Smart Diagnostics for 3D CFET: A Machine Learning Approach to Failure Analysis

This work introduces a novel Convolutional Neural Network for classifying transfer characteristics in emerging Gate-All-Around MOSFET. Trained on vast experimental dataset, the algorithm successfully identifies distinct failure modes across wafers with complex processing variations. The automated analysis enables faster yield enhancement and process optimization for next-generation 3D MOSFET technologies.

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Publication Details

Published
2025-03-24
DOI
https://doi.org/10.1109/icmts63811.2025.11068926
Citations
1
Primary Topic
Integrated Circuits and Semiconductor Failure Analysis
Type
article
Field-Weighted Citation Impact
0.73

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article

Smart Diagnostics for 3D CFET: A Machine Learning Approach to Failure Analysis

Hüsnü Murat Koçak, Naoto Horiguchi, T. Chiarella, Cassie Sheng et al.
1 citations
Integrated Circuits and Semiconductor Failure Analysis
0.73
article

Smart Diagnostics for 3D CFET: A Machine Learning Approach to Failure Analysis

Hüsnü Murat Koçak, Naoto Horiguchi, T. Chiarella, Cassie Sheng, Jérôme Mitard, Steven Demuyck
article en
1 citations

Abstract

This work introduces a novel Convolutional Neural Network for classifying transfer characteristics in emerging Gate-All-Around MOSFET. Trained on vast experimental dataset, the algorithm successfully identifies distinct failure modes across wafers with complex processing variations. The automated analysis enables faster yield enhancement and process optimization for next-generation 3D MOSFET technologies.

Imec the Netherlands (NL), IMEC (BE)
HORIZON EUROPE Framework Programme
Decent work and economic growth
Openalex Percentile: Top 26%
Integrated Circuits and Semiconductor Failure Analysis
0.73
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