Source abstract
Abstract
Cancer remains a leading global health threat, with early detection critical to improving survival rates. However, conventional diagnostic methods suffer from limitations in sensitivity, specificity, and accessibility, particularly in low- and middle-income countries. This study presents a next-generation metasurface biosensor integrating MXene (Ti3C2Tx), black phosphorus, graphene, and noble metals (Au and Ag) for high-precision cancer detection in the terahertz (THz) regime. Numerical simulations and experimental validations demonstrate the sensor’s exceptional performance: a maximum sensitivity of 2000 GHz/refractive index unit (RIU), a strong linear correlation between resonance frequency and refractive index (R2 = 0.952 76), and a figure of merit up to 29.851 RIU−1. Parametric optimizations, including graphene chemical potential (0.1–0.9 eV) and angle of incidence (0°–80°), further enhance spectral tunability and absorption efficiency. Compared to state-of-the-art biosensors, this design outperforms in sensitivity, detection accuracy (15), and adaptability for point-of-care applications. Integration with machine learning confirms robust agreement between experimental and theoretical data (R2 = 0.96–0.97), highlighting its potential to revolutionize early cancer diagnostics and reduce global health disparities.
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Affiliations
Department of Biology, College of Science, Princess Nourah bint Abdulrahman University 1 , P.O. Box 84428, Riyadh 11671,
Photonic and Phononic Crystals Lab., Physics Department, Faculty of Science, Beni-Suef University 2 , Beni-Suef 62512,
Physics Department, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU) 3 , Riyadh 11623,
Department of Mechanical and Industrial Engineering, College of Engineering, National University of Science and Technology 4 , Sultanate of Oman,
Department of Optics and Optical Engineering, University of Science and Technology of China 5 , 96 Jinzhai Road, Hefei 230026,
Department of Electrical and Communication Engineering, National University of Science and Technology 6 , Muscat,
INFN-Laboratori Nazionali di Frascati 7 , Via E. Fermi 54, 00044 Frascati,
Funding
Princess Nourah Bint Abdulrahman University