ICYS Research Fellow Dr. NISHIOKA has developed an AI device using ion gel and graphene that dramatically streamlines machine learning computations.
ICYS Research Fellow Dr. NISHIOKA has developed an AI device using ion gel and graphene that dramatically streamlines machine learning computations.
【Key Points of This Research】
Based on the concept of a physical reservoir—a computing paradigm that directly exploits physical phenomena occurring within materials and devices—we have developed a new AI device that integrates an ion gel with graphene.
By harnessing the diverse response dynamics and intrinsic complexity arising from ion–electron interactions at material interfaces, the device achieves computational performance comparable to deep learning while reducing the computational load by approximately two orders of magnitude.
It demonstrates significantly higher performance than conventional physical reservoirs across various information processing tasks, representing a new approach that utilizes nanoscale physical phenomena as computational resources and paving the way toward ultra–low-power, high-efficiency edge AI devices.
【Title of the Paper】
Two Orders of Magnitude Reduction in Computational Load Achieved by Ultrawideband Responses of an Ion-Gating Reservoir【Publication Details】
This research was presented by Dr. Daiki NISHIOKA, ICYS Research Fellow.
Published in ACS Nano on Oct. 13, 2025.
DOI: 10.1021/acsnano.5c06174