Basic approaches to photoresist mask formation modeling in computational lithography

The article gives an overview of the main currently used models for the formation of photoresist masks and the problems in which they are applied. The main stages of «full physical» modeling of mask formation are briefly considered in the case of both traditional DNQ photoresists and CA photoresists. The concept of compact models (VT5 and CM1), which predict the contour of the resist mask for a full-sized device topology is considered. Examples of some calculations using both full physical modeling and compact models are given. Using a full physical modeling of the resist mask formation the lithographic stack was optimized for a promising technological process. The optimum thickness ratios for the binary BARC used in the water immersion lithographic process are found. The problem of determining the optimal number of calibration structures that maximally cover the space of aerial image parameters was solved. To solve this problem, cluster analysis was used. Clustering was carried out using the k-means method. The optimal sample size was from 300 to 350 structures, the mean square error in this case is 1.4 nm, which slightly exceeds the noise of the process for 100 nm structures. Using SEM images for calibrating the VT5 model allows reducing the standard error of 40 structures to 1.18 nm.

photoresist, projection photolithography, VT5, CM1, k-means clustering

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