Enhancing CD-SEM Accuracy with Attention-Boosted Noise2Noise Model

Yu Okada, Hsuehli Liu, Chieh En Lee, Chung Hao Tien, Peichen Yu*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Semiconductor manufacturing relies on Critical Dimension Scanning Electron Microscopy (CD-SEM) for precision in resist pattern measurements. High-resolution CD-SEM images, while desirable, can damage the resist due to increased electron beam exposure with higher frame numbers. To address this, Noise2Noise, a deep-learning noise reduction method, is introduced. Noise2Noise employs multiple noise images for unsupervised noise reduction. However, it struggles with unknown samples and limited training data. This research enhances the Noise2Noise model by introducing Attention and Residual-Recurrent structures to extract high-precision images from low-resolution inputs (1 frame). The Attention-boosted Noise2Noise model in particular exhibits superior accuracy with improved Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) for unseen patterns. Overall, the modeling error characterized by (ΔCD/CD) has been reduced compared to the conventional Noise2Noise method, promising improved CD-SEM accuracy for advanced CMOS manufacturing.

原文English
主出版物標題Metrology, Inspection, and Process Control XXXVIII
編輯Matthew J. Sendelbach, Nivea G. Schuch
發行者SPIE
ISBN(電子)9781510672161
DOIs
出版狀態Published - 2024
事件Metrology, Inspection, and Process Control XXXVIII 2024 - San Jose, 美國
持續時間: 26 2月 202429 2月 2024

出版系列

名字Proceedings of SPIE - The International Society for Optical Engineering
12955
ISSN(列印)0277-786X
ISSN(電子)1996-756X

Conference

ConferenceMetrology, Inspection, and Process Control XXXVIII 2024
國家/地區美國
城市San Jose
期間26/02/2429/02/24

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