EUV SRAFs printing modeling with bright field mask

Chih-I Wei; Azat Latypov; Shuling Wang; Satya Sriram; Prakash Deep; Yunfei Deng; Ethan Maguire; Shumay Shang; Germain Fenger; Werner Gillijns

doi:10.1117/12.2640532

15 September 2022 EUV SRAFs printing modeling with bright field mask

Chih-I Wei, Azat Latypov, Shuling Wang, Satya Sriram, Prakash Deep, Yunfei Deng, Ethan Maguire, Shumay Shang, Germain Fenger, Werner Gillijns

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Proceedings Volume 12325, Photomask Japan 2022: XXVIII Symposium on Photomask and Next-Generation Lithography Mask Technology; 1232506 (2022) https://doi.org/10.1117/12.2640532
Event: Photomask Japan 2022, 2022, Online Only

Abstract

The common process window of EUV patterning is being limited when the 1-dimensional (1D) pitch shrinks to 32nm or below. There are many investigations and studies that propose an alternative EUV photomask absorber to mitigate photomask 3-dimensional (3D) topology effects and can partially mitigate the contrast fading effect and reduce through pitch best focus shift.^1,2,3 Another method to counter photomask 3D effects, is sub-resolution assistant features (SRAFs). SRAF insertion is one possible way to create a dense optical environment, which will prevent strong best focus shift from semi-isolated to isolated features. However, the side effect of SRAF insertion is unwanted SRAF printing occurring on the surface or bottom of the photoresist.⁴ In order to predict the partial removal or small residues of photoresist after the lithographic development process, a flow of compact photoresist 3D modeling (R3D) in conjunction with stochastic modeling can be adopted. In this paper, a bright field EUV photomask with regular 1D line-space grid design and positive tone development (PTD) are considered. The SEM images of through pitch 1D structures with various sizes of SRAFs are collected. To quantify SRAF printing, pixel brightness is compared to resist-opened background area, the printing SRAF regions can then be identified and clustered. Compact resist stochastic modeling is also performed by line-width roughness (LWR) sampling and used to predict SRAFs printing pixels by using Average Printing Area (APA) method with R3D modeling.⁵ Therefore, not only severe SRAF printing events can be predicted well, but also the accurate prediction of SRAF printing with very low probabilities can also be achieved.

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Chih-I Wei, Azat Latypov, Shuling Wang, Satya Sriram, Prakash Deep, Yunfei Deng, Ethan Maguire, Shumay Shang, Germain Fenger, and Werner Gillijns "EUV SRAFs printing modeling with bright field mask", Proc. SPIE 12325, Photomask Japan 2022: XXVIII Symposium on Photomask and Next-Generation Lithography Mask Technology, 1232506 (15 September 2022); https://doi.org/10.1117/12.2640532

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KEYWORDS

SRAF

Semiconducting wafers

Stochastic processes

Data modeling

Scanning electron microscopy

Photomasks

Extreme ultraviolet

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