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Synergistic multi-wavelength optical stimulation enhances synaptic dynamics and reservoir computing performance in ferroelectric thin-film transistorsopen access

Authors
Lee, SeungjunJang, HeeseongAn, GwangminJu, SeohyeonKim, Sungjun
Issue Date
Nov-2025
Publisher
Elsevier Ltd
Keywords
Electrical And Optical Functionality; Ferroelectric Thin-film Transistors; Hafnium Zirconium Oxide; Multi-wavelength; Synaptic Devices; Brain; Ferroelectric Devices; Ferroelectricity; Gallium Compounds; Hafnium Oxides; Image Classification; Indium Compounds; Neural Networks; Nonvolatile Storage; Photosensitivity; Semiconducting Indium; Zinc Oxide; Zirconium Compounds; C. Thin Film Transistor (tft); Electrical And Optical Functionality; Ferroelectric Thin-film Transistor; Ferroelectric Thin-films; Gallium Zinc Oxides; Multiwavelength; Optical Functionalities; Optical Stimulation; Synaptic Device; Zirconia Oxide; Ferroelectric Thin Films
Citation
Nano Energy, v.144, pp 1 - 12
Pages
12
Indexed
SCIE
SCOPUS
Journal Title
Nano Energy
Volume
144
Start Page
1
End Page
12
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/59052
DOI
10.1016/j.nanoen.2025.111395
ISSN
2211-2855
2211-3282
Abstract
Ferroelectric thin-film transistors (FeTFTs) with light-sensitive indium gallium zinc oxide channels are promising neuromorphic devices capable of integrating sensing, memory, and processing functionalities. In this work, we present an Indium-Gallium-Zinc-Oxide (IGZO)-based FeTFT that synergistically utilizes electrical and multi-wavelength optical stimuli to emulate a broad spectrum of synaptic and neural behaviors. The device, fabricated with a Ta/IGZO/Hf<inf>0.5</inf>Zr<inf>0.5</inf>O<inf>2</inf>/TiN back-gate stack, exhibits robust ferroelectric characteristics and nonvolatile memory behavior through polarization switching. Under optical illumination at 405, 450, and 520 nm, the device demonstrates distinct short-term memory dynamics, including paired-pulse facilitation, learning–forgetting–relearning processes, and nociceptive responses such as allodynia and hyperalgesia. Moreover, the FeTFT performs light-driven logic operations and mimics classical Pavlovian conditioning using purely optical inputs. These diverse behaviors are leveraged to implement a physical reservoir computing system. Using multi-wavelength optical stimulation, the FeTFT generates well-separated reservoir states, significantly enhancing recognition accuracy in a 4-bit image classification task. This device demonstrates the highest Fashion Modified National Institute of Standards and Technology recognition rate of 85.53 % was achieved under dual-wavelength stimulation (405 nm and 450 nm), confirming the effectiveness of spectral engineering in optimizing reservoir state separability. This study highlights the potential of optoelectronic FeTFTs as multifunctional building blocks for energy-efficient, brain-inspired vision systems. © 2025 Elsevier B.V., All rights reserved.
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