High-sensitivity terahertz metasurface biosensor for multi-cancer detection: a machine learningenhanced approach using graphene–MXene– silver–copper hybrid architecture
| dc.contributor.author | Wekalao, Jacob | |
| dc.contributor.author | Elsayed, Hussein A. | |
| dc.contributor.author | Mehaney, Ahmed | |
| dc.contributor.author | Ochen, William | |
| dc.contributor.author | Othman, Sarah I. | |
| dc.contributor.author | Bellucc, Stefano | |
| dc.contributor.author | Amuthakkannan, Rajakannu | |
| dc.contributor.author | Ahmed, Ashour M. | |
| dc.contributor.author | Muheki, Jonas | |
| dc.date.accessioned | 2025-12-30T09:09:14Z | |
| dc.date.available | 2025-12-30T09:09:14Z | |
| dc.date.issued | 2025-12-19 | |
| dc.description | 22 p. | |
| dc.description.abstract | Early cancer detection requires highly sensitive diagnostic tools beyond the capabilities of conventional imaging and biopsy methods. We present a terahertz (THz) metasurface biosensor that integrates a copper-coated H-shaped resonator with three silver rectangular resonators enclosed within an MXene circular ring. The design incorporates complex electromagnetic interactions, nonlocal effects, and coupled-mode modelling to optimise performance. The biosensor achieves a sensitivity of 1000 GHz/RIU, a quality factor of 3.6–3.747, and a figure of merit up to 13.333 RIU⁻¹. It maintains stable absorption (52.789–53.804%) across 0.27–0.281 THz, with a linear resonance–refractive-index response (R² = 0.95276). Machine-learning optimisation of graphene chemical potential further enhances predictive accuracy (R² = 0.93). By enabling simultaneous detection of multiple cancer biomarkers through frequency-shift analysis, this noninvasive platform offers strong potential for real-time, early-stage cancer screening. | |
| dc.identifier.citation | Wekalao, Jacob ...et al. (2025) High-sensitivity terahertz metasurface biosensor for multi-cancer detection: a machine learning-enhanced approach using graphene–MXene–silver–copper hybrid architecture, Materials Technology, 40:1, 2585986, DOI: 10.1080/10667857.2025.2585986 | |
| dc.identifier.issn | 1066-7857 | |
| dc.identifier.issn | 1753-5557 | |
| dc.identifier.uri | https://doi.org/10.1080/10667857.2025.2585986 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12504/2697 | |
| dc.language.iso | en | |
| dc.publisher | Materials Technology Advanced Performance Materials | |
| dc.subject | Optical biosensor | |
| dc.subject | early diagnosis | |
| dc.subject | sensitivity enhancement | |
| dc.subject | electromagnetic coupling | |
| dc.subject | coupled mode theory | |
| dc.subject | refractive index sensing | |
| dc.subject | multi-cancer detection | |
| dc.subject | machine learning optimisation | |
| dc.title | High-sensitivity terahertz metasurface biosensor for multi-cancer detection: a machine learningenhanced approach using graphene–MXene– silver–copper hybrid architecture | |
| dc.type | Article |