We have investigated graphene-based three various refractive index sensors (split ring resonator (SRR), split ring resonator with thin wire (SRRTW), and thin wire (TW) refractive index sensors) for the encoding and sensing-based applications. The sensors are designed to detect the presence of hemoglobin biomolecules with high sensitivity. The results are analyzed in the form of transmittance, and electric field and detailed sensitivity analysis is also carried out for the proposed graphene-based refractive index sensors for four various concentrations of hemoglobin biomolecules. We have also investigated the sensor’s performance in terms of quality factor, Q, and figure of merit (FOM). The encoding of ‘0’ and ‘1’ is attained by varying the graphene chemical potential fulfilling the one-digit coding. An array of these sensors can then be used for encoding-based applications. The detailed analysis of reported sensors is also carried out by checking the effect of varying physical parameters such as substrate thickness, split ring gap, and thin wire width on tunability. These sensors can be applied in biomedical or encoding-based applications. Experiments are performed using XGBoost regressor to determine, whether simulation time and resources can be reduced by using regression analysis to predict the transmittance values of intermediate frequency or not. Experimental results prove that regression analysis using XGBoost Regressor can reduce the simulation time and resources by at least 70 percent.

Heavy metal ion contamination of water supplies has significantly increased during the last century due to advances in industry and technology. Therefore, a lot of effort was put into developing chemical and physical methods for detecting and tracking the presence of these potentially harmful solutions. Despite their comparatively high sensitivity and low detection limits, these methods are hindered by complex instrumentation and tedious, expensive, and difficult chemical processes. Therefore, in this study, we present a straightforward and effective sensing method based on the graphene metasurface for detecting several classes of heavy metal ions. A graphene-metasurface-inspired optical sensor with a glass substrate is developed that can detect Cu²⁺ and Mg²⁺ with a sensitivity of 113.92 GHz/RIU and 113.9 GHz/RIU, respectively. In addition to that, the linear fitting curve for both the metal ions is established, and R² score of 0.9997 and 0.9982 is achieved, respectively. Furthermore, the lowest value of the figure of merit (FOM) of 2.98 RIU⁻¹ and the maximum Quality factor (Q factor) of 11.22 is obtained. The proposed structure also exhibited a low detection limit as well as a resolution of 0.52 RIU and 78.14 THz, respectively. As a result of these findings, a simple and accurate tool for detecting water contamination with heavy metals and aqueous solutions with relatively high performance is developed.