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In-electrode faraday cage-type biosensors: Enclosing biorecognition for ultra-sensitive electrochemical and
Nastaran Arab1, Andrea Salis2, Morteza Hosseini3
1Nanobiosensors Lab, Department of Nanobiotechnology and Biomimetics, School of Life Science Engineering, College of Interdisciplinary Science and Technology, University of Tehran, Tehran, 1439817435, Iran.
Abstract:
Electrochemiluminescence (ECL) and electrochemical biosensors traditionally rely on on-electrode, sandwich-type architectures in which only a small fraction of immobilized labels resides within the electrochemically active region, fundamentally limiting sensitivity. In recent years, a new class of Faraday-cage-type (FCT) or in-electrode biosensors has emerged as a powerful strategy to overcome these distance-dependent constraints. These systems employ conductive two-dimensional (2D) nanomaterials co-functionalized with biorecognition elements and signal labels that directly overlap the electrode surface, effectively extending the electroactive interface and relocating the outer Helmholtz plane to the surface of the 2D scaffold. As a result, all luminophores are positioned within the electron-transfer zone, enabling full utilization of labelling density and achieving substantial gains in ECL and electrochemical signal output. This review provides a comprehensive fabrication of FCT biosensors, covering their mechanistic foundations, structural components, and the diverse 2D nanomaterials used to construct high-performance signal units. We summarize recent advances in FCT-based detection of proteins, peptides, pathogens, and nucleic acids, highlighting how these architectures address long-standing limitations of conventional sandwich assays. Finally, we discuss current challenges and future opportunities for the development, standardization, and practical translation of FCT biosensing platforms. The rapid evolution of this field underscores the growing analytical potential of in-electrode architectures for ultrasensitive and clinically relevant biomarker detection.
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