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Optimal Energetic-Trap Distribution of Nano-Scaled Charge Trap Nitride for Wider Vth Window in 3D NAND Flash Using a Machine-Learning Method.

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第一作者： Kihoon,Nam

第一单位： Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.

作者： Kihoon,Nam ^[1] ; Chanyang,Park ^[1] ; Jun-Sik,Yoon ^[1] ; Hyeok,Yun ^[1] ; Hyundong,Jang ^[1] ; Kyeongrae,Cho ^[1] ; Ho-Jung,Kang ^[2] ; Min-Sang,Park ^[3] ; Jaesung,Sim ^[2] ; Hyun-Chul,Choi ^[4] ; Rock-Hyun,Baek ^[1]

作者单位： Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea. ^[1] SK hynix Inc., Cheongju-si 28429, Chungcheongbuk-do, Korea. ^[2] SK hynix Inc., Icheon-si 17336, Gyeonggi-do, Korea. ^[3] Department of Electrical Engineering, Yeungnam University, Gyeongsan 38541, Korea. ^[4]

关键词 3D NAND Flash charge trap nitride gradient-descent method machine learning multi-level cell threshold voltage window trap distribution

DOI 10.3390/nano12111808

PMID 35683664

发布时间 2022-07-16

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Nanomaterials (Basel, Switzerland)

2022年12卷11期

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Optimal Energetic-Trap Distribution of Nano-Scaled Charge Trap Nitride for Wider <i>V<sub>th</sub></i> Window in 3D NAND Flash Using a Machine-Learning Method.

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Optimal Energetic-Trap Distribution of Nano-Scaled Charge Trap Nitride for Wider <i>V<sub>th</sub></i> Window in 3D NAND Flash Using a Machine-Learning Method.

Nanomaterials (Basel, Switzerland)

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Nanomaterials (Basel, Switzerland)

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