Ant Colony Optimization-Based Freeform Sources for Enhancing Nanolithographic Imaging Performance

As the complexity of mask patterns increases, the standard off-axis illumination in 193-nm immersion systems is increasingly becoming inadequate for high-quality lithography. In this study, a source optimization (SO) technique was employed for improving lithographic resolution. A pixel-based optimization process was developed for constructing freeform sources on a PC platform to enhance contrast and improve process window (PW). In the proposed SO algorithm, the metaheuristic binary ant colony optimization algorithm was applied for constructing the freeform sources. Moreover, the proposed algorithm converged to the optimal solution between the 300th and 400th iterations. The performance of this algorithm was assessed using the half pitch (hp) 45-nm line/space (L/S) and 55-nm SRAM contact hole (CH) patterns. The fitness function was quality of aerial image, exposure latitude (EL), and depth of focus (DOF); the constructed freeform sources enhanced the contrast and extended the PW for the patterns. The DOF increased from 0.91 to 1.1 μm and 0.042 to 0.061 μm for the L/S and SRAM CH patterns, respectively, at an EL of 5% when using the freeform source. Moreover, the freeform source improved the mask error enhancement factor by 22% for the SRAM pattern.