Artificial Neuron Based on Electrical Anisotropy from WSe <sub>2</sub> Field Effect Transistors

Neuromorphic systems have been recognized as potential computational platforms for overcoming the von Neumann architecture, where neurons are the basic units for neuromorphic computing. However, artificial neurons of two-dimensional materials suffered from limited stability and complex architecture. In this work, a multi-terminal neural device was constructed based on the electrical anisotropic properties of WSe<sub>2</sub>. Axon-multisynaptic performance with modulating plasticity was realized successfully by a stable six-terminal WSe<sub>2</sub> field effect transistor. And dendritic functionality with optoelectronic synergy was obtained, showcasing the functional integrity of this neural device. Recognition accuracy of handwritten digits was obtained to 97% based on the synaptic weight of an artificial neuron. Additionally, gesture control of a robot manipulator was achieved with anisotropic synaptic responses from a WSe<sub>2</sub> sample. These findings not only provide novel material platforms and circuit design solutions for constructing artificial neural networks but also mark a significant advancement in the development of neuromorphic electronics capable of processing complex signals.

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Publication Details

Journal
Advanced Science
Published
2026-01-20
DOI
https://doi.org/10.1002/advs.202515893
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Neuron Based on Electrical Anisotropy from WSe 2 Field Effect Transistors

Zongqian Tan, Qi Sun, Chaoqi Chen, Jinsheng Zhu et al.
Advanced Science
Advanced Memory and Neural Computing
article

Artificial Neuron Based on Electrical Anisotropy from WSe 2 Field Effect Transistors

Zongqian Tan, Qi Sun, Chaoqi Chen, Jinsheng Zhu, Yaxian Lu, Tao Lin, Kun Lv, Ni Zhang, Ping Chen, Zhiling Chen
article en

Abstract

Neuromorphic systems have been recognized as potential computational platforms for overcoming the von Neumann architecture, where neurons are the basic units for neuromorphic computing. However, artificial neurons of two-dimensional materials suffered from limited stability and complex architecture. In this work, a multi-terminal neural device was constructed based on the electrical anisotropic properties of WSe<sub>2</sub>. Axon-multisynaptic performance with modulating plasticity was realized successfully by a stable six-terminal WSe<sub>2</sub> field effect transistor. And dendritic functionality with optoelectronic synergy was obtained, showcasing the functional integrity of this neural device. Recognition accuracy of handwritten digits was obtained to 97% based on the synaptic weight of an artificial neuron. Additionally, gesture control of a robot manipulator was achieved with anisotropic synaptic responses from a WSe<sub>2</sub> sample. These findings not only provide novel material platforms and circuit design solutions for constructing artificial neural networks but also mark a significant advancement in the development of neuromorphic electronics capable of processing complex signals.

Advanced ScienceVol. 13(17)
Guangxi University (CN), Beihang University (CN)
Openalex Percentile: Top 83%
Advanced Memory and Neural Computing
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Artificial Neuron Based on Electrical Anisotropy from WSe <sub>2</sub> Field Effect Transistors — Zongqian Tan, Qi Sun, et al. · Advanced Science (2026) | TGRS Research Map | TGRS