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Pathogens pose a substantial threat to human health and food safety, and Escherichia coli (E. coli) is a commonly encountered pathogen that is widely distributed. However, there is an unmet need to develop a simple and rapid method to detect E. coli. Here, we present a floating-gate (FG) carbon nanotube field-effect transistor (CNTFET) biosensor for the rapid identification of E. coli BL21. The dielectric layer of the CNTFET was functionalized with a potassium ion-selective membrane, and when combined with T4 bacteriophage as the target recognization element, it enables specific detection of the target pathogen. The sensor achieves a rapid response time of 50 s and a detection limit as low as 0.2 cfu/mL of E. coli BL21, with minimal cross-reactivity toward non-target pathogens. Moreover, the FG-CNTFET biosensor demonstrates low cost, high sensitivity, and fast performance in real-world samples, offering a promising platform for pathogen detection.

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Carbon Nanotube-Based Field Effect Transistors for High-Sensitivity Detection of Pathogens in Real Water Samples

  • 会议论文

  • 发表日期：

    2026年

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  • Anhui Wang,
  • Qiaoshu Chen

摘要

Pathogens pose a substantial threat to human health and food safety, and Escherichia coli (E. coli) is a commonly encountered pathogen that is widely distributed. However, there is an unmet need to develop a simple and rapid method to detect E. coli. Here, we present a floating-gate (FG) carbon nanotube field-effect transistor (CNTFET) biosensor for the rapid identification of E. coli BL21. The dielectric layer of the CNTFET was functionalized with a potassium ion-selective membrane, and when combined with T4 bacteriophage as the target recognization element, it enables specific detection of the target pathogen. The sensor achieves a rapid response time of 50 s and a detection limit as low as 0.2 cfu/mL of E. coli BL21, with minimal cross-reactivity toward non-target pathogens. Moreover, the FG-CNTFET biosensor demonstrates low cost, high sensitivity, and fast performance in real-world samples, offering a promising platform for pathogen detection.