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

Wen Deng , Yimeng Yu , Xin Yan , Yifei Li , Lisheng Wang , Jinsong Wu , Jean-Jacques Gaumet , Wen Luo

Energy & Environmental Materials ›› 2025, Vol. 8 ›› Issue (6) : e70075

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Energy & Environmental Materials ›› 2025, Vol. 8 ›› Issue (6) : e70075 DOI: 10.1002/eem2.70075
RESEARCH ARTICLE

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

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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/MoS2 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 107, an ultra-wide modulation range of 10–106, 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.

Keywords

2D materials / memtransistors / neuromorphic electronics / photoelectric co-regulation / p-n heterojunction

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Wen Deng, Yimeng Yu, Xin Yan, Yifei Li, Lisheng Wang, Jinsong Wu, Jean-Jacques Gaumet, Wen Luo. Ultra-High Switching Ratio Memtransistor Based on Van Der Waals Heterostructures Toward Neuromorphic Computing. Energy & Environmental Materials, 2025, 8(6): e70075 DOI:10.1002/eem2.70075

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2025 The Author(s). Energy & Environmental Materials published by John Wiley & Sons Australia, Ltd on behalf of Zhengzhou University.

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