Simulation of Optoelectronic Synaptic Behavior in SnSe<sub>2</sub>/WSe<sub>2</sub> Heterojunction Transistors

The extensive research on neuromorphic devices exemplified by transistors is attributed to their capacity to emulate the synaptic plasticity found in the human brain. The unique properties of two-dimensional (2D) materials, such as layered structure, excellent optoelectronic properties, and ability to form heterojunctions, make them promising candidates for synaptic devices. Herein, a transistor based on a SnSe2/WSe2 heterojunction structure is investigated, and it can be used to simulate the function of optoelectronic synapses. The heterojunction exhibits bidirectional responses to optical stimuli with different wavelengths (λ = 400 nm/500 nm), enabling the device to emulate both excitatory and inhibitory synaptic behaviors in an all-optical pathway. Besides optical stimulus, gate voltage is used to modulate the synaptic performance of the device under 500 nm illumination, enabling it to mimic light adaption of biological eyes successfully. Based on the wavelength-selective synaptic plasticity, an optically driven artificial neural network (ANN) is proposed to classify handwritten digits with an accuracy of around 80%. This work will be an important step toward the future development of multifunctional optoelectronic synapses.

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Publication Details

Journal
ACS Applied Electronic Materials
Published
2025-02-20
DOI
https://doi.org/10.1021/acsaelm.4c02195
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92

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article

Simulation of Optoelectronic Synaptic Behavior in SnSe2/WSe2 Heterojunction Transistors

Zhenpeng Cheng, Yifan Zhang, Fengxiang Chen, Zixuan Huang et al.
4 citations
ACS Applied Electronic Materials
Advanced Memory and Neural Computing
2.92
article

Simulation of Optoelectronic Synaptic Behavior in SnSe2/WSe2 Heterojunction Transistors

Zhenpeng Cheng, Yifan Zhang, Fengxiang Chen, Zixuan Huang, Lisheng Wang
article en
4 citations

Abstract

The extensive research on neuromorphic devices exemplified by transistors is attributed to their capacity to emulate the synaptic plasticity found in the human brain. The unique properties of two-dimensional (2D) materials, such as layered structure, excellent optoelectronic properties, and ability to form heterojunctions, make them promising candidates for synaptic devices. Herein, a transistor based on a SnSe2/WSe2 heterojunction structure is investigated, and it can be used to simulate the function of optoelectronic synapses. The heterojunction exhibits bidirectional responses to optical stimuli with different wavelengths (λ = 400 nm/500 nm), enabling the device to emulate both excitatory and inhibitory synaptic behaviors in an all-optical pathway. Besides optical stimulus, gate voltage is used to modulate the synaptic performance of the device under 500 nm illumination, enabling it to mimic light adaption of biological eyes successfully. Based on the wavelength-selective synaptic plasticity, an optically driven artificial neural network (ANN) is proposed to classify handwritten digits with an accuracy of around 80%. This work will be an important step toward the future development of multifunctional optoelectronic synapses.

ACS Applied Electronic MaterialsVol. 7(5)
Wuhan University of Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Affordable and clean energy
Openalex Percentile: Top 10%
Advanced Memory and Neural Computing
2.92
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