CaF2/TiO2 nanophotonic biosensor based on a one-dimensional photonic crystal for Chikungunya virus detection

被引:1
|
作者
Aly, Arafa H. [1 ,2 ]
Mohamed, B. A. [1 ]
Al-Dossari, M. [3 ]
Mohamed, D. [1 ]
Awasthi, S. K. [4 ]
Fouad, Emadelden [5 ]
Alshomrany, Ali S. [6 ]
Amin, A. F. [7 ]
Hanafy, H. [1 ]
机构
[1] Beni Suef Univ, Fac Sci, Phys Dept, TH PPM Grp, Bani Suwayf 62514, Egypt
[2] Western Caspian Univ, Dept Tech Sci, Baku 1001, Azerbaijan
[3] King Khalid Univ, Dahran Aljanoub Appl Coll, Abha 62529, Saudi Arabia
[4] Jaypee Inst Informat Technol, Dept Phys & Mat Sci & Engn, Noida 201304, UP, India
[5] Florida Polytech Univ, Dept Engn Phys, Lakeland, FL 33805 USA
[6] Umm Al Aura Univ, Coll Sci, Dept Phys, Al Taif 24381, Saudi Arabia
[7] Beni Suef Univ, Fac Technol & Educ, Bani Suwayf 62111, Egypt
关键词
D O I
10.1364/AO.537230
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
An optical sensor based on a defective photonic crystal is proposed to identify the Chikungunya virus in blood components, including plasma, platelets, red blood cells (RBCs), and uric acid. Under healthy conditions, each blood component has a unique refractive index; this value is altered if the person is infected with the Chikungunya virus. The infected blood sample results in a deviation in the refractive index of the sample as compared to a normal sample due to the presence of the infection in the human blood. With the help of our suggested structure, this alteration can be detected, and the normal cell can be distinguished from the infected one. To simulate the results, the transfer matrix method (TMM) is applied. The sensitivity of the suggested structures loaded separately with the sample containing plasma, platelets, red blood cells, and uric acid is found to be 1411, 1352, 1335, and 795 nm/RIU, respectively. These results are enough to support our claim that the present design can be used as an ultra-sensitive nanophotonic biosensor for the detection of the Chikungunya virus. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
引用
收藏
页码:7909 / 7916
页数:8
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