A Robust Approach for Process Variation Aware Mask Optimization
Jian Kuanga, Wing-Kai Chowb and Evangeline F.Y. Youngc
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.
As the minimum feature size continues to shrink, whereas the wavelength of light used for lithography remains constant, Resolution Enhancement Techniques are widely used to optimize mask, so as to improve the subwavelength printability. Besides correcting for error between the printed image and target shape, a mask optimization method also needs to consider process variation. In this paper, a robust mask optimization approach is proposed to optimize the process window as well as the Edge Placement Error (EPE) of the printed image. Experiments results on the public benchmarks are encouraging.
Full Text (PDF)