Numerical Simulation of Surface Plasmon Resonance Optical Fiber Biosensor Enhanced by Using Alloys for Medical Application.

IF 1.5 Q3 INSTRUMENTS & INSTRUMENTATION
Sensing and Imaging Pub Date : 2023-01-01 Epub Date: 2023-01-31 DOI:10.1007/s11220-022-00409-y
Parisa Esmailidastjerdipour, Fateme Shahshahani
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引用次数: 0

Abstract

Tuberculosis is a very dangerous disease. Therefore, early and quick diagnosis of this disease can increase the chances of overcoming it. Studies show that people with tuberculosis have a lower blood plasma refractive index than healthy people. The performance of the fiber optic sensor based on surface plasmon resonance is investigated for the metal/oxide/graphene structure and for cases where the diameter of the fiber optic core is 300, 600, and 940 µm while blood plasma is considered as the sensing medium. The sensor characteristics such as sensitivity, detection accuracy and figure of merit are simulated for each structure using the theory of matrix method in Wolfram Mathematica software. The simulation results show that the aluminum/lutetium oxide/graphene structure has the highest quality factor when the core diameter of the optical fiber is 940 µm. In continuation of this research, the effects of using alloys with different mixture proportions to improve the quality are investigated. According to results, the structure of aluminum/copper alloy (with a ratio of 30/70)-lutetium oxide graphene is the best choice for improving the quality of the sensor.

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利用合金增强表面等离子体共振光纤生物传感器的数值模拟,用于医疗应用。
肺结核是一种非常危险的疾病。因此,早期快速诊断这种疾病可以增加战胜疾病的机会。研究表明,肺结核患者的血浆折射率低于健康人。本文研究了基于表面等离子体共振的光纤传感器在金属/氧化物/石墨烯结构以及光纤纤芯直径为 300、600 和 940 微米的情况下的性能,并将血浆视为传感介质。利用 Wolfram Mathematica 软件中的矩阵法理论模拟了每种结构的传感器特性,如灵敏度、检测精度和优点系数。模拟结果表明,当光纤纤芯直径为 940 微米时,铝/氧化镥/石墨烯结构的品质因数最高。在继续这项研究的过程中,还研究了使用不同混合比例的合金来提高质量的效果。结果表明,铝/铜合金(比例为 30/70)-氧化镥石墨烯结构是提高传感器质量的最佳选择。
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来源期刊
Sensing and Imaging
Sensing and Imaging INSTRUMENTS & INSTRUMENTATION-
CiteScore
5.00
自引率
0.00%
发文量
31
期刊介绍: Sensing and Imaging: An International Journal publishes peer-reviewed theoretical and experimental papers in print and online covering sensing and imaging techniques, systems, networks, and applications in engineering, science and medicine. The journal scope is broad and multidisciplinary, covering subsurface and surface sensing, and other sensing areas. Subsurface and surface sensing involves detection, identification and classification of objects, structures and matter, respectively, under and at surfaces.
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