Chinese Optics Letters, 2019, 17 (12): 121102, Published Online: Dec. 3, 2019   

Adaptive gradient-based source and mask co-optimization with process awareness Download: 907次

Author Affiliations
1 School of Automation, Guangdong University of Technology, Mega Education Center South, Guangzhou 510006, China
2 Guangxi Key Laboratory of Multimedia Communications and Network Technology, School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China
Abstract
We develop a source and mask co-optimization framework incorporating the minimization of edge placement error (EPE) and process variability band (PV Band) into the cost function to compensate simultaneously for the image distortion and the increasingly pronounced lithographic process conditions. Explicit differentiable functions of the EPE and the PV Band are presented, and adaptive gradient methods are applied to break symmetry to escape suboptimal local minima. Dependence on the initial mask conditions is also investigated. Simulation results demonstrate the efficacy of the proposed source and mask optimization approach in pattern fidelity improvement, process robustness enhancement, and almost unaffected performance with random initial masks.

Yijiang Shen, Fei Peng, Xiaoyan Huang, Zhenrong Zhang. Adaptive gradient-based source and mask co-optimization with process awareness[J]. Chinese Optics Letters, 2019, 17(12): 121102.

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