Estimating pattern sensitivity to the printing process for varying dose/focus conditions for RET development in the sub-22nm era

Abstract

Evaluating pattern sensitivity to variability of the process parameters is of increasing importance to improve resolution enhancement techniques. In this paper, we propose an efficient algorithm to extract printed shapes from SEM images, a novel quality metric which analyzes the topology of the extracted printed shapes with respect to the target mask shape and a unique set of descriptors that define the sensitivity of a pattern. Compared to traditional CD methods, the proposed method has better accuracy, increased robustness and ability to spot global changes. Compared to contours distance methods, it is designed to expose most critical regions and capture context effects. © 2014 SPIE.