Highly Sensitive and Accurate Cortisol Sensor Based on Long-Range Surface Plasmon Resonance
V. Kuḿar, Nitesh Kumar, Sarika Pal, Bela Goyal, Anuj K. Sharma, Yogendra Kumar Prajapati
Abstract
Cortisol is a stress hormone that can significantly control metabolism and immune system activities. Its higher and lower levels can cause Cushing's syndrome and Addison's disease, respectively. An accurate and highly sensitive detection of cortisol levels is crucial to monitor human mental and physical health. In this sequence, we propose and simulate a sensor design based on long-range surface plasmon resonance (LRSPR) for measuring cortisol concentrations in human saliva. The sensor's structure includes a 2S2G prism, Cytop (1500 nm), silver (18 nm), bismuth titanate (12 nm), molybdenum ditelluride (2×0.82 nm), cysteamine (5 nm), and a sensing medium (SM). A detailed analysis of the simulation results related to proposed sensor design shows that it achieves a high angular figure of merit (FOM<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ang.</sub>) of 276.3 RIU<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>, detection accuracy (DA) of 25/°, imaging sensitivity (S<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">img.</sub>) of 13,931 RIU<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>, and an imaging figure of merit (IFOM) of 348,275 (°RIU)<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>. The comparison reveals that the proposed sensor significantly outperforms the conventional surface plasmon resonance (CSPR) sensor. The Finite Element Method (FEM) simulations further reveal that the proposed sensor design achieves a large penetration depth of 510.10 nm and a cortisol detection limit of 0.1765 ng/ml. The results demonstrate a significant improvement compared to the sensor reported in the literature. It shows the potential for non-invasive and accurate cortisol monitoring required for monitoring related health conditions..