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Design Strategies for Carbon Nanotube-Based Biosensors in Complex Biological Media: From Interfacial Physics to System-Level Translation

Year: 2026
Type: article
Abstract: Carbon nanotube (CNT) biosensors offer sensitive electrical and near-infrared optical readouts, yet performance in defined buffers does not necessarily translate to reliable measurements in complex biological media. Ionic screening, nonspecific adsorption, variable sample composition, and transport limitations can disrupt the relationship between molecular recognition and sensor output. This review examines how interfacial engineering and system-level design address these constraints across serum, plasma, whole blood, saliva, urine, and intracellular or tissue environments. We connect receptor orientation and dimensions, antifouling coatings, and designed corona phases to their effects on analyte accessibility, transduction, and signal stability. We then discuss sample separation, enrichment, and microfluidic delivery as integral parts of the measurement workflow. Electrical CNT architectures and optical single-walled CNT sensors are compared in terms of their operating mechanisms, matrix-dependent limitations, and validation requirements. Particular attention is given to distinguishing direct sensing from CNT-assisted sample preparation, optical visibility from selective analyte measurement, and fortified-sample testing from clinical validation. We also examine data-driven recognition discovery, manufacturing reproducibility, and reporting practices needed for meaningful comparison across platforms. The central design principle is to optimize the complete sample-to-answer process around the dominant limitation in the intended biological environment. Progress toward practical CNT biosensing therefore requires matrix-matched calibration, explicit characterization of sample conditioning, and independent validation across devices, batches, and biological specimens.
Source: Sensors
Language: English
Field: Chemistry
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7225613788
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Cites: 91
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