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The enormous energy consumption of modern machine learning technologies, such as deep learning and generative artificial intelligence, is one of the most critical concerns of the time. To solve this problem, physical reservoir computing, which uses the non-linear dynamics exhibited by mechanical systems such as materials and devices as a computational resource for highly efficient information processing, has attracted much attention in recent years. In particular, ion-gated transistors, a group of devices that control electrical conductivity using electrochemical mechanisms such as electric double layers and redox, show very high computational performance with complex and diverse output properties in contrast to their simple structures, due to the complexity of the physical and chemical processes involved. This research provides an overview of physical reservoir computing using ion-gating transistors, focusing on the materials used, various computational tasks, and operating mechanisms.

Rights:

• Creative Commons BY Attribution 4.0 International
  

Keyword: reservoir computing, ion-gating reservoir, solid state ionics, ion-gating transistor

Date published: 2024-11-20

Publisher: Wiley

Journal:

• Advanced Electronic Materials (ISSN: 2199160X) vol. 10 issue. 12

Funding:

• Japan Society for the Promotion of Science 24KJ0229
• Precursory Research for Embryonic Science and Technology JPMJPR23H4

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

MDR DOI:

First published URL: https://doi.org/10.1002/aelm.202400625

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Updated at: 2024-12-13 12:30:51 +0900

Published on MDR: 2024-12-13 12:30:51 +0900