Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime
Abstract This study presents the design and analysis of a biosensor for COVID-19 detection, integrating graphene metasurfaces with gold, silver, and GST materials. The proposed sensor architecture combines a square ring resonator with a circular ring resonator, optimized through COMSOL Multiphysics...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-92991-w |
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| author | Hussein A. Elsayed Jacob Wekalao Ahmed Mehaney Haifa E. Alfassam Mostafa R. Abukhadra Ali Hajjiah Wail Al Zoubi |
| author_facet | Hussein A. Elsayed Jacob Wekalao Ahmed Mehaney Haifa E. Alfassam Mostafa R. Abukhadra Ali Hajjiah Wail Al Zoubi |
| author_sort | Hussein A. Elsayed |
| collection | DOAJ |
| description | Abstract This study presents the design and analysis of a biosensor for COVID-19 detection, integrating graphene metasurfaces with gold, silver, and GST materials. The proposed sensor architecture combines a square ring resonator with a circular ring resonator, optimized through COMSOL Multiphysics simulations in the infrared regime. The sensor demonstrates exceptional performance characteristics, with absorption values exceeding 99.5% in the primary detection band (4.2–4.6 μm) and approximately 97.5% in the secondary band (5.0–5.5 μm). The device exhibits high sensitivity (4000 nm/RIU), a detection limit of 0.078, and a figure of merit of 16.000 RIU⁻¹ when utilizing crystalline GST as the substrate material. The sensor’s performance was further enhanced through machine learning optimization using XGBoost regression, achieving perfect correlation (R² = 100%) between predicted and experimental values across various operational parameters. The dual-band detection mechanism, combined with the integration of advanced materials and machine learning optimization, offers a promising platform for rapid, label-free, and highly sensitive COVID-19 detection. This research contributes to the development of next-generation biosensing technologies for viral detection and disease diagnosis. |
| format | Article |
| id | doaj-art-cc6b2cfdfce447a2910e08fbbaa13eb8 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-cc6b2cfdfce447a2910e08fbbaa13eb82025-08-20T02:56:15ZengNature PortfolioScientific Reports2045-23222025-03-0115112610.1038/s41598-025-92991-wGraphene metasurfaces biosensor for COVID-19 detection in the infra-red regimeHussein A. Elsayed0Jacob Wekalao1Ahmed Mehaney2Haifa E. Alfassam3Mostafa R. Abukhadra4Ali Hajjiah5Wail Al Zoubi6Department of Physics, College of Science, University of Ha’ilDepartment of Optics and Optical Engineering, University of Science and Technology of ChinaPhysics Department, Faculty of Science, Beni-Suef UniversityDepartment of Biology, college of Science, Princess Nourah bint Abdulrahman UniversityMaterials Technologies and their applications Lab, Faculty of Science, Beni-Suef UniversityDepartment of Electrical Engineering, College of Engineering and Petroleum, Kuwait UniversityMaterials Electrochemistry Laboratory, School of Materials Science and Engineering, Yeungnam UniversityAbstract This study presents the design and analysis of a biosensor for COVID-19 detection, integrating graphene metasurfaces with gold, silver, and GST materials. The proposed sensor architecture combines a square ring resonator with a circular ring resonator, optimized through COMSOL Multiphysics simulations in the infrared regime. The sensor demonstrates exceptional performance characteristics, with absorption values exceeding 99.5% in the primary detection band (4.2–4.6 μm) and approximately 97.5% in the secondary band (5.0–5.5 μm). The device exhibits high sensitivity (4000 nm/RIU), a detection limit of 0.078, and a figure of merit of 16.000 RIU⁻¹ when utilizing crystalline GST as the substrate material. The sensor’s performance was further enhanced through machine learning optimization using XGBoost regression, achieving perfect correlation (R² = 100%) between predicted and experimental values across various operational parameters. The dual-band detection mechanism, combined with the integration of advanced materials and machine learning optimization, offers a promising platform for rapid, label-free, and highly sensitive COVID-19 detection. This research contributes to the development of next-generation biosensing technologies for viral detection and disease diagnosis.https://doi.org/10.1038/s41598-025-92991-wCOVID-19 biosensorGraphene metasurfacesPhase change materialsMachine learning optimizationDual-Band detectionLabel-free sensing |
| spellingShingle | Hussein A. Elsayed Jacob Wekalao Ahmed Mehaney Haifa E. Alfassam Mostafa R. Abukhadra Ali Hajjiah Wail Al Zoubi Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime Scientific Reports COVID-19 biosensor Graphene metasurfaces Phase change materials Machine learning optimization Dual-Band detection Label-free sensing |
| title | Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime |
| title_full | Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime |
| title_fullStr | Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime |
| title_full_unstemmed | Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime |
| title_short | Graphene metasurfaces biosensor for COVID-19 detection in the infra-red regime |
| title_sort | graphene metasurfaces biosensor for covid 19 detection in the infra red regime |
| topic | COVID-19 biosensor Graphene metasurfaces Phase change materials Machine learning optimization Dual-Band detection Label-free sensing |
| url | https://doi.org/10.1038/s41598-025-92991-w |
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