Modeling and simulation of SPR biosensors for detection of hemoglobin, electrolytes, glucose, and mosquito-borne infections in blood

Abstract

Recently, Surface Plasmon Resonance (SPR) has become an important technique in the development of sensors, surpassing traditional methods. This advancement represents an exciting frontier in nanotechnology, providing innovative solutions for the detection of biomolecules. This research is dedicated to design a simple device to measure hemoglobin (Hb) concentration in blood, detecting mosquito-borne diseases, and assessing glucose and electrolyte levels. Hemoglobin, a vital protein within red blood cells, plays a crucial role in oxygen transportation throughout the body. The device a nanohole array integrated dual-mode SPR sensor accurately measure hemoglobin concentrations, which aids to detect hemoglobin disorder. The study also explored the detection of the dengue NS1 antigen and malaria virus in humans through a MIM based grating-SPR sensor which is capable to focuses on the early identification of these mosquito-borne diseases. Additionally, glucose and electrolytes level in blood is also detected. The study simulated refractive indices of blood samples and assessed the plasmonic response through a wavelength range of 450 nm to 2500 nm. The proposed 3- layers biosensor has a top grating layer placed on a plasmonic metal base of Gold (Au) and Silver (Ag), all supported by a substrate. The plasmonic response is investigated through numerical simulation performed in ANSYS Lumerical FDTD solution 8.19.1584 for x64 version. Several key performance parameters namely Sensitivity, Full-Width-at-Half- Maximum (FWHM), Quality Factor, and Detection Accuracy were calculated to evaluate the performance of the plasmonic sensor model in biomolecular detection. The obtained results were compared with those reported in the existing literature to determine the degree of improvement and the extent of innovation introduced. It was found that the proposed design is capable of sensing the refractive indices of biomarkers across a broad wavelength range, thereby offering significant potential for advancing bio-sensing technologies