Numerical Analysis on PCF-based SPR Sensors' Air-hole Attributed Performance to Blood Cancer Detection

In the human body, both cancerous cells and their corresponding normal counterparts are recognized as the body's intrinsic fluidic cells, each characterized by its unique refractive index (RI). For the purpose of disease detection, the analysis of fluidic samples may alternatively be facilitated through the utilization of refractometric surface plasmon resonance (SPR) sensor based on photonic crystal fiber (PCF). The sensor can detect the cancerous cells using the changes in resonance wavelength of abnormal cell and relative normal cell loss peak. This study explores the numerical analysis of three PCF-based SPR sensors for detecting blood cancers. The sensitivity to RI was investigated for these three models, which were constructed with different air-hole geometries. They feature a coating of TiO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> to enhance bond between the gold layer and the PCF. Computational analyses were conducted employing the COMSOL Multiphysics software, leveraging the full-vector finite element method. The outcomes demonstrate the sensors' efficacy in distinguishing Jurkat, leukemia, and other blood cancer cell types within a narrow RI range spanning from 1.390 to 1.394. The calculated wavelength sensitivities for three models ('a', 'b', and 'c') for detecting blood cancer cells (Jurkat) were 8571.43 nm/RIU, 5000 nm/RIU, and 8571.43 nm/RIU, respectively. In contrast, the computed amplitude sensitivity was −2688.57 RIU −1 , −1241.17 RIU −1 , and −1633.12 RIU −1 , respectively. In addition, while calculating the shift in wavelength, the model 'a' had the largest shift (140 nm) compared to the models 'b' and 'c'. This improved performance offers scope for improved early detection capabilities in identifying malignant cells non-invasively.