Simulation of OptoelectronicSynaptic Behavior inSnSe<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 SnSe<sub>2</sub>/WSe<sub>2</sub> 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.

Publication Details

Journal
Figshare
Published
2025-02-20
DOI
https://doi.org/10.1021/acsaelm.4c02195.s001
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Simulation of OptoelectronicSynaptic Behavior inSnSe2/WSe2 Heterojunction Transistors

Figshare
Advanced Memory and Neural Computing
article

Simulation of OptoelectronicSynaptic Behavior inSnSe2/WSe2 Heterojunction Transistors

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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 SnSe<sub>2</sub>/WSe<sub>2</sub> 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.

Figshare
Openalex Percentile: Top 57%
Advanced Memory and Neural Computing
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Simulation of OptoelectronicSynaptic Behavior inSnSe<sub>2</sub>/WSe<sub>2</sub> Heterojunction Transistors · Figshare (2025) | TGRS Research Map | TGRS