Terahertz metamaterial-based perfect absorber biosensor with AI integration and multiband double-negative response for early non-melanoma skin cancer detection

dc.contributor.authorHamza, Musa N.
dc.contributor.authorAlibakhshikenari, Mohammad
dc.contributor.authorVirdee, Bal
dc.contributor.authorJayanthi, Renu Karthick Rajaguru
dc.contributor.authorLavadiya, Sunil
dc.contributor.authorDin, Iftikhar ud
dc.contributor.authorSanches, Bruno
dc.contributor.authorKoziel, Slawomir
dc.contributor.authorPanda, Abinash
dc.contributor.authorFarmani, Ali
dc.contributor.authorMezache, Zinelabiddine
dc.contributor.authorShamsan, Zaid Ahmed
dc.contributor.authorZakeri, Hassan
dc.contributor.authorHung, Tran Huy
dc.contributor.departmentDepartment of Engineering
dc.date.accessioned2026-09-14T10:08:01Z
dc.date.available2026-09-14T10:08:01Z
dc.date.issued2026-03-01
dc.descriptionPublisher Copyright: Copyright © 2026. Published by Elsevier B.V.en
dc.description.abstractThis paper presents a multiband terahertz metamaterial-based biosensor designed as a perfect absorber for the early detection of non-melanoma skin cancer. The proposed structure integrates a meticulously engineered multilayer architecture that achieves simultaneous negative permittivity, permeability, and refractive index (double-negative response) within the 0–5 THz range. Unlike conventional terahertz sensors that rely on one or two resonances, our design produces approximately twenty high-Q absorption peaks, with eleven exceeding 95%, four exceeding 97%, and two surpassing 99% absorption. These dense resonances enhance field localization and increase sensitivity to dielectric variations in biological tissue. Numerical simulation demonstrates a sensitivity of 629.95 THz/RIU and a figure of merit of 15,179.59 RIU−1, significantly outperforming existing metamaterial biosensors. To further improve diagnostic capability, a broadband spectral-analysis framework is incorporated to analyze the full terahertz spectral response using Euclidean distance, mean squared error, and correlation metrics. The Spectral classification framework reliably distinguishes between healthy and cancerous tissue profiles, enabling an automated and robust detection. The biosensor's performance is further validated by incorporating it into a microwave imaging system, which provides spatial confirmation of cancerous tissue. These results establish the proposed device as a compact, high-resolution, and non-invasive platform for the early diagnosis of non-melanoma skin cancer.en
dc.description.versionPeer revieweden
dc.format.extent20450369
dc.format.extent
dc.identifier.citationHamza, M N, Alibakhshikenari, M, Virdee, B, Jayanthi, R K R, Lavadiya, S, Din, I U, Sanches, B, Koziel, S, Panda, A, Farmani, A, Mezache, Z, Shamsan, Z A, Zakeri, H & Hung, T H 2026, 'Terahertz metamaterial-based perfect absorber biosensor with AI integration and multiband double-negative response for early non-melanoma skin cancer detection', Results in Optics, vol. 24, 101082. https://doi.org/10.1016/j.rio.2026.101082en
dc.identifier.doi10.1016/j.rio.2026.101082
dc.identifier.issn2666-9501
dc.identifier.other250807980
dc.identifier.other9c10abf4-588c-4826-809a-aeff05692c28
dc.identifier.other105044535909
dc.identifier.otherunpaywall: 10.1016/j.rio.2026.101082
dc.identifier.urihttps://hdl.handle.net/20.500.11815/8256
dc.language.isoen
dc.relation.ispartofseriesResults in Optics; 24()en
dc.relation.urlhttps://www.scopus.com/pages/publications/105044535909en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.subjectDouble-negative metamaterialsen
dc.subjectMetamaterial absorberen
dc.subjectMicrowave imagingen
dc.subjectMultiband resonanceen
dc.subjectNon-melanoma skin canceren
dc.subjectSimilarity-based classification frameworken
dc.subjectSpectral classificationen
dc.subjectTerahertz biosensoren
dc.subjectAtomic and Molecular Physics, and Opticsen
dc.titleTerahertz metamaterial-based perfect absorber biosensor with AI integration and multiband double-negative response for early non-melanoma skin cancer detectionen
dc.type/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/articleen

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