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Solution-Gated Thin Film Transistor Biosensor-Based SnO2 Amorphous Film for Label-Free Detection of Epithelial Cell
Yaxing Zhang1, Zhiwei Cai1, Rong Zou2
1Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials, Hubei Key Laboratory of Polymer Materials, School of Materials Science and Engineering, Hubei University, Wuhan 430062, China.
Abstract:
Epithelial cell adhesion molecule (EpCAM) was considered to be an important marker of multiple tumors, and its high expression is closely related to the early diagnosis and treatment of tumors. At present, metal oxide semiconductors have become a key component of biosensor and bioelectronics technology. Tin oxide shows great potential for development because of its nontoxic, nonpolluting, low price, and excellent electrical properties. In this study, a novel SnO2 solution-gated thin film transistor (SGTFT) biosensor for the specific detection of EpCAM was successfully developed using SnO2 film prepared by the sol-gel method as the channel material. By selecting the optimal thickness of 100 nm SnO2 film as the channel material, the transconductance value (gm) reached 1432 μS, and the threshold voltage (Vth) remained stable at 0.288 V. In order to achieve qualitative and quantitative detection of EpCAM, SnO2 films were subjected to a specific chemical treatment to fix the aptamer. Through a specific recognition between the aptamer and EpCAM, the gate voltage changes were triggered to regulate the channel current of the device. FE-SEM, EIS, XPS, and electrical performance tests were employed to track and measure the modification process. Based on the optimizations described above, the prepared SGTFT exhibited high detection sensitivity (14.6 mV·dec-1), the limit of detection (LOD) down to 24.4 pg/mL, and the calibration curves in the range of 0.02 ng/mL-500 ng/mL for EpCAM sensing. The developed SnO2-SGTFT biosensor is anticipated to provide a new highly sensitive and specific detection platform for health monitoring and disease diagnosis.
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