Ionic Potential Relaxation Effect in a Hydrogel Enabling Synapse-Like Information Processing

The next-generation brain-like intelligence based on neuromorphic architectures emphasizes learning the ionic language of the brain, aiming for efficient brain-like computation and seamless human-computer interaction. Ionic neuromorphic devices, with ions serving as information carriers, provide possibilities to achieve this goal. Soft and biocompatible ionic conductive hydrogels are an ideal substrate for constructing ionic neuromorphic devices, but it remains a challenge to modulate the ion transport behavior in hydrogels to mimic neuroelectric signals. Here, we describe an ionic potential relaxation effect in a hydrogel device prepared by sandwiching a layer of polycationic hydrogel (CH) between two layers of neutral hydrogel (NH), allowing this device to simulate various electrical signal patterns observed in biological synapses, including short- and long-term plasticity patterns. Theoretical and experimental results show that the selective permeation and hysteretic diffusion of ions caused by the anion selectivity of the CH layer are responsible for potential relaxation. Such an effect allows us with hydrogels to enable synapse-like information processing functions, including tactile perception, learning, memory, and neuromorphic computing. Additionally, the hydrogel device can operate stably even under 180° bending and 50% tensile strain, expanding the pathway for implementing advanced brain-like intelligent systems.

Authors

Institutions

Publication Details

Journal
ACS Nano
Published
2024-10-16
DOI
https://doi.org/10.1021/acsnano.4c09154
Citations
28
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
5.84

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ionic Potential Relaxation Effect in a Hydrogel Enabling Synapse-Like Information Processing

Kai Xiao, Youzhi Qu, Jiqing Dai, Quanying Liu et al.
28 citations
ACS Nano
Advanced Memory and Neural Computing
5.84
article

Ionic Potential Relaxation Effect in a Hydrogel Enabling Synapse-Like Information Processing

Kai Xiao, Youzhi Qu, Jiqing Dai, Quanying Liu, Zhiyuan Liu, Li Wang, Hongjie Zhang, Guoheng Xu, Wenchao Liu, Song Wang, Ting Wang
article en
28 citations

Abstract

The next-generation brain-like intelligence based on neuromorphic architectures emphasizes learning the ionic language of the brain, aiming for efficient brain-like computation and seamless human-computer interaction. Ionic neuromorphic devices, with ions serving as information carriers, provide possibilities to achieve this goal. Soft and biocompatible ionic conductive hydrogels are an ideal substrate for constructing ionic neuromorphic devices, but it remains a challenge to modulate the ion transport behavior in hydrogels to mimic neuroelectric signals. Here, we describe an ionic potential relaxation effect in a hydrogel device prepared by sandwiching a layer of polycationic hydrogel (CH) between two layers of neutral hydrogel (NH), allowing this device to simulate various electrical signal patterns observed in biological synapses, including short- and long-term plasticity patterns. Theoretical and experimental results show that the selective permeation and hysteretic diffusion of ions caused by the anion selectivity of the CH layer are responsible for potential relaxation. Such an effect allows us with hydrogels to enable synapse-like information processing functions, including tactile perception, learning, memory, and neuromorphic computing. Additionally, the hydrogel device can operate stably even under 180° bending and 50% tensile strain, expanding the pathway for implementing advanced brain-like intelligent systems.

ACS NanoVol. 18(43)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Southern University of Science and Technology (CN), Moscow University «Synergy» (RU), Shenzhen Institutes of Advanced Technology (CN)
Science and Technology Foundation of Shenzhen City, National Natural Science Foundation of China, China Postdoctoral Science Foundation, Science, Technology and Innovation Commission of Shenzhen Municipality
Openalex Percentile: Top 3%
Advanced Memory and Neural Computing
5.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.