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 (ThV<sup>2+</sup>) 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.

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Publication Details

Journal
Angewandte Chemie International Edition
Published
2025-12-23
DOI
https://doi.org/10.1002/anie.202523345
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

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

Gang He, Zhikang Han, Siyu Sun, Bai Sun et al.
Angewandte Chemie International Edition
Advanced Memory and Neural Computing
article

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

Gang He, Zhikang Han, Siyu Sun, Bai Sun, Chengjing Liu, Yueyan Zhang, Wei Zhang
article en

Abstract

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 (ThV<sup>2+</sup>) 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.

Angewandte Chemie International EditionVol. 65(13)
Ministry of Education (TW), Xi'an Jiaotong University (CN)
Affordable and clean energy
Openalex Percentile: Top 43%
Advanced Memory and Neural Computing
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