Article Two Orders of Magnitude Reduction in Computational Load Achieved by Ultrawideband Responses of an Ion-Gating Reservoir

Daiki Nishioka SAMURAI ORCID (National Institute for Materials Science) ; Hina Kitano SAMURAI ORCID (National Institute for Materials Science) ; Wataru Namiki SAMURAI ORCID (National Institute for Materials Science) ; Satofumi Souma ; Kazuya Terabe SAMURAI ORCID (National Institute for Materials Science) ; Takashi Tsuchiya SAMURAI ORCID (National Institute for Materials Science)

two-orders-of-magnitude-reduction-in-computational-load-achieved-by-ultrawideband-responses-of-an-ion-gating-reservoir.pdf
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Daiki Nishioka, Hina Kitano, Wataru Namiki, Satofumi Souma, Kazuya Terabe, Takashi Tsuchiya. Two Orders of Magnitude Reduction in Computational Load Achieved by Ultrawideband Responses of an Ion-Gating Reservoir. ACS Nano. 2025, 19 (42), 36896-36914. https://doi.org/10.1021/acsnano.5c06174

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(abstract)

The rising energy demands of conventional AI systems underscore the need for efficient computing technologies, such as brain-inspired computing. Physical reservoir computing (PRC), leveraging the nonlinear dynamics of physical systems for information processing, has emerged as a promising approach for neuromorphic computing. However, current PRC systems are constrained by narrow responsive time scales and limited performance. To address these challenges, an ion-gel/graphene electric double layer (EDL) transistor-based ion-gating reservoir (IGR) was developed. This IGR achieves a highly tunable and ultrawide time-scale response through the coexistence of fast EDL dynamics at the ion-gel/graphene interface and slower molecular adsorption dynamics on the graphene surface. Consequently, the system demonstrates an exceptionally broad responsive range, from 1 MHz to 20 Hz, while maintaining a high information processing capacity and adaptability across multiple time scales.

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Keyword: reservoir computing, neuromorphic computing, ion-gating reservoir, electric doube layer transistor, iontronics

Date published: 2025-10-28

Publisher: American Chemical Society (ACS)

Journal:

  • ACS Nano (ISSN: 1936086X) vol. 19 issue. 42 p. 36896-36914

Funding:

  • Ministry of Education, Culture, Sports, Science and Technology JPMXP1224NM5236
  • Precursory Research for Embryonic Science and Technology JPMJPR23H4
  • Japan Society for the Promotion of Science JP24KJ0299

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

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First published URL: https://doi.org/10.1021/acsnano.5c06174

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Updated at: 2025-12-09 16:30:21 +0900

Published on MDR: 2025-12-09 12:30:33 +0900

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