Optoelectronic Artificial Synapses Based on ZnO/Nanoporous Hybrid Thin Film by Atomic/Molecular Layer Deposition

An optoelectronic artificial synapse device has been established based on ZnO/Zn-HQ nanoporous hybrid thin films by atomic/molecular layer deposition. This unique nanoporous microstructure in devices significantly enhances the optoelectronic response and relaxation time, enabling important biosynaptic functions under optical stimuli, such as Pavlov's dog experiment and pattern recognition. The mechanism of ionization-deionization of oxygen vacancies has been proposed for this device.

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Publication Details

Journal
The Journal of Physical Chemistry Letters
Published
2025-05-02
DOI
https://doi.org/10.1021/acs.jpclett.5c00856
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92

Funders

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Optoelectronic Artificial Synapses Based on ZnO/Nanoporous Hybrid Thin Film by Atomic/Molecular Layer Deposition

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The Journal of Physical Chemistry Letters
Advanced Memory and Neural Computing
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article

Optoelectronic Artificial Synapses Based on ZnO/Nanoporous Hybrid Thin Film by Atomic/Molecular Layer Deposition

Chuyi Zhang, Di Wu, Aidong Li, Song Sun, Yidong Xia, Lin Zhu, Yuchen Li, Shuang Chen
article en
4 citations

Abstract

An optoelectronic artificial synapse device has been established based on ZnO/Zn-HQ nanoporous hybrid thin films by atomic/molecular layer deposition. This unique nanoporous microstructure in devices significantly enhances the optoelectronic response and relaxation time, enabling important biosynaptic functions under optical stimuli, such as Pavlov's dog experiment and pattern recognition. The mechanism of ionization-deionization of oxygen vacancies has been proposed for this device.

The Journal of Physical Chemistry LettersVol. 16(19)
Division of Materials Science and Engineering (AU), Collaborative Innovation Center of Advanced Microstructures (CN), Nanjing University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 9%
Advanced Memory and Neural Computing
2.92
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