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author:

Lan, S. (Lan, S..) [1] | Si, J. (Si, J..) [2] | Zheng, Z. (Zheng, Z..) [3] | Lin, J. (Lin, J..) [4] | Yu, R. (Yu, R..) [5] | Xu, W. (Xu, W..) [6] | Zhou, C. (Zhou, C..) [7] | Cai, X. (Cai, X..) [8] | Liao, W. (Liao, W..) [9]

Indexed by:

Scopus

Abstract:

Artificial synaptic devices are the hardware foundation of modern computing systems which have shown great potential in overcoming the bottleneck of traditional von-Neumann computing architectures. Organic synaptic transistors have garnered considerable attention due to their merits, such as low cost, low weight, and mechanical flexibility. Various materials are utilized for the charge-capture layer in organic synaptic transistors. Indium gallium zinc oxide (IGZO) is a typical metal oxide semiconductor with a wide bandgap, high carrier mobility, and stable characteristics. Moreover, IGZO is an n-type semiconductor with a lower highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy level compared to p-type semiconductor, which has great potential as a capture material to fabricate high-performance synaptic devices. However, the application of IGZO as the trapping layer in organic synaptic transistors has received limited attention. Consequently, an organic synaptic transistor based on organic/inorganic heterojunction was developed. The impact of program/erase time on memory performance was investigated, revealing that the memory window and memory ratio increased as the write/erase time was extended. Additionally, typical synaptic behavior were successfully emulated, including excitatory/inhibitory postsynaptic current, paired-pulse facilitation, paired-pulse depression, high-pass filtering characteristics, and the transformation of short-term plasticity to long-term plasticity. Notably, the synaptic transistor based on an inorganic-organic bilayer heterojunction achieved a high recognition accuracy of 89.2% using the Modified National Institute of Standards and Technology dataset for handwritten digit training. This study provides a facile route for fabricating high-performance synaptic transistors, paving the way for the development of advanced brain-like computers. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.

Keyword:

memory neuromorphic computing organic/inorganic heterojunction synaptic transistor

Community:

  • [ 1 ] [Lan S.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 2 ] [Si J.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 3 ] [Zheng Z.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 4 ] [Lin J.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 5 ] [Yu R.]Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou, 350002, China
  • [ 6 ] [Xu W.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 7 ] [Zhou C.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 8 ] [Cai X.]Department of Physics, Jimei University, Xiamen, 361021, China
  • [ 9 ] [Liao W.]Department of Physics, Jimei University, Xiamen, 361021, China

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Source :

Journal of Physics D: Applied Physics

ISSN: 0022-3727

Year: 2025

Issue: 13

Volume: 58

3 . 1 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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