Wave-Shaped Microstructure Cancer Detection Sensor in Terahertz Band: Design and Analysis

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Abstract

For the quick identification of diverse types of cancer/malignant cells in the human body, a new hollow-core optical waveguide based on Photonic Crystal Fiber (PCF) is proposed and numerically studied. The refractive index (RI) differs between normal and cancerous cells, and it is through this distinction that the other crucial optical parameters are assessed. The proposed cancer cell biosensor’s guiding characteristics are examined in the COMSOL Multiphysics v5.5 environment. The Finite Element Method (FEM) framework is used to quantify the display of the suggested fiber biosensor. Extremely fine mesh elements are additionally added to guarantee the highest simulation accuracy. The simulation results on the suggested sensor model achieve a very high relative sensitivity of 99.9277%, 99.9243%, 99.9302%, 99.9314%, 99.9257% and 99.9169%, a low effective material loss of (Formula presented.) cm (Formula presented.), (Formula presented.) cm (Formula presented.), (Formula presented.) cm (Formula presented.), (Formula presented.) cm (Formula presented.), (Formula presented.) cm (Formula presented.), and (Formula presented.) cm (Formula presented.) for adrenal gland cancer, blood cancer, breast cancer type-1, breast cancer type-2, cervical cancer, and skin cancer, respectively, at a 3.0 THz frequency regime. A very low confinement loss of (Formula presented.) dB/cm is also indicated by the simulation findings for all of the cancer cases that were mentioned. The straightforward PCF structure of the proposed biosensor offers a high likelihood of implementation when used in conjunction with these conventional performance indexes. So, it appears that this biosensor will create new opportunities for the identification and diagnosis of various cancer cells.

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APA

Khan, M. R. H., Chowdhury, A. A., Islam, M. R., Hosen, M. S., Mim, M. H., & Nishat, M. M. (2023). Wave-Shaped Microstructure Cancer Detection Sensor in Terahertz Band: Design and Analysis. Applied Sciences (Switzerland), 13(9). https://doi.org/10.3390/app13095784

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