الفهرس 
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Abstract
Due to the advances in medical science, optical biosensors have been the key interest of the researchers recently. Generally, optical devices have advantages over the traditional devices of high accuracy, immunity against stray electromagnetics, wide range, and small response time. Additionally, optical biosensors are highly efficient in biomedical mediums where other electrical based devices would fail to operate. Further, optical biosensors can be fabricated with small scale down to nanometres where the interaction with nano-organisms can be achieved. Furthermore, surface plasmon (SP) based photonic crystal fiber (PCF) biosensors are characterized with high degree of flexibility where they can be adjusted to suite a specific sensing process. In addition, the high dependence of the surface plasmon on the index of refraction of the dielectric surrounding it at the metal/dielectric interface provides SP biosensors with superiority among their other alternatives. It is worth noting that the study of DNA hybridization has become a key interest in the field of medical diagnosing and disease infection prediction. Regarding this point, it is possible to obtain an unknown DNA sequence from a successful hybridization with another known sequence. In addition, according to the degree of successful hybridization between a person and a virus DNA’s it is possible to predict the probability for that person to get infected by that virus. In this context, a novel design of a highly sensitive SP PCF biosensor for DNA hybridization detection is presented and analyzed. Through this study, the coupling between the core guided modes in a silica core D-shaped PCF and the SP modes around the gold nanowires is described and verified. Further, the structural geometrical parameters of the proposed biosensors are adjusted to achieve the highest sensitivity for DNA hybridization detection. The analysis is carried out using full vectorial finite element method (FVFEM). The proposed biosensor achieves a high sensitivity of 94.59 nm/RIU. To the best of the researcher’s knowledge, it is the first time to introduce a label free SP PCF DNA biosensor with high sensitivity. Moreover, the structure of the suggested sensor is easy for fabrication with standard PCF fabrication technologies. Furthermore, the suggested biosensor has a great potential for DNA classification-based applications. In addition, the suggested design is capable of predicting the potential for exact people to get infected with a specific disease in the future. Moreover, A design of SP PCF for DNA hybridization detection is proposed and analyzed. The suggested biosensor relies on plasmonic D-shaped PCF configuration where the core guided mode in the silica core is coupled effectively with the SP mode near the planner plasmonic silver layer of the D-shape. The resonance wavelength is sensitive to the DNA hybridization process. Therefore, the suggested biosensor is studied to maximize the DNA hybridization detection sensitivity by adjusting the structural geometrical parameters. The numerical results are obtained using full vectorial finite element method with perfectly matched layer boundary condition and non-uniform meshing capabilities. The reported D-shaped PCF offers high wavelength sensitivity of 405.4 nm/RIU with a corresponding amplitude sensitivity of 5.65 RIU^(-1). Consequently, the applications based on DNA classification and infection probability prediction can be potentially implemented by the reported biosensor. Further, two novel designs of compact surface plasmon resonance multifunctional biosensors based on nematic liquid crystal (NLC) and Alcohol mixture PCF are proposed and studied. The suggested sensors have a central hole filled either with NLC or alcohol mixture as temperature dependent materials. Further, another large hole filled with liquid analyte has a gold nanorod as a plasmonic material. Therefore, the proposed sensors can be used for temperature and analyte refractive index sensing via the coupling between the core guided modes in the central hole and the surface plasmon modes around the gold nanorod. The effects of the structure geometrical parameters are studied to maximize the sensitivity of the PCF biosensors. The numerical analysis is carried out using full-vectorial finite element method with perfectly matched layer boundary conditions. The reported multifunctional NLC based sensor offers high sensitivity of 5 nm/℃ for temperature range (30℃ : 50℃) and 3700 nm/RIU (refractive index unit) for refractive index range (1.33 : 1.34) for temperature and analyte refractive index sensing, respectively. In addition, the alcohol mixture PCF sensor achieves high temperature sensitivity of 13.1 nm/℃ over temperature range (-4℃ : 53℃) with high analyte refractive index sensitivity of 12700 nm/RIU for refractive index change (1.33 : 1.34). To the best of the researcher’s knowledge, it is the first time to introduce PCF biosensor with high sensitivity for temperature and analyte refractive index sensing as well. In addition, according to the unfortunate increase in the cancer infections around the globe along with the high treatment complexity and cost, an early detection for cancer infection has become of high importance. Based on the difference in the refractive index of the cancer cells and normal cells, it is possible to diagnose cancer infection at very early stages. In this regard, a unique design of metamaterial biosensor for cancer early detection is proposed and analyzed. The suggested structure is based on two loops of hexagonal gold layers on a polyamide substrate. High field confinement is obtained in the sensing region with high absorption of 0.999 and high quality factor of 11.33 at f= 3.15 THz. The resonance frequency is sensitive to the sample refractive index variation. Therefore, high average sensitivity of 1649.8 GHz/RIU is achieved for cancer early detection through basal cell, breast cell, bervical cell, jurkat, MCF-7, and PC12. Further, high linear performance is obtained with good robustness against fabrication imperfection. The analysis is carried out using full vectorial finite element method.