Abstract
Malaria is a mosquito-borne disease caused by unicellular hemoparasites of the genus Plasmodium that results in the death of over one million people worldwide every year. Early diagnosis plays a key role in the treatment of infected patients and can reduce the mortality rate. This work proposes a simple designed photonic crystal fiber (PCF) sensor for detecting malarial infection using the refractive index (RI) of red blood cells (RBCs). The initial structure of the PCF sensor consists of double loops of circular air holes arranged in a hexagonal formation. A horizontal elliptical channel in the center of the fiber contains the RBCs sample. The sensor’s response was observed from the shift of the transmission spectra due to change in the RI of RBCs during different life stages of the parasite. Model parameters (transmission length, pitch, air hole diameter, and eccentricity of the elliptical channel) of the proposed sensor were optimized to obtain the best possible response. The highest spectral sensitivities were obtained about 11,428.57 nm/RIU, 9473.68 nm/RIU, and 9655.17 nm/RIU for the ring, trophozoite, and schizont phases of the parasite, respectively. Due to its high sensitivity, easy identification capability, and short transmission length, this sensor can be utilized as a cost-effective and useful device for malaria diagnosis.
Highlights
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A single elliptical channel photonic crystal fiber sensor is reported for the potential malaria detection.
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The reported sensor is numerically investigated using finite element method based COMSOL Multiphysics software.
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The design parameters of the sensor are also optimized for achieving the best sensing response.
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The reported sensor shows the highest spectral sensitivities of 11,428.57 nm/RIU, 9473.68 nm/RIU, and 9655.17 nm/RIU for infected RBCs during the parasite’s ring, trophozoite, and schizont phases, respectively.
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Shafkat, A., Rashed, A.N.Z., El-Hageen, H.M. et al. Design and analysis of a single elliptical channel photonic crystal fiber sensor for potential malaria detection. J Sol-Gel Sci Technol 98, 202–211 (2021). https://doi.org/10.1007/s10971-021-05490-5
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DOI: https://doi.org/10.1007/s10971-021-05490-5