Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime DOI Creative Commons
Hussein A. Elsayed, Jacob Wekalao, Ahmed Mehaney

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 12, 2025

This study presents the design and analysis of a biosensor for COVID-19 detection, integrating graphene metasurfaces with gold, silver, GST materials. The proposed sensor architecture combines square ring resonator circular resonator, optimized through COMSOL Multiphysics simulations in infrared regime. demonstrates exceptional performance characteristics, absorption values exceeding 99.5% primary detection band (4.2–4.6 μm) approximately 97.5% secondary (5.0–5.5 μm). device exhibits high sensitivity (4000 nm/RIU), limit 0.078, figure merit 16.000 RIU⁻¹ when utilizing crystalline as substrate material. sensor's was further enhanced machine learning optimization using XGBoost regression, achieving perfect correlation (R² = 100%) between predicted experimental across various operational parameters. dual-band mechanism, combined integration advanced materials optimization, offers promising platform rapid, label-free, highly sensitive detection. research contributes to development next-generation biosensing technologies viral disease diagnosis.

Language: Английский

Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime DOI Creative Commons
Hussein A. Elsayed, Jacob Wekalao, Ahmed Mehaney

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 12, 2025

This study presents the design and analysis of a biosensor for COVID-19 detection, integrating graphene metasurfaces with gold, silver, GST materials. The proposed sensor architecture combines square ring resonator circular resonator, optimized through COMSOL Multiphysics simulations in infrared regime. demonstrates exceptional performance characteristics, absorption values exceeding 99.5% primary detection band (4.2–4.6 μm) approximately 97.5% secondary (5.0–5.5 μm). device exhibits high sensitivity (4000 nm/RIU), limit 0.078, figure merit 16.000 RIU⁻¹ when utilizing crystalline as substrate material. sensor's was further enhanced machine learning optimization using XGBoost regression, achieving perfect correlation (R² = 100%) between predicted experimental across various operational parameters. dual-band mechanism, combined integration advanced materials optimization, offers promising platform rapid, label-free, highly sensitive detection. research contributes to development next-generation biosensing technologies viral disease diagnosis.

Language: Английский

Citations

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