sensitivity achieved is 98.09 % for Nitroglycerine and 88.25 % for RDX at 2 THz. Additionally, we have achieved little effective material loss (EML) and an extensive effective area. The proposed sensor design is compatible with current fabrication technologies, ensuring practical feasibility. Furthermore, the prediction was conducted with the Random Forest Regressor. We have attained optimal accuracy of prediction with a unity R2 score, and this model may be utilized for predicting much behaviour, including relative sensitivity and EML for frequency.