Bioinspired High-Performance Neuromorphic Devices Enabled by Thienoviologen-Based Electrochemical Ion Gating

Neuromorphic computing is a bioinspired paradigm that emulates the structure and functionality of biological neural networks, demanding cutting-edge materials and device architectures. In this work, we present a bioinspired electrochemical neuromorphic device (BEND) utilizing a thienoviologen-based electrolyte. The incorporation of thiophene groups into the viologen structure (ThV²⁺) leads to a reduced energy gap, improved radical stability, and enhanced electrochemical activity. The device exhibits excellent ambient stability and continuously tunable conductivity in response to voltage pulse stimulation. When integrated into a convolutional neural network (CNN) for image recognition, BEND achieves an accuracy of nearly 80% on the Fashion-MNIST dataset. Moreover, the device successfully mimics essential synaptic functions such as spike-timing-dependent plasticity (STDP), Pavlovian learning, and supports dual-terminal logic gate operations. These results significantly expand the functional versatility of viologen-based materials in neuromorphic electronics and offer new insights into the design of next-generation electrochemical artificial synapses.