Optical wafer defect inspection at the 10 nm technology node and beyond

  • Abstract The growing demand for electronic devices, smart devices, and the Internet of Things constitutes the primary driving force for marching down the path of decreased critical dimension and increased circuit intricacy of integrated circuits. However, as sub-10 nm high-volume manufacturing is becoming the mainstream, there is greater awareness that defects introduced by original equipment manufacturer components impact yield and manufacturing costs. The identification, positioning, and classification of these defects, including random particles and systematic defects, are becoming more and more challenging at the 10 nm node and beyond. Very recently, the combination of conventional optical defect inspection with emerging techniques such as nanophotonics, optical vortices, computational imaging, quantitative phase imaging, and deep learning is giving the field a new possibility. Hence, it is extremely necessary to make a thorough review for disclosing new perspectives and exciting trends, on the foundation of former great reviews in the field of defect inspection methods. In this article, we give a comprehensive review of the emerging topics in the past decade with a focus on three specific areas: (a) the defect detectability evaluation, (b) the diverse optical inspection systems, and (c) the post-processing algorithms. We hope, this work can be of importance to both new entrants in the field and people who are seeking to use it in interdisciplinary work.
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Jinlong Zhu, Jiamin Liu, Tianlai Xu, Shuai Yuan, Zexu Zhang, Hao Jiang, Honggang Gu, Renjie Zhou, Shiyuan Liu. Optical wafer defect inspection at the 10 nm technology node and beyond[J]. International Journal of Extreme Manufacturing, 2022, 4(3): 032001. DOI: 10.1088/2631-7990/ac64d7
Jinlong Zhu, Jiamin Liu, Tianlai Xu, Shuai Yuan, Zexu Zhang, Hao Jiang, Honggang Gu, Renjie Zhou, Shiyuan Liu. Optical wafer defect inspection at the 10 nm technology node and beyond[J]. International Journal of Extreme Manufacturing, 2022, 4(3): 032001. DOI: 10.1088/2631-7990/ac64d7

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