Next-generation advanced surface plasmon resonance biosensor for dopamine detection with ZnO-ag multilayer design: Machine learning optimization for high sensitivity.

The individual's physiological system needs to function effectively for a person to maintain life in good health. Deficiency of vitamins and minerals and a structured approach to life tend to trigger variations in the quantity of biological substances, which include hormonal substances, proteins, and neurotransmitters, and threaten the well-being of humans. The most common and the most fundamental catecholamine neurotransmitter present throughout the brain and nervous system is dopamine. The primary nervous system, kidneys, the hormone-sensitive, cardiac, and metabolic functions of humans have each been controlled by how much it is in the body's tissues. Consequently, it would be desirable to come up with an exceptionally sensitive, precise and productive approach that allows for a quick determination of Dopamine levels. Here, we have defined a novel design of Radial Petal-Loop Pattern Refractive Index Biosensor (RPLPRIB) for measurements of dopamine components like Dn1, Dn2, Dn3, Dn4, and Dn5, with refractive index values of 1.256, 1.267, 1.289, 1.291, and 1.309. This structure's petal rings possess a greater efficient area of surface for substrate binding, which enabled greater numbers of dopamine receptors for interaction at the same time, therefore reducing the limit of detection. The outcomes of the RPLPRIB show substantial sensitivity of 1666.66 nm/RIU, and substantial limits of detection 0.000190 RIU, for the concentrations of Dn5 and Dn3, respectively. The substantial quality factor values of 2077.66 and the sensor range value of 2108.78 RIU have been achieved for the concentration of Dn4. The machine learning approach also shows a substantial R-square value of 0.991156 with a low mean-square error. The defined idea represents suitable results that can perfectly help to determine dopamine.