Nanoengineered Graphene Metasurface Surface Plasmon Resonance Sensor for Precise Hemoglobin Detection with AI-Assisted Performance Prediction

Abstract

The development of highly sensitive and reliable biosensors for hemoglobin detection is crucial for various medical and diagnostic applications. Hemoglobin, a vital protein in red blood cells responsible for oxygen transport, serves as an important biomarker for numerous health conditions. Accurate and rapid measurement of hemoglobin levels can aid in the early detection and monitoring of anemia, blood disorders, and other medical conditions. This study presents a biosensor design for hemoglobin detection, integrating a graphene-based metasurface with circular and square ring resonators constructed from silver and gold nanostructures. The proposed sensor leverages the unique plasmonic properties of plasmonic nanostructures and the remarkable optical characteristics of graphene to enhance its performance. Extensive parametric analysis and optimization are conducted to enhance detection accuracy among other performance parameters. Detection analysis demonstrated the sensor’s ability to resolve changes in hemoglobin concentration through distinct shifts in transmittance and reflectance spectra. The resulting sensor exhibits enhanced sensitivity of 3500nmRIU⁻¹ to infrared energy, maximum FOM of 17.6, and detection limits of 0.05 among other performance parameters. Furthermore, machine learning optimization using 1D convolutional neural network regression is employed to predict the sensor’s behavior achieving high accuracy with maximum R² scores ranging up to 1. The sensor design exhibits remarkable potential for applications requiring highly sensitive and precise hemoglobin monitoring in medical diagnostics and healthcare.