The signal-to-noise ratio improvement of solid-state nanopore sensors

ShiNian Leng; YingMin Qu; Ting Weng; ShaoXi Fang; Mohamed Bahri; XiaoQing Zeng; HuaMing Zhang; DeQiang Wang; YaJie Yin

doi:10.1117/12.2668074

20 April 2023 The signal-to-noise ratio improvement of solid-state nanopore sensors

ShiNian Leng, YingMin Qu, Ting Weng, ShaoXi Fang, Mohamed Bahri, XiaoQing Zeng, HuaMing Zhang, DeQiang Wang, YaJie Yin

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126020D (2023) https://doi.org/10.1117/12.2668074
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

Compared with biological nanopores, solid-state nanopores（SSN） have advantages in chemical, mechanical, and thermal stability, pore size tunability and integration, and detect a broader range of targets. However, the current problems of low signal-to-noise ratio (SNR), inefficient preparation, and poor reproducibility of solid-state nanopores remain unsolved, limiting their application to replace biological nanopores as the main sensor devices. In this paper, we address the low SNR problems of solid-state nanopores, introduce the recent research done by researchers to improve the SNR of solidstate nanopores, make a breakdown into the existing resistive pulse detection field, and give an outlook on various sensing detection methods based on nanopores.

Citation Download Citation

ShiNian Leng, YingMin Qu, Ting Weng, ShaoXi Fang, Mohamed Bahri, XiaoQing Zeng, HuaMing Zhang, DeQiang Wang, and YaJie Yin "The signal-to-noise ratio improvement of solid-state nanopore sensors", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126020D (20 April 2023); https://doi.org/10.1117/12.2668074

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