2025-07-21 中国科学院(CAS)
<関連情報>
- https://english.cas.cn/newsroom/research_news/chem/202507/t20250723_1048178.shtml
- https://www.pnas.org/doi/10.1073/pnas.2413060122
グラフェン酸化物膜内のイオンの閉じ込めにより、神経形態的人工味覚を実現 Confinement of ions within graphene oxide membranes enables neuromorphic artificial gustation
Yuchun Zhang, Lin Liu, Yu Qiao, +2 , and Yong Yan
Proceedings of the National Academy of Sciences Published: July 7, 2025
DOI:https://doi.org/10.1073/pnas.2413060122
Significance
The development of fluidic neuromorphic components and perceiving systems for emulating the function of biological nervous systems is imperative and challenging. This study introduces a graphene oxide ionic memristive device capable of performing both sensory and computing functions. Experimental and theoretical simulations indicate that the prolonged retention of ions within graphene oxide channels accounts for the memristive characteristics. Importantly, this device can be used to construct a reservoir-computing gustatory system, which can effectively perceive sweet, salty, bitter, and sour flavors. Our system-level implementation of artificial gustation—although it is a proof-of-concept demonstration—should represent a substantial advancement toward future intelligent perceptions and/or taste reconstruction.
Abstract
Introducing neuromorphic computing paradigms into taste-sensing technology will bring unprecedented opportunities for developing new hardware architectures with perceptual intelligence. Constructing the biomimetic gustatory system, however, remains a challenge due to the scarcity of suitable components operating under wet conditions. Here, we report that ion confinement within the layered graphene oxide membranes can be used to develop a memristive device capable of implementing both synaptic function and chemical sensing. The continuum model and ion dynamics characterizations demonstrate that interfacial adsorption–desorption slows down ion transport and leads to memristive behavior. Based on this nanofluidic device, we built an artificial gustatory system in the physiological environment, which can efficiently classify different flavors according to the reservoir computing algorithm. Our results suggest a paradigm for in-sensor computing in liquid.
