# Redox-based ion-gating reservoir consisting of (104) oriented LiCoO2 film, assisted by physical masking

https://mdr.nims.go.jp/datasets/d6acba9b-0df0-4264-a1cf-26dea81b1db5

## File

- [Shibata_et_al-2023-Scientific_Reports.pdf](https://mdr.nims.go.jp/filesets/5fa15e99-defe-4cb2-841d-7e4640a221ae/download) ([Detail](https://mdr.nims.go.jp/filesets/5fa15e99-defe-4cb2-841d-7e4640a221ae.md))

## Id

d6acba9b-0df0-4264-a1cf-26dea81b1db5

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-12-11T09:58:54.789816Z

## Updated at

2024-12-12T07:30:42.859180Z

## Published at

2024-12-12T07:30:42.983125Z

## Doi



## First published url

https://doi.org/10.1038/s41598-023-48135-z

## Date published

2023-11-29

## Recorded date published



## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Redox-based ion-gating reservoir consisting of (104) oriented LiCoO2 film,
    assisted by physical masking
  title_type: original
  lang: en

## Description

- description: Reservoir computing (RC) is a machine learning framework suitable for
    processing time series data, and is a computationally inexpensive and fast learning
    model. A physical reservoir is a hardware implementation of RC using a physical
    system, which is expected to become the social infrastructure of a data society
    that needs to process vast amounts of information. Ion-gating reservoirs (IGR)
    are compact and suitable for integration with various physical reservoirs, but
    the prediction accuracy and operating speed of redox-IGRs using WO3 as the channel
    are not sufficient due to irreversible Li+ trapping in the WO3 matrix during operation.
    Here, in order to enhance the computation performance of redox-IGRs, we developed
    a redox-based IGR using a (104) oriented LiCoO2 thin film with high electronic
    and ionic conductivity as a trap-free channel material. The subject IGR utilizes
    resistance change that is due to a redox reaction (LiCoO2 ⟺ Li1−xCoO2 + xLi+ +
    xe−) with the insertion and desertion of Li+. The prediction error in the subject
    IGR was reduced by 72% and the operation speed was increased by 4 times compared
    to the previously reported WO3, which changes are due to the nonlinear and reversible
    electrical response of LiCoO2 and the high dimensionality enhanced by a newly
    developed physical masking technique. This study has demonstrated the possibility
    of developing high-performance IGRs by utilizing materials with stronger nonlinearity
    and by increasing output dimensionality.
  description_type: abstract
  lang: und

## Creator

- name: Kaoru Shibata
  role: author
  orcid: https://orcid.org/0009-0002-4771-6375
  organization: National Institute for Materials Science
- name: Daiki Nishioka
  role: author
  orcid: https://orcid.org/0000-0002-3369-7700
  organization: National Institute for Materials Science
- name: Wataru Namiki
  role: author
  orcid: https://orcid.org/0000-0003-4053-7366
  organization: National Institute for Materials Science
- name: Takashi Tsuchiya
  role: author
  orcid: https://orcid.org/0000-0002-6950-6160
  organization: National Institute for Materials Science
- name: Tohru Higuchi
  role: author
- name: Kazuya Terabe
  role: author
  orcid: https://orcid.org/0000-0003-3988-3456
  organization: National Institute for Materials Science

## Contact agent



## Publisher

organization: Springer Science and Business Media LLC

## Managing organization



## Keyword

- subject: reservoir computing
  schema: not_defined
- subject: ionics
  schema: not_defined
- subject: redox transistor
  schema: not_defined
- subject: ion-gating reservoir
  schema: not_defined
- subject: neuromorphic computing
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin



## Embargo



## Journal

- title: Scientific Reports
  issn: '20452322'
  volume: '13'
  issue: '1'
  article_number: '21060'

## Conference



## Related item



## Funding

- identifier: JP22H04625
  funder_name: MEXT | Japan Society for the Promotion of Science
- identifier: JP22KJ2799
  funder_name: MEXT | Japan Society for the Promotion of Science
- funder_name: Iketani Science and Technology Foundation

## 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



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## Custom property



## Fileset

- id: 5fa15e99-defe-4cb2-841d-7e4640a221ae
  filename: Shibata_et_al-2023-Scientific_Reports.pdf
  content_type: application/pdf
  size: 10827332
  md5: 3748cad8f52fc31b1ebdd465b9a135d7

## Thumbnail

fileset_id: 5fa15e99-defe-4cb2-841d-7e4640a221ae
filename: Shibata_et_al-2023-Scientific_Reports.pdf