Ta<sub>2</sub>PdS<sub>6</sub>/MoS<sub>2</sub> HeterojunctionPhototransistor for High-Performance Photoelectric Synapses and GraphicIdentification

Artificial synapses and neurons with efficient, high-speed, and highly parallel information processing capabilities are considered to be a new direction for the next generation of learning, cognition, and data storage. In this work, we have integrated photodetectors and photoelectric synapse in Ta<sub>2</sub>PdS<sub>6</sub>/MoS<sub>2</sub> van der Waals heterostructures, which can be used in photodetection and optical artificial neural networks. We have systematically studied the photoelectric characteristics of the blue-violet to near-infrared (405 ∼ 1550 nm) band. At 633 nm, the responsivity and specific detectivity are as high as 590.36 AW<sup>–1</sup> and 5.63 × 10<sup>11</sup> Jones, respectively. In addition, the heterojunction acquired a persistent photoconductivity behavior due to the presence of interfacial defect states, which was used to simulate the synaptic properties of the human brain, such as transition from short-term memory to long-term memory, paired-pulse facilitation, “learning–forgetting–relearning” behavior, and excitatory-postsynaptic current. In addition, on the basis of photoelectric synapse, the recognition of handwritten digits with different noise levels by an artificial neural network was simulated, which shows a high training accuracy (90%). This study lays a foundation for the development of high-performance heterojunctions and artificial synapses using two-dimensional materials.

Publication Details

Journal
Figshare
Published
2025-03-19
DOI
https://doi.org/10.1021/acsami.5c01804.s001
Primary Topic
2D Materials and Applications
Type
article
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article

Ta2PdS6/MoS2 HeterojunctionPhototransistor for High-Performance Photoelectric Synapses and GraphicIdentification

Figshare
2D Materials and Applications
article

Ta2PdS6/MoS2 HeterojunctionPhototransistor for High-Performance Photoelectric Synapses and GraphicIdentification

article en

Abstract

Artificial synapses and neurons with efficient, high-speed, and highly parallel information processing capabilities are considered to be a new direction for the next generation of learning, cognition, and data storage. In this work, we have integrated photodetectors and photoelectric synapse in Ta<sub>2</sub>PdS<sub>6</sub>/MoS<sub>2</sub> van der Waals heterostructures, which can be used in photodetection and optical artificial neural networks. We have systematically studied the photoelectric characteristics of the blue-violet to near-infrared (405 ∼ 1550 nm) band. At 633 nm, the responsivity and specific detectivity are as high as 590.36 AW<sup>–1</sup> and 5.63 × 10<sup>11</sup> Jones, respectively. In addition, the heterojunction acquired a persistent photoconductivity behavior due to the presence of interfacial defect states, which was used to simulate the synaptic properties of the human brain, such as transition from short-term memory to long-term memory, paired-pulse facilitation, “learning–forgetting–relearning” behavior, and excitatory-postsynaptic current. In addition, on the basis of photoelectric synapse, the recognition of handwritten digits with different noise levels by an artificial neural network was simulated, which shows a high training accuracy (90%). This study lays a foundation for the development of high-performance heterojunctions and artificial synapses using two-dimensional materials.

Figshare
Openalex Percentile: Top 65%
2D Materials and Applications
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