Ephaptic Coupling in Ultralow‐Power Ion‐Gel Nanofiber Artificial Synapses for Enhanced Working Memory

• DOI: 10.1002/adma.202419013
• Publication Date: 2025-03-12T06:13:43Z
• Authors: Yuanxia Chen; Junfeng Xia; Youzhi Qu; Hongjie Zhang; Tingting Mei; Xinyi Zhu; Guoheng Xu; Dongyang Li; Li Wang; Quanying Liu; Kai Xiao
• Keywords: Neuromorphic engineering; MNIST database

Neuromorphic devices are designed to replicate the energy-efficient information processing advantages found in biological neural networks by emulating working mechanisms of neurons and synapses. However, most existing neuromorphic focus primarily on functionally mimicking synapses, with insufficient emphasis ion transport mechanisms. This limitation makes it challenging achieve complexity connectivity inherent systems, such as ephaptic coupling. Here, an ionic biomimetic synaptic device based a flexible ion-gel nanofiber network is proposed, which transmits enables coupling through capacitance formation extremely low energy consumption just 6 femtojoules. The hysteretic behavior endows synaptic-like memory effects, significantly enhancing performance reservoir computing system for classifying MNIST handwritten digit dataset demonstrating high efficiency edge learning. More importantly, array establish communication connections, exhibiting global oscillatory behaviors similar networks. perform tasks, paving way developing brain-like systems characterized vast connectivity.