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Nanopore Impedance Spectroscopy Reveals Electrical Properties of Single Nanoparticles for Detecting and Identifying Pathogenic Viruses.
Kitta, Kazuki; Sakamoto, Maami; Hayakawa, Kei; Nukazuka, Akira; Kano, Kazuhiko; Yamamoto, Takatoki.
Afiliação
  • Kitta K; Mechanical Engineering, Tokyo Institute of Technology, Ishikawadai 1-314, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
  • Sakamoto M; Mechanical Engineering, Tokyo Institute of Technology, Ishikawadai 1-314, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
  • Hayakawa K; Material Research and Innovation Division, DENSO CORPORATION, 1-1 Showa-cho, Kariya, Aichi 448-8661, Japan.
  • Nukazuka A; Material Research and Innovation Division, DENSO CORPORATION, 1-1 Showa-cho, Kariya, Aichi 448-8661, Japan.
  • Kano K; Material Research and Innovation Division, DENSO CORPORATION, 1-1 Showa-cho, Kariya, Aichi 448-8661, Japan.
  • Yamamoto T; Mechanical Engineering, Tokyo Institute of Technology, Ishikawadai 1-314, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
ACS Omega ; 8(16): 14684-14693, 2023 Apr 25.
Article em En | MEDLINE | ID: mdl-37125101
ABSTRACT
In the conventional nanopore method, direct current (DC) is used to study molecules and nanoparticles; however, it cannot easily discriminate between materials with similarly sized particles. Herein, we developed an alternating current (AC)-based nanopore method to measure the impedance of a single nanoparticle and distinguish between particles of the same size based on their material characteristics. We demonstrated the performance of this method using impedance measurements to determine the size and frequency characteristics of various particles, ranging in diameter from 200 nm to 1 µm. Furthermore, the alternating current method exhibited high accuracy for biosensing applications, identifying viruses with over 85% accuracy using single-particle measurement and machine learning. Therefore, this novel nanopore method is useful for applications in materials science, biology, and medicine.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article