Impact of the Crystal Phase of ZrO₂ on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application

In this work, we investigated the effects of the crystal phase of ZrO<sub>2</sub> on charge trapping memtransistors (CTMTs) as synaptic devices for neural network applications. The ZrO<sub>2</sub> deposited through thermal (t-ZrO<sub>2</sub>) atomic layer depositi...

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Main Authors: Yu-Che Chou, Chien-Wei Tsai, Chin-Ya Yi, Wan-Hsuan Chung, Chao-Hsin Chien
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of the Electron Devices Society
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Online Access:https://ieeexplore.ieee.org/document/9091548/
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author Yu-Che Chou
Chien-Wei Tsai
Chin-Ya Yi
Wan-Hsuan Chung
Chao-Hsin Chien
author_facet Yu-Che Chou
Chien-Wei Tsai
Chin-Ya Yi
Wan-Hsuan Chung
Chao-Hsin Chien
author_sort Yu-Che Chou
collection DOAJ
description In this work, we investigated the effects of the crystal phase of ZrO<sub>2</sub> on charge trapping memtransistors (CTMTs) as synaptic devices for neural network applications. The ZrO<sub>2</sub> deposited through thermal (t-ZrO<sub>2</sub>) atomic layer deposition (ALD) and plasma (p-ZrO<sub>2</sub>) ALD were analyzed using an X-ray diffractometer, which indicated that the t-ZrO<sub>2</sub> consisted of pure cubic phase, whereas p-ZrO<sub>2</sub> consisted of both cubic and tetragonal phases. Through X-ray photoelectron spectroscopy analysis, we then constructed the energy band diagram of the gate stacks. The <inline-formula> <tex-math notation="LaTeX">$\Delta \mathrm E_{C}$ </tex-math></inline-formula> of t- and p-ZrO<sub>2</sub> with respect to tunneling and blocking Al<sub>2</sub>O<sub>3</sub> were 1.84 and 1.19 eV respectively. Because of the relatively large <inline-formula> <tex-math notation="LaTeX">$\Delta \text{E}_{\mathrm{ C}}$ </tex-math></inline-formula> of t-ZrO<sub>2</sub>, the window of the flat band voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm{ FB}}$ </tex-math></inline-formula>) shift extracted from charge trapping capacitors was enlarged by 591.9 mV more than the one using p-ZrO<sub>2</sub> as the charge trapping layer. Retention was also improved by 10.4&#x0025; after <inline-formula> <tex-math notation="LaTeX">$10^{5}$ </tex-math></inline-formula> s in the t-ZrO<sub>2</sub> case. Finally, we fabricated the CTMTs with the gate stack of the t-ZrO<sub>2</sub> case and demonstrated their characteristics as synaptic devices. With the optimization of pulse schemes, we reduced the nonlinear factors of depression (<inline-formula> <tex-math notation="LaTeX">${\alpha } _{\mathrm{ d}}$ </tex-math></inline-formula>) and potentiation (<inline-formula> <tex-math notation="LaTeX">${\alpha } _{\mathrm{ p}}$ </tex-math></inline-formula>) from &#x2212;6.72 and 6.47 to 0.03 and 0.01 respectively, enlarged the ON/OFF ratio from 15.6 to 70.4 and increased the recognition accuracy from 27.6&#x0025; to 86.5&#x0025; simultaneously.
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spelling doaj-art-b759a893e8764a5c873b38a262121ebf2025-08-22T23:09:17ZengIEEEIEEE Journal of the Electron Devices Society2168-67342020-01-01857257610.1109/JEDS.2020.29938599091548Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network ApplicationYu-Che Chou0Chien-Wei Tsai1Chin-Ya Yi2Wan-Hsuan Chung3Chao-Hsin Chien4Institute of Electronics, National Chiao Tung University, Hsinchu, TaiwanInstitute of Electronics, National Chiao Tung University, Hsinchu, TaiwanInstitute of Electronics, National Chiao Tung University, Hsinchu, TaiwanInstitute of Electronics, National Chiao Tung University, Hsinchu, TaiwanInstitute of Electronics, National Chiao Tung University, Hsinchu, TaiwanIn this work, we investigated the effects of the crystal phase of ZrO<sub>2</sub> on charge trapping memtransistors (CTMTs) as synaptic devices for neural network applications. The ZrO<sub>2</sub> deposited through thermal (t-ZrO<sub>2</sub>) atomic layer deposition (ALD) and plasma (p-ZrO<sub>2</sub>) ALD were analyzed using an X-ray diffractometer, which indicated that the t-ZrO<sub>2</sub> consisted of pure cubic phase, whereas p-ZrO<sub>2</sub> consisted of both cubic and tetragonal phases. Through X-ray photoelectron spectroscopy analysis, we then constructed the energy band diagram of the gate stacks. The <inline-formula> <tex-math notation="LaTeX">$\Delta \mathrm E_{C}$ </tex-math></inline-formula> of t- and p-ZrO<sub>2</sub> with respect to tunneling and blocking Al<sub>2</sub>O<sub>3</sub> were 1.84 and 1.19 eV respectively. Because of the relatively large <inline-formula> <tex-math notation="LaTeX">$\Delta \text{E}_{\mathrm{ C}}$ </tex-math></inline-formula> of t-ZrO<sub>2</sub>, the window of the flat band voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm{ FB}}$ </tex-math></inline-formula>) shift extracted from charge trapping capacitors was enlarged by 591.9 mV more than the one using p-ZrO<sub>2</sub> as the charge trapping layer. Retention was also improved by 10.4&#x0025; after <inline-formula> <tex-math notation="LaTeX">$10^{5}$ </tex-math></inline-formula> s in the t-ZrO<sub>2</sub> case. Finally, we fabricated the CTMTs with the gate stack of the t-ZrO<sub>2</sub> case and demonstrated their characteristics as synaptic devices. With the optimization of pulse schemes, we reduced the nonlinear factors of depression (<inline-formula> <tex-math notation="LaTeX">${\alpha } _{\mathrm{ d}}$ </tex-math></inline-formula>) and potentiation (<inline-formula> <tex-math notation="LaTeX">${\alpha } _{\mathrm{ p}}$ </tex-math></inline-formula>) from &#x2212;6.72 and 6.47 to 0.03 and 0.01 respectively, enlarged the ON/OFF ratio from 15.6 to 70.4 and increased the recognition accuracy from 27.6&#x0025; to 86.5&#x0025; simultaneously.https://ieeexplore.ieee.org/document/9091548/Germaniumhigh-<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">κ</italic> dielectricsmultilayer perceptronneural network hardwaresynaptic devicezirconium oxide
spellingShingle Yu-Che Chou
Chien-Wei Tsai
Chin-Ya Yi
Wan-Hsuan Chung
Chao-Hsin Chien
Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application
IEEE Journal of the Electron Devices Society
Germanium
high-<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">κ</italic> dielectrics
multilayer perceptron
neural network hardware
synaptic device
zirconium oxide
title Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application
title_full Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application
title_fullStr Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application
title_full_unstemmed Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application
title_short Impact of the Crystal Phase of ZrO&#x2082; on Charge Trapping Memtransistor as Synaptic Device for Neural Network Application
title_sort impact of the crystal phase of zro x2082 on charge trapping memtransistor as synaptic device for neural network application
topic Germanium
high-<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">κ</italic> dielectrics
multilayer perceptron
neural network hardware
synaptic device
zirconium oxide
url https://ieeexplore.ieee.org/document/9091548/
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AT chienweitsai impactofthecrystalphaseofzrox2082onchargetrappingmemtransistorassynapticdeviceforneuralnetworkapplication
AT chinyayi impactofthecrystalphaseofzrox2082onchargetrappingmemtransistorassynapticdeviceforneuralnetworkapplication
AT wanhsuanchung impactofthecrystalphaseofzrox2082onchargetrappingmemtransistorassynapticdeviceforneuralnetworkapplication
AT chaohsinchien impactofthecrystalphaseofzrox2082onchargetrappingmemtransistorassynapticdeviceforneuralnetworkapplication