Ultra‐High Switching Ratio Memtransistor Based on Van Der Waals Heterostructures Toward Neuromorphic Computing

The exceptional resistive switching characteristics and neuromorphic computational potential of memristors are crucial for advancing information processing in both traditional and non‐traditional computing paradigms. However, the non‐ideal resistive switching behavior of conventional oxide‐based memristors hardly meets the performance requirements for neuromorphic computing applications. Besides, the two‐terminal memristors are restricted by their configuration limitations toward multi‐field/multi‐functional modulation. Herein, this article presents a 2D GaSe/MoS 2 heterojunction thin‐film transistor with four‐terminal (4‐T) tuning capability and flexible programming/erasing operations for non‐volatile storage. The heterojunction transistor demonstrates an exceptional resistance switching ratio exceeding 10 7 , an ultra‐wide modulation range of 10–10 6 , highly reliable stability, and cyclic durability. The in situ Kelvin probe force microscope and dynamic characterization reveal the conduction mediated by defect‐induced space charge limitations, as well as the tuning filling process of trap states within the channel by dual‐gate terminals. This device functions as a 4‐T artificial synapse, capable of achieving basic optoelectronic synaptic operations. The self‐denoising and pattern recognition capabilities exhibited by artificial neural networks based on this device serve as excellent examples for developing efficient and energy‐saving neuromorphic computing architectures.

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Publication Details

Journal
Energy & environment materials
Published
2025-07-12
DOI
https://doi.org/10.1002/eem2.70075
Citations
5
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
3.65

Funders

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article

Ultra‐High Switching Ratio Memtransistor Based on Van Der Waals Heterostructures Toward Neuromorphic Computing

Wen Deng, Jinsong Wu, Yimeng Yu, Xinping Yan et al.
5 citations
Energy & environment materials
Advanced Memory and Neural Computing
3.65
article

Ultra‐High Switching Ratio Memtransistor Based on Van Der Waals Heterostructures Toward Neuromorphic Computing

Wen Deng, Jinsong Wu, Yimeng Yu, Xinping Yan, Wen Luo, Jean‐Jacques Gaumet, Lisheng Wang, Yifei Li
article en
5 citations

Abstract

The exceptional resistive switching characteristics and neuromorphic computational potential of memristors are crucial for advancing information processing in both traditional and non‐traditional computing paradigms. However, the non‐ideal resistive switching behavior of conventional oxide‐based memristors hardly meets the performance requirements for neuromorphic computing applications. Besides, the two‐terminal memristors are restricted by their configuration limitations toward multi‐field/multi‐functional modulation. Herein, this article presents a 2D GaSe/MoS 2 heterojunction thin‐film transistor with four‐terminal (4‐T) tuning capability and flexible programming/erasing operations for non‐volatile storage. The heterojunction transistor demonstrates an exceptional resistance switching ratio exceeding 10 7 , an ultra‐wide modulation range of 10–10 6 , highly reliable stability, and cyclic durability. The in situ Kelvin probe force microscope and dynamic characterization reveal the conduction mediated by defect‐induced space charge limitations, as well as the tuning filling process of trap states within the channel by dual‐gate terminals. This device functions as a 4‐T artificial synapse, capable of achieving basic optoelectronic synaptic operations. The self‐denoising and pattern recognition capabilities exhibited by artificial neural networks based on this device serve as excellent examples for developing efficient and energy‐saving neuromorphic computing architectures.

Energy & environment materialsVol. 8(6)
Wuhan University of Technology (CN), Wuhan University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 7%
Advanced Memory and Neural Computing
3.65
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