神经形态工程学
铁电性
人工神经网络
锡
退火(玻璃)
像素
光电子学
锗
材料科学
电导
硅
计算机科学
算法
凝聚态物理
物理
人工智能
复合材料
电介质
冶金
作者
H. Y. Lin,Chao-Cheng Lin,Chung-Ting Shih,Wen-Yueh Jang,Tseung‐Yuen Tseng
出处
期刊:IEEE Electron Device Letters
[Institute of Electrical and Electronics Engineers]
日期:2023-07-13
卷期号:44 (9): 1444-1447
被引量:2
标识
DOI:10.1109/led.2023.3295337
摘要
In this work, we fabricate a ferroelectric tunnel junction (FTJ) device with W/MgO/HZO/TiN structure. The effect of MgO thickness on the FTJ properties of HZO films is studied. Device with 0.5 nm thick MgO insulating layer and annealing at 600 °C for 20 s exhibits a large memory window of about 30 and stable endurance of at least one million cycles with multilevel states. For pulse measurements, this device shows excellent nonlinearities of 0.1 and 0.32 for potentiation(P) and depression(D), respectively. The conductance data of P and D are input into simulated Hopfield neural network model for training to learn $10\times10$ -pixel size images. Such model recognizes the input images to reach an accuracy of 100 % in only 19 iterations. This result demonstrates that our FTJ device has high potential working as artificial synapse for the neuromorphic computing application in the future.
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