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Infrared-Triggered Retinomorphic Artificial Synapse Electronic Device Containing Multi-Dimensional van der Waals Heterojunctionsopen access

Authors
Shim, SoobinKim, SeongchanLee, DonghyunKim, HyeongtaeKwon, Mi JiCho, Su-yeonLestari, Windy AyuSeo, JaeyoungYeo, DongjoonNa, JinaKundale, Somnath SuhasOh, NuriPark, Jun Hong
Issue Date
Jun-2025
Publisher
Wiley - V C H Verlag GmbbH & Co.
Keywords
2D materials; artificial visual system; retinomorphic synapse device; short-wavelength infrared; van der Waals heterojunction
Citation
Small, v.21, no.24, pp 1 - 13
Pages
13
Indexed
SCIE
SCOPUS
Journal Title
Small
Volume
21
Number
24
Start Page
1
End Page
13
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/208615
DOI
10.1002/smll.202410892
ISSN
1613-6810
1613-6829
Abstract
Biological systems excel in image recognition with low power and fast responses. Inspired by the human eye, researchers have developed solid-state artificial visual systems. In this study, a retinomorphic artificial synapse device based on a tungsten diselenide (WSe2)/indium arsenide quantum dot (InAs QD) heterostructure is developed. This device exhibits enhanced short-wavelength infrared (SWIR) responsivity at 1060 nm, which is a synaptic behavior analogous to the human retina. The WSe2/InAs QD improves charge transport and photon absorption through the quantum confinement effects of InAs QDs, facilitating efficient SWIR detection. The heterojunction enables effective electron-hole pair separation, enhancing the photodetector performance. The device adapts to SWIR signal pulses like the human eye to light flicker. The WSe2/InAs QD device demonstrates significantly higher responsivity and a superior ability to emulate a wide range of synaptic properties compared to previously reported Si-based and 2D material/QD-based devices. An artificial neural network trained on the Fashion MNIST dataset achieved over 85% accuracy, which is higher than previous reports. This showcases the potential of retina-inspired SWIR optoelectronic devices for compact, efficient machine vision and in-sensor computing. This study underscores the potential of integrating QDs with 2D materials to create advanced photodetectors that mimic biological sensory functions.
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