Paper
10 December 2024 A fast method for aerial image blur evaluation
Ziqi Li, Lisong Dong, Xiaojing Su, Wei Zhao, Yayi Wei, Lijie Zhang
Author Affiliations +
Proceedings Volume 13423, Eighth International Workshop on Advanced Patterning Solutions (IWAPS 2024); 1342305 (2024) https://doi.org/10.1117/12.3052323
Event: 8th International Workshop on Advanced Patterning Solutions (IWAPS 2024), 2024, Jiaxing, Zhejiang, China
Abstract
The source mask-optimization (SMO) is an inevitable computational lithography technique in the fabrication of advance integrate circuit (IC). Meanwhile, the aerial image (AI) blur is an important parameter to approximate the imaging degrade effect of resist and wafer stage during the SMO calculation. In this work, we propose a novel method to evaluate the imaging degrading of the AI blur. The AI blur convolution kernel is first transferred to the frequential space with the Fourier transformation. Then, the frequential coverage of the kernel is compared with the imaging pupil. Larger frequential coverage of the kernel indicates that the AI blur has trivial impact on the imaging, while low frequential coverage revel that the AI blur can degrade the imaging seriously. The proposed method can determine an appropriate range of AI blur setting, which is valuable at the beginning of the SMO process.
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ziqi Li, Lisong Dong, Xiaojing Su, Wei Zhao, Yayi Wei, and Lijie Zhang "A fast method for aerial image blur evaluation", Proc. SPIE 13423, Eighth International Workshop on Advanced Patterning Solutions (IWAPS 2024), 1342305 (10 December 2024); https://doi.org/10.1117/12.3052323
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KEYWORDS
Artificial intelligence

Lithography

Source mask optimization

Convolution

Projection systems

Evolutionary algorithms

Image analysis

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