Two-Dimensional Zeolitic Imidazolate Framework BasedOptoelectronic Synaptic Transistor

Neuromorphic computing systems that integrate memory and computation offer a solution to the limitations of traditional von Neumann architectures. Optoelectronic synaptic transistors, responding to both optical and electrical signals, enable multifunctional operation with low power consumption. However, challenges such as short data retention and low processing efficiency remain. This study presents an optoelectronic synaptic transistor utilizing two-dimensional (2D) MoS<sub>2</sub>, 2D zeolitic imidazolate framework (ZIF) Zn<sub>2</sub>(bim)<sub>4</sub>, and gold (Au) nanoparticles (NPs) as semiconductor, tunneling layer, and floating gate materials, respectively. By adjusting the tunneling layer thickness, the charge-blocking capacity of Zn<sub>2</sub>(bim)<sub>4</sub> is modulated, improving long-term data retention. The optoelectronic properties of MoS<sub>2</sub> and the charge-trapping ability of Au NPs enable the transistor to mimic synaptic behaviors such as postsynaptic current (PSC), long-term potentiation (LTP), and transition from short-term to long-term memory (STM-LTM). This device can also be integrated into an artificial neural network (ANN) for smart healthcare applications, achieving 88.1% accuracy in electrocardiogram classification through optoelectronic dual-mode stimulation.

Publication Details

Journal
Figshare
Published
2025-06-30
DOI
https://doi.org/10.1021/acs.jpclett.5c00009.s001
Primary Topic
Advanced Memory and Neural Computing
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article
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Two-Dimensional Zeolitic Imidazolate Framework BasedOptoelectronic Synaptic Transistor

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Advanced Memory and Neural Computing
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Two-Dimensional Zeolitic Imidazolate Framework BasedOptoelectronic Synaptic Transistor

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Abstract

Neuromorphic computing systems that integrate memory and computation offer a solution to the limitations of traditional von Neumann architectures. Optoelectronic synaptic transistors, responding to both optical and electrical signals, enable multifunctional operation with low power consumption. However, challenges such as short data retention and low processing efficiency remain. This study presents an optoelectronic synaptic transistor utilizing two-dimensional (2D) MoS<sub>2</sub>, 2D zeolitic imidazolate framework (ZIF) Zn<sub>2</sub>(bim)<sub>4</sub>, and gold (Au) nanoparticles (NPs) as semiconductor, tunneling layer, and floating gate materials, respectively. By adjusting the tunneling layer thickness, the charge-blocking capacity of Zn<sub>2</sub>(bim)<sub>4</sub> is modulated, improving long-term data retention. The optoelectronic properties of MoS<sub>2</sub> and the charge-trapping ability of Au NPs enable the transistor to mimic synaptic behaviors such as postsynaptic current (PSC), long-term potentiation (LTP), and transition from short-term to long-term memory (STM-LTM). This device can also be integrated into an artificial neural network (ANN) for smart healthcare applications, achieving 88.1% accuracy in electrocardiogram classification through optoelectronic dual-mode stimulation.

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