TY - JOUR
T1 - Fast source mask co-optimization method for high-NA EUV lithography
AU - Li, Ziqi
AU - Dong, Lisong
AU - Ma, Xu
AU - Wei, Yayi
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024
Y1 - 2024
N2 - Extreme ultraviolet (EUV) lithography with high numerical aperture (NA) is a future technology to manufacture the integrated circuit in sub-nanometer dimension. Meanwhile, source mask co-optimization (SMO) is an extensively used approach for advanced lithography process beyond 28 nm technology node. This work proposes a novel SMO method to improve the image fidelity of high-NA EUV lithography system. A fast high-NA EUV lithography imaging model is established first, which includes the effects of mask three-dimensional structure and anamorphic magnification. Then, this paper develops an efficient SMO method that combines the gradient-based mask optimization algorithm and the compressive-sensing-based source optimization algorithm. A mask rule check (MRC) process is further proposed to simplify the optimized mask pattern. Results illustrate that the proposed SMO method can significantly reduce the lithography patterning error, and maintain high computational efficiency.
AB - Extreme ultraviolet (EUV) lithography with high numerical aperture (NA) is a future technology to manufacture the integrated circuit in sub-nanometer dimension. Meanwhile, source mask co-optimization (SMO) is an extensively used approach for advanced lithography process beyond 28 nm technology node. This work proposes a novel SMO method to improve the image fidelity of high-NA EUV lithography system. A fast high-NA EUV lithography imaging model is established first, which includes the effects of mask three-dimensional structure and anamorphic magnification. Then, this paper develops an efficient SMO method that combines the gradient-based mask optimization algorithm and the compressive-sensing-based source optimization algorithm. A mask rule check (MRC) process is further proposed to simplify the optimized mask pattern. Results illustrate that the proposed SMO method can significantly reduce the lithography patterning error, and maintain high computational efficiency.
KW - computational lithography
KW - high-NA EUV lithography
KW - lithography imaging model
KW - source-mask co-optimization
UR - http://www.scopus.com/inward/record.url?scp=85192472978&partnerID=8YFLogxK
U2 - 10.29026/oea.2024.230235
DO - 10.29026/oea.2024.230235
M3 - Article
AN - SCOPUS:85192472978
SN - 2096-4579
VL - 7
JO - Opto-Electronic Advances
JF - Opto-Electronic Advances
IS - 4
M1 - 230245
ER -