期刊
JAPANESE JOURNAL OF APPLIED PHYSICS
卷 59, 期 8, 页码 -出版社
IOP Publishing Ltd
DOI: 10.35848/1347-4065/aba5e0
关键词
3D NAND; threshold voltage; machine learning; read disturbance
Machine learning (ML) is proposed as a method to predict threshold voltage (V-t) distribution by read disturbance in the unselected strings of three-dimensional NAND Flash Memory (3D NAND). We extracted theV(t)distribution after each read cycles in 3D NAND considering the process variation using Technology Computer-Aided Design (TCAD) simulation. The neural network (NN) was developed and was trained to have a small error rate. Through a test process, predictedV(t)by ML was in good agreement with TCAD simulation data. In rapidly developed technology, the prediction by ML-based on the NN can be a powerful tool in terms of consuming less time. Also, ML can be applied to predict other conditions and reliability issues.
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