Thick-mask optimization based on particle swarm optimization algorithm

Abstract

Extreme ultraviolet lithography (EUV) is a key technology for micro-nano processing and is widely used in the chip manufacturing process. Mask optimization is one of the key resolution enhancement techniques in EUV lithography. In this paper, a thick mask optimization method based on particle swarm optimization (PSO) algorithm is proposed to improve simulation accuracy and imaging quality. In this work, we change the calculation order of formulas, which is used to accelerate the imaging calculations. The equivalent film layer method is used to approximate the reflection coefficients of thick mask multilayer film structures to improve the simulation accuracy. The inverse lithography problem for thick mask optimization is solved by particle swarm optimization algorithm. The simulation results show that this method can effectively improve the simulation accuracy and imaging quality.