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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.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: reservoir computing, ion-gating reservoir, solid state ionics, ion-gating transistor

刊行年月日: 2024-11-20

出版者: Wiley

掲載誌:

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

研究助成金:

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

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1002/aelm.202400625

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更新時刻: 2024-12-13 12:30:51 +0900

MDRでの公開時刻: 2024-12-13 12:30:51 +0900