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Article

Patterning Fidelity Enhancement and Aberration Mitigation in EUV Lithography Through Source–Mask Optimization

1
School of Micro-Electronics, Fudan University, Shanghai 200433, China
2
National Integrated Circuit Innovation Center, Shanghai 201204, China
*
Author to whom correspondence should be addressed.
Micromachines 2025, 16(10), 1166; https://doi.org/10.3390/mi16101166 (registering DOI)
Submission received: 8 September 2025 / Revised: 1 October 2025 / Accepted: 13 October 2025 / Published: 14 October 2025
(This article belongs to the Special Issue Recent Advances in Lithography)

Abstract

Extreme ultraviolet (EUV) lithography faces critical challenges in aberration control and patterning fidelity as technology nodes shrink below 3 nm. This work demonstrates how Source–Mask Optimization (SMO) simultaneously addresses both illumination and mask design to enhance pattern transfer accuracy and mitigate aberrations. Through a comprehensive optimization framework incorporating key process metrics, including critical dimension (CD), exposure latitude (EL), and mask error factor (MEF), we achieve significant improvements in imaging quality and process window for 40 nm minimum pitch patterns, representative of 2 nm node back-end-of-line (BEOL) requirements. Our analysis reveals that intelligent SMO implementation not only enables robust patterning solutions but also compensates for inherent EUV aberrations by balancing source characteristics with mask modifications. On average, our results show a 4.02% reduction in CD uniformity variation, concurrent with a 1.48% improvement in exposure latitude and a 5.45% reduction in MEF. The proposed methodology provides actionable insights for aberration-aware SMO strategies, offering a pathway to maintain lithographic performance as feature sizes continue to scale. These results underscore SMO’s indispensable role in advancing EUV lithography capabilities for next-generation semiconductor manufacturing.
Keywords: Source–Mask Optimization; computational lithography; lithography imaging model; pattern fidelity; aberration control Source–Mask Optimization; computational lithography; lithography imaging model; pattern fidelity; aberration control

Share and Cite

MDPI and ACS Style

Wang, Q.; Wu, Q.; Li, Y.; Liu, X.; Li, Y. Patterning Fidelity Enhancement and Aberration Mitigation in EUV Lithography Through Source–Mask Optimization. Micromachines 2025, 16, 1166. https://doi.org/10.3390/mi16101166

AMA Style

Wang Q, Wu Q, Li Y, Liu X, Li Y. Patterning Fidelity Enhancement and Aberration Mitigation in EUV Lithography Through Source–Mask Optimization. Micromachines. 2025; 16(10):1166. https://doi.org/10.3390/mi16101166

Chicago/Turabian Style

Wang, Qi, Qiang Wu, Ying Li, Xianhe Liu, and Yanli Li. 2025. "Patterning Fidelity Enhancement and Aberration Mitigation in EUV Lithography Through Source–Mask Optimization" Micromachines 16, no. 10: 1166. https://doi.org/10.3390/mi16101166

APA Style

Wang, Q., Wu, Q., Li, Y., Liu, X., & Li, Y. (2025). Patterning Fidelity Enhancement and Aberration Mitigation in EUV Lithography Through Source–Mask Optimization. Micromachines, 16(10), 1166. https://doi.org/10.3390/mi16101166

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