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

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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.

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Data Availability

The data supporting the findings in this work are available from the corresponding author with a reasonable request.

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Acknowledgements

The authors would like to express their gratitude to the National Forensic Sciences University for granting access to the digital computer laboratory for this research, as well as to the ICCR for their scholarship support.

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Authors and Affiliations

  1. School of Engineering and Technology, National Forensic Sciences University, Gandhinagar, 382007, Gujarat, India

    Jacob Wekalao

  2. School of Digital Forensics and Cyber Security, National Forensic Sciences University, Gandhinagar, 382007, Gujarat, India

    Ngaira Mandela

  3. School of Behavioral Sciences, National Forensic Sciences University, Gandhinagar, 382007, Gujarat, India

    Obed Apochi

  4. School of Pharmacy, National Forensic Sciences University, Gandhinagar, 382007, Gujarat, India

    Costable Lefu

  5. School of Forensic Sciences, National Forensic Sciences University, Gandhinagar, 382007, Gujarat, India

    Tobias Topisia

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Contributions

“Conceptualization, JW,NM; Methodology,JW,NM,OA; Software.JW,CL,OA; Validation, all authors; Writing—original draft preparation, All authors; Formal Analysis, JW,TT,CL; Writing—review and editing, All Authors; All authors have read and agreed to the published version of the manuscript.”

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Wekalao, J., Mandela, N., Apochi, O. et al. Nanoengineered Graphene Metasurface Surface Plasmon Resonance Sensor for Precise Hemoglobin Detection with AI-Assisted Performance Prediction. Plasmonics (2024). https://doi.org/10.1007/s11468-024-02489-w

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