Efficient UV-Sensitive Si-In-ZnO-Based Photo-TFT and Its Behavior as an Optically Stimulated Artificial Synapse
- Authors
- Sarkar, Arijit; Lee, 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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