Flexible and Conformable Carbon Nanotube Twin Transistors for Real-Time Glucose Biosensing
Source abstract
Abstract
Semiconductive single-walled carbon nanotube (SWNT)-based transistors have long and extensively been explored for sensing applications, biosensors in particular, but reproducible reliable results remain elusive. The random distribution of the nanotube network, as well as the variation of the network due to deformation or surrounding fluidic dynamics, leads to fluctuation of the channel current, which is difficult to control. The signal-to-noise ratio is thus low, and calibration is required. To mitigate this challenge, SWNT-based twin transistors are introduced, where one acts as a sensor and the other as a reference. The twin transistors share gate and source electrodes, and all of the source/drain electrodes are sealed by a parylene layer to minimize electrolytic leakage. A common-source amplifier circuit generates voltage signal readouts from the sensor and reference transistors, and the differential outputs reduce the noise level by 59%. Arrays of twin transistors were fabricated in a hybrid process involving photolithography, solution-based deposition of the SWNTs, and transfer to a polyurethane substrate. To demonstrate glucose biosensing, glucose oxidase was immobilized on the SWNTs in the sensor channels. A semipermeable Nafion layer was applied to embed the SWNT network. This resulted in a sensor that can deliver real-time detection of glucose in human serum and a 100% increase in normalized responses per decade of glucose concentrations between 100 μM and 100 mM. The response is proportional to the cubic root of glucose concentration, indicating that the redox electrons conducted by the nanotubes in the channel length direction contribute to the sensor response. A portable glucose-sensing system with flexible twin transistors is also demonstrated without the need for device-specific calibrations.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Neuroscience and Neural Engineering · Carbon Nanotubes in Composites · Electrochemical sensors and biosensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Materials Sciences and Engineering, Henry Samueli School of Engineering and Applied Science
University of California
Andrew and Peggy Cherng Department of Medical Engineering
California Institute of Technology
Funding
National Eye Institute · National Science Foundation
References (62)
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