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Infrared-Triggered Retinomorphic Artificial Synapse Electronic Device Containing Multi-Dimensional van der Waals
Soobin Shim1, Seongchan Kim2, Donghyun Lee3
1Department of Materials Engineering and Convergence Technology, Gyeongsang National University, Jinju, Gyeongsangnam-do, 52828, Republic of Korea.
Small (Weinheim an Der Bergstrasse, Germany)
|March 4, 2025
Summary
Researchers developed a novel artificial synapse using tungsten diselenide (WSe2) and indium arsenide quantum dots (InAs QDs). This device mimics the human retina for efficient short-wavelength infrared (SWIR) detection and machine vision applications.
Area of Science:
- Materials Science
- Optoelectronics
- Biomimetic Engineering
Background:
- Biological visual systems offer superior image recognition with low power and rapid responses.
- Solid-state artificial visual systems are inspired by the human eye's functionality.
- Existing artificial systems often lack the efficiency and responsiveness of biological counterparts.
Purpose of the Study:
- To develop a retinomorphic artificial synapse device for enhanced short-wavelength infrared (SWIR) detection.
- To investigate the performance of a tungsten diselenide (WSe2)/indium arsenide quantum dot (InAs QD) heterostructure for synaptic behavior.
- To demonstrate the potential of this device for machine vision and in-sensor computing.
Main Methods:
- Fabrication of a WSe2/InAs QD heterostructure device.
- Characterization of the device's responsivity at 1060 nm SWIR wavelength.
- Evaluation of synaptic properties and emulation of biological visual responses.
- Integration into an artificial neural network for image recognition tasks.
Main Results:
- The WSe2/InAs QD device exhibited enhanced SWIR responsivity, mimicking retinal synaptic behavior.
- Quantum confinement effects of InAs QDs improved charge transport and photon absorption.
- Effective electron-hole pair separation was achieved at the heterojunction, boosting photodetector performance.
- The device demonstrated superior synaptic property emulation compared to Si-based and other 2D material/QD devices.
- An artificial neural network achieved over 85% accuracy on the Fashion MNIST dataset.
Conclusions:
- The WSe2/InAs QD heterostructure shows significant promise for retina-inspired SWIR optoelectronic devices.
- Integration of QDs with 2D materials is a viable strategy for advanced photodetectors mimicking biological functions.
- The developed device offers potential for compact, efficient machine vision and in-sensor computing applications.
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