Electrooptic Dual-Mode Synergetic Control of Two-Dimensional Nonvolatile Floating-Gate Transistors for Artificial Synapses

Floating-gate memories based on two-dimensional (2D) materials show great potential for mimicking synapses in artificial neural networks (ANNs), offering a promising pathway toward hardware neuromorphic computing. However, current implementations predominantly rely on electrical modulation, limiting their applications in future artificial visual systems. Here, we demonstrate an electrooptic dual-mode artificial synapse based on a van der Waals heterostructured MoS<sub>2</sub> floating-gate transistor. This device uniquely combines electrically controlled nonvolatile programmability with light-tunable multilevel storage states, enabling versatile synaptic functionalities. Specifically, electrical stimulation induces key synaptic behaviors, including excitatory/inhibitory responses and long-term potentiation/depression, while optical excitation facilitates long-term neuroplasticity through persistent multilevel conductance states. It can also work as an optoelectronic heterosynaptic transistor and perform dual-mode modulation through both electrical and optical inputs. With this characteristic, we demonstrate its application in an ANN visual sensor, which achieves a remarkable recognition accuracy of 91.97% in handwritten digit classification.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-12-09
DOI
https://doi.org/10.1021/acsami.5c17888
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Electrooptic Dual-Mode Synergetic Control of Two-Dimensional Nonvolatile Floating-Gate Transistors for Artificial Synapses

Z. Zhang, Zhe Sheng, Wennan Hu, Zheng Zhang et al.
1 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
0.73
article

Electrooptic Dual-Mode Synergetic Control of Two-Dimensional Nonvolatile Floating-Gate Transistors for Artificial Synapses

Z. Zhang, Zhe Sheng, Wennan Hu, Zheng Zhang, Haoran Sun, Yi Zhao, Yaping He
article en
1 citations

Abstract

Floating-gate memories based on two-dimensional (2D) materials show great potential for mimicking synapses in artificial neural networks (ANNs), offering a promising pathway toward hardware neuromorphic computing. However, current implementations predominantly rely on electrical modulation, limiting their applications in future artificial visual systems. Here, we demonstrate an electrooptic dual-mode artificial synapse based on a van der Waals heterostructured MoS<sub>2</sub> floating-gate transistor. This device uniquely combines electrically controlled nonvolatile programmability with light-tunable multilevel storage states, enabling versatile synaptic functionalities. Specifically, electrical stimulation induces key synaptic behaviors, including excitatory/inhibitory responses and long-term potentiation/depression, while optical excitation facilitates long-term neuroplasticity through persistent multilevel conductance states. It can also work as an optoelectronic heterosynaptic transistor and perform dual-mode modulation through both electrical and optical inputs. With this characteristic, we demonstrate its application in an ANN visual sensor, which achieves a remarkable recognition accuracy of 91.97% in handwritten digit classification.

ACS Applied Materials & InterfacesVol. 17(51)
Hangzhou Normal University (CN), Jiangsu Second Normal University (CN), Fudan University (CN), Shanghai Fudan Microelectronics (China) (CN)
Openalex Percentile: Top 21%
Advanced Memory and Neural Computing
0.73
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