Gradient-based joint source polarization mask optimization for optical lithography

Xu Ma; Lisong Dong; Chunying Han; Jie Gao; Yanqiu Li; Gonzalo R. Arce

doi:10.1117/1.JMM.14.2.023504

5 May 2015 Gradient-based joint source polarization mask optimization for optical lithography

Xu Ma, Lisong Dong, Chunying Han, Jie Gao, Yanqiu Li, Gonzalo R. Arce

Author Affiliations +

Funded by: National Natural Science Foundation of China (NSFC), National Natural Science Foundation of China, Natural Science Foundation of China, Key Program of National Natural Science Foundation of China, National Science and Technology Major Project, Program of Education Ministry for Changjiang Scholars in University, the National Natural Science Foundation of China, National Science and Technology Major Project, National Natural Science Foundation of China, Changjiang Scholars in University, the National Natural Science Foundation of China, Program for New Century Excellent Talents in University, New Century Excellent Talents in University, Program for New Century Excellent Talents in University (New Century Excellent Talents Program)

Journal of Micro/Nanolithography, MEMS, and MOEMS, Vol. 14, Issue 2, 023504 (May 2015). https://doi.org/10.1117/1.JMM.14.2.023504

Abstract

Source and mask optimization (SMO) has emerged as a key resolution enhancement technique for advanced optical lithography. Current SMO, however, keeps the polarization state fixed, thus limiting the degrees of freedom during the optimization procedure. To overcome this limitation, pixelated gradient-based joint source polarization mask optimization (SPMO) approaches, which effectively extend the solution space of the SMO problem by introducing polarization variables, are developed. First, the SPMO framework is formulated using an integrative and analytic vector imaging model that is capable of explicitly incorporating the polarization angles. Subsequently, two optimization methods, namely simultaneous SPMO (SISPMO) and sequential SPMO (SESPMO) are developed, both of which exploit gradient-based algorithms to solve for the optimization problem. In addition, a postprocessing method is applied to reduce the complexity of the optimized polarization angle pattern for improving its manufacturability. Illustrative simulations are presented to validate the effectiveness of the proposed algorithms. The simulations also demonstrate the superiority of the SESPMO over SISPMO in computational efficiency and improvement of image fidelity.

Citation Download Citation

Xu Ma, Lisong Dong, Chunying Han, Jie Gao, Yanqiu Li, and Gonzalo R. Arce "Gradient-based joint source polarization mask optimization for optical lithography," Journal of Micro/Nanolithography, MEMS, and MOEMS 14(2), 023504 (5 May 2015). https://doi.org/10.1117/1.JMM.14.2.023504

Published: 5 May 2015

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