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Efficient UV-Sensitive Si-In-ZnO-Based Photo-TFT and Its Behavior as an Optically Stimulated Artificial Synapse

Authors
Sarkar, ArijitLee, Sang Yeol
Issue Date
Feb-2023
Publisher
AMER CHEMICAL SOC
Keywords
optoelectronic synapse; artificial synapse; synaptic TFTs; UV-photoresponse; photo-TFTs; phototransistors
Citation
ACS APPLIED ELECTRONIC MATERIALS, v.5, no.2, pp.1057 - 1066
Journal Title
ACS APPLIED ELECTRONIC MATERIALS
Volume
5
Number
2
Start Page
1057
End Page
1066
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/87141
DOI
10.1021/acsaelm.2c01559
ISSN
2637-6113
Abstract
Integration of optoelectronic synaptic devices as neuromorphic vision sensors has currently attracted significant attention due to their ability of imitating human visual systems. Low-power-consuming UV-sensitive phototransistors fabricated using amorphous oxide semiconductors are one of the potential contenders for the development of optically stimulated synaptic devices. Herein, amorphous Si-In-ZnO (a-SIZO)-based UV -sensitive photo thin-film transistors (photo-TFTs) were fabricated, which exhibited an efficient spectral photoresponsivity of 4.93 x 103 A/W and detectivity of 5.47 x 1015 jones at 350 nm wavelength. Considerable photoresponse in the visible range (450- 650 nm) was also observed. The presence of persistent photo-conductivity (PPC) in the photoresponse characteristics enabled the photo-TFT to perform simultaneously as an optically stimulated artificial synapse. The typical synaptic behaviors such as excitatory post-synaptic current (EPSC), pair-pulse facilitation (PPF), short-term plasticity (STP) to long-term plasticity (LTP), etc. were demonstrated efficiently by the fabricated photo-TFT, indicating its learning and memorizing capabilities similar to a biological synapse. The concurrent demonstration of efficient UV range photoresponse and optically stimulated synaptic behavior enables the a-SIZO-based photo-TFT as a promising pathway toward the development of artificial visual sensors which can be integrated into future neuromorphic systems.
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