Polycrystalline InGaO Thin-Film Transistor with SiO <sub>2</sub> Gate Insulator for High-Performance Artificial Synapses

Metal-oxide semiconductor (MOS)-based synaptic transistors are promising candidates for highly integrated neuromorphic chips. Ferroelectrics and electrolytes have been extensively studied, but they have not satisfied the scalability and integration of the chips. We report a synaptic thin-film transistor (TFT) based on polycrystalline InGaO (C-IGO) semiconductor, exhibiting a large counterclockwise hysteresis with a memory window (MW) ratio of 57%, attributed to positively charged oxygen vacancy (V<sub>o</sub><sup>+/++</sup>) migration within the C-IGO layer. The C-IGO TFT could be integrated with the back-end-of-line (BEOL) process. The scalable process could be achieved with self-aligned (SA) coplanar C-IGO TFT with conventional gate insulator (GI) materials. The C-IGO synaptic TFT exhibits high synaptic performance, including long-term potentiation/depression (LTP/LTD) characteristics. Modified National Institute of Standards and Technology (MNIST) handwritten digit image recognition simulation based on potentiation/depression curves yields high recognition accuracy (91.64%). The results validate the potential for high-density, neuromorphic, and artificial intelligence (AI) applications.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2026-01-05
DOI
https://doi.org/10.1021/acsami.5c20927
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Polycrystalline InGaO Thin-Film Transistor with SiO 2 Gate Insulator for High-Performance Artificial Synapses

Kwak Joon-Young, Solbee Lee, Taebin Lim, Heerak Wi et al.
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
article

Polycrystalline InGaO Thin-Film Transistor with SiO 2 Gate Insulator for High-Performance Artificial Synapses

Kwak Joon-Young, Solbee Lee, Taebin Lim, Heerak Wi, Jin Jang
article en

Abstract

Metal-oxide semiconductor (MOS)-based synaptic transistors are promising candidates for highly integrated neuromorphic chips. Ferroelectrics and electrolytes have been extensively studied, but they have not satisfied the scalability and integration of the chips. We report a synaptic thin-film transistor (TFT) based on polycrystalline InGaO (C-IGO) semiconductor, exhibiting a large counterclockwise hysteresis with a memory window (MW) ratio of 57%, attributed to positively charged oxygen vacancy (V<sub>o</sub><sup>+/++</sup>) migration within the C-IGO layer. The C-IGO TFT could be integrated with the back-end-of-line (BEOL) process. The scalable process could be achieved with self-aligned (SA) coplanar C-IGO TFT with conventional gate insulator (GI) materials. The C-IGO synaptic TFT exhibits high synaptic performance, including long-term potentiation/depression (LTP/LTD) characteristics. Modified National Institute of Standards and Technology (MNIST) handwritten digit image recognition simulation based on potentiation/depression curves yields high recognition accuracy (91.64%). The results validate the potential for high-density, neuromorphic, and artificial intelligence (AI) applications.

ACS Applied Materials & InterfacesVol. 18(1)
ON Semiconductor (United States) (US), Japan Display (Japan) (JP), Kyung Hee University (KR), Ewha Womans University Medical Center (KR), Institute of Semiconductor Physics (RU)
Openalex Percentile: Top 98%
Advanced Memory and Neural Computing
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Polycrystalline InGaO Thin-Film Transistor with SiO <sub>2</sub> Gate Insulator for High-Performance Artificial Synapses — Kwak Joon-Young, Solbee Lee, et al. · ACS Applied Materials & Interfaces (2026) | TGRS Research Map | TGRS