IEICE Electronics Express
Online ISSN : 1349-2543
ISSN-L : 1349-2543
LETTER
Machine learning model for predicting threshold voltage by taper angle variation and word line position in 3D NAND flash memory
Dong Chan LeeJang Kyu LeeHyungcheol Shin
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JOURNAL FREE ACCESS

2020 Volume 17 Issue 22 Pages 20200345

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Abstract

In this letter, a machine learning (ML) model is presented to predict the variation of the threshold voltage (Vth) according to the taper angle and target word line (WLT) position in 3D NAND flash memory. Through Technology Computer-Aided Design (TCAD) simulation, Vth is extracted according to taper angle and WLT position. TCAD data is used as the training data set required for learning by an artificial neural network algorithm (NNA). The completed ML model is then used to predict Vth for each word line (WL). It was also confirmed that the ML model predicted well even for TCAD data that was not used as a training data set.

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© 2020 by The Institute of Electronics, Information and Communication Engineers
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