Solid-state nanopore sensor combined with time series analysis algorithms for nanoparticles discrimination

Yiheng Che; Zhenhua Li; Lei Wang; Sijia Xie; Chang Chen

doi:10.1117/12.2678954

15 May 2023 Solid-state nanopore sensor combined with time series analysis algorithms for nanoparticles discrimination

Yiheng Che, Zhenhua Li, Lei Wang, Sijia Xie, Chang Chen

Proceedings Volume 12699, Third International Conference on Sensors and Information Technology (ICSI 2023); 126990W (2023) https://doi.org/10.1117/12.2678954
Event: International Conference on Sensors and Information Technology (ICSI 2023), 2023, Xiamen, China

Abstract

This work develops a solid-state nanopore sensing system for the detection of biological nanoparticles. A silicon-based silicon nitride solid-state nanopore chip with a low aspect ratio was designed and made by the microfabrication technique. As a demonstration, the chip was used to characterize and analyze carboxyl-modified polystyrene particles. Time series analysis was used to construct the characteristics of the current signal during nanoparticle translocation. Time series analysis based on machine learning algorithms combined with Bayesian optimization was used to perform signal discrimination of particles of different sizes. This sensing technique has promise for identifying the characteristics of nanoparticles like proteins, viruses.

Citation Download Citation

Yiheng Che, Zhenhua Li, Lei Wang, Sijia Xie, and Chang Chen "Solid-state nanopore sensor combined with time series analysis algorithms for nanoparticles discrimination", Proc. SPIE 12699, Third International Conference on Sensors and Information Technology (ICSI 2023), 126990W (15 May 2023); https://doi.org/10.1117/12.2678954

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