# Physical reservoir computing with graphene-based solid electric double layer transistor and the information processing capacity analysis

https://mdr.nims.go.jp/datasets/1c555c29-4898-4edd-b872-e7ebacdfadf2

## File

- [Kitano_2025_Appl._Phys._Express_18_024501.pdf](https://mdr.nims.go.jp/filesets/634325af-f01c-478f-888e-2c4f5f1795d3/download) ([Detail](https://mdr.nims.go.jp/filesets/634325af-f01c-478f-888e-2c4f5f1795d3.md))
- [apexadb19bsupp1.pdf](https://mdr.nims.go.jp/filesets/6f2c9c3b-c27a-4846-839a-d1ef82121d51/download) ([Detail](https://mdr.nims.go.jp/filesets/6f2c9c3b-c27a-4846-839a-d1ef82121d51.md))

## Id

1c555c29-4898-4edd-b872-e7ebacdfadf2

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-02-23T01:08:23.799006Z

## Updated at

2025-12-11T03:30:03.927929Z

## Published at

2025-02-25T07:30:30.127194Z

## Doi



## First published url

https://doi.org/10.35848/1882-0786/adb19b

## Date published

2025-02-01

## Recorded date published

2025-2-1

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Physical reservoir computing with graphene-based solid electric double layer
    transistor and the information processing capacity analysis
  title_type: original
  lang: en

## Description

- 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.
  description_type: abstract
  lang: und

## Creator

- name: Hina Kitano
  role: author
  orcid: https://orcid.org/0009-0008-9132-0275
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Daiki Nishioka
  role: author
  orcid: https://orcid.org/0000-0002-3369-7700
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Kazuya Terabe
  role: author
  orcid: https://orcid.org/0000-0003-3988-3456
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Takashi Tsuchiya
  role: author
  orcid: https://orcid.org/0000-0002-6950-6160
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: IOP Publishing

## Managing organization



## Keyword

- subject: physical reservoir computing
  schema: not_defined
- subject: ion-gating reservoir
  schema: not_defined
- subject: information capacity analysis
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Applied Physics Express
  issn: '18820786'
  volume: '18'
  issue: '2'
  article_number: '024501'

## Conference



## Related item



## Funding

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

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: 634325af-f01c-478f-888e-2c4f5f1795d3
  filename: Kitano_2025_Appl._Phys._Express_18_024501.pdf
  content_type: application/pdf
  size: 1678514
  md5: d6422c4f5345420b0b4ab3c9ee038ac8
- id: 6f2c9c3b-c27a-4846-839a-d1ef82121d51
  filename: apexadb19bsupp1.pdf
  content_type: application/pdf
  size: 1816523
  md5: 12042154bb2cbb56effa94b039463391

## Thumbnail

fileset_id: 634325af-f01c-478f-888e-2c4f5f1795d3
filename: Kitano_2025_Appl._Phys._Express_18_024501.pdf