Download all files (1.13 MB)

Collection

Citation

Description:

Physical reservoir computing (PRC) is helpful for power reduction in machine learning technology, although the challenge is to improve computational performance. In this study, we developed a PRC device utilizing ion-electron coupled dynamics in an electric double layer transistor (EDLT) consisting of monolayer graphene channels and a Li+ conducting inorganic oxide thin film. The ambipolar transfer characteristics of graphene channels in the EDLT obtained complex and diverse drain current responses, providing high information processing capacity and high PRC performance in the nonlinear autoregressive moving average (NARMA) task.

Rights:

• Creative Commons BY Attribution 4.0 International
  

Keyword: physical reservoir computing, ion-gating reservoir, information capacity analysis

Date published: 2025-02-01

Publisher: IOP Publishing

Journal:

• Applied Physics Express (ISSN: 18820786) vol. 18 issue. 2 024501

Funding:

• JFE 21st Century Foundation
• Ministry of Education, Culture, Sports, Science and Technology JPMXP1224NM5236
• Precursory Research for Embryonic Science and Technology JPMJPR23H4
• Japan Society for the Promotion of Science JP24KJ0229

Manuscript type: Publisher's version (Version of record)

MDR DOI:

First published URL: https://doi.org/10.35848/1882-0786/adb19b

Related item:

Other identifier(s):

Contact agent:

Updated at: 2025-12-11 12:30:03 +0900

Published on MDR: 2025-02-25 16:30:30 +0900