Evolution of tapered and TFBG biosensors toward hybrid architectures

Citation

Abushagur, Abdulfatah A.G. and Abushagur, Abdulmalik A. and Ibrahim@Ghazali, Siti Azlida and Bakar, Ahmad Ashrif A. and Azeman, Nur Hidayah and Hamzah, Abdulwahhab Essa and Yusoff, Zulfadzli (2026) Evolution of tapered and TFBG biosensors toward hybrid architectures. Sensors and Actuators Reports, 12. p. 100498. ISSN 26660539

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Abstract

Optical fiber biosensors have gained prominence as versatile platforms for label-free, real-time biochemical analysis. Among the various architectures, Tapered Optical Fibers (TOFs) and Tilted Fiber Bragg Gratings (TFBGs) stand out for their exceptional sensitivity and clinical adaptability. This review provides a comprehensive, comparative overview of these two approaches, examining their fundamental sensing mechanisms and recent application trends in detecting targets ranging from small protein biomarkers to massive, folded viral genomes. Particular attention is given to advances in plasmonic coupling, complex nanomaterial amplification, and microfluidic multiplexing. Furthermore, we critically analyzed the fundamental physical limitations that currently hinder broader commercial and in vivo deployment, specifically the shallow penetration depth of TFBGs, the environmental cross-sensitivity of TOFs, and the geometric reproducibility of both. Finally, we propose future perspectives in which the physical hybridization of tapered fibers with TFBGs, enabled by advanced fabrication techniques like post-taper femtosecond inscription, may address these bottlenecks. By combining such structural innovations with algorithmic data processing, hybrid architectures represent a promising direction for the next generation of robust, point-of-care biosensing technologies.

Item Type: Article
Uncontrolled Keywords: Tilted fiber Bragg grating, Tapered optical fiber, Surface plasmon resonance
Subjects: T Technology > TH Building construction > TH1000-1725 Systems of building construction Including fireproof construction, concrete construction
Divisions: Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 03 Sep 2026 08:33
Last Modified: 03 Sep 2026 08:33
URII: http://shdl.mmu.edu.my/id/eprint/16647

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