All-Solution-Processed IGZO Optoelectronic Synaptic Transistor with Dual-Mode Operation toward Artificial Vision Applications

Realizing the dual-mode electric and optical synaptic plasticity within one neuromorphic device is impressive for the construction of a compact artificial visual system. Here, we proposed indium gallium zinc oxide (IGZO) photoelectric synaptic transistors utilizing all-solid-state electrolytes (Li-doped ZrO<sub>2</sub>) as gate dielectric layers. The device was fabricated by using a facile and cost-effective all-solution method. The synaptic transistor exhibited dual-mode electric and optical synaptic plasticity. Meanwhile, the tunable conductance is achieved through electric potentiation and depression processes, demonstrating the potential for realizing neuromorphic computing. Based on this, a simulated convolutional neural network was designed to realize handwriting digit recognition, achieving an accuracy of 96.8%. Additionally, sophisticated neuromorphic applications such as logic operations, Pavlov's classical experiment, and pupillary reflex simulation were successfully realized. Therefore, the designed transistor demonstrates significant potential for future applications in artificial vision.

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Publication Details

Journal
ACS Omega
Published
2025-04-18
DOI
https://doi.org/10.1021/acsomega.5c01052
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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article

All-Solution-Processed IGZO Optoelectronic Synaptic Transistor with Dual-Mode Operation toward Artificial Vision Applications

Shiwei Lin, Junru An, Lilan Zou, Haonan Xu
2 citations
ACS Omega
Advanced Memory and Neural Computing
1.46
article

All-Solution-Processed IGZO Optoelectronic Synaptic Transistor with Dual-Mode Operation toward Artificial Vision Applications

Shiwei Lin, Junru An, Lilan Zou, Haonan Xu
article en
2 citations

Abstract

Realizing the dual-mode electric and optical synaptic plasticity within one neuromorphic device is impressive for the construction of a compact artificial visual system. Here, we proposed indium gallium zinc oxide (IGZO) photoelectric synaptic transistors utilizing all-solid-state electrolytes (Li-doped ZrO<sub>2</sub>) as gate dielectric layers. The device was fabricated by using a facile and cost-effective all-solution method. The synaptic transistor exhibited dual-mode electric and optical synaptic plasticity. Meanwhile, the tunable conductance is achieved through electric potentiation and depression processes, demonstrating the potential for realizing neuromorphic computing. Based on this, a simulated convolutional neural network was designed to realize handwriting digit recognition, achieving an accuracy of 96.8%. Additionally, sophisticated neuromorphic applications such as logic operations, Pavlov's classical experiment, and pupillary reflex simulation were successfully realized. Therefore, the designed transistor demonstrates significant potential for future applications in artificial vision.

ACS OmegaVol. 10(16)
Hainan University (CN)
National Natural Science Foundation of China, Hainan University
Affordable and clean energy
Openalex Percentile: Top 18%
Advanced Memory and Neural Computing
1.46
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