Pupilgram adjusting scheme using intelligent illuminator for ArF immersion exposure tool

Abstract

Source Mask Optimization¹ (SMO) is one of the most important techniques available for extending ArF immersion lithography. However, imaging with a small k1 factor (~0.3 or smaller) is very sensitive to errors in the imaging system, such as lens apodization, process control, mask error, etc. As a result, the real source shape must be re-adjusted to realize expected imaging performance as may be seen, for example, in an OPE curve. The intelligent illuminator can modify the pupilgram with high spatial and intensity resolution in the pupil. But the question is: How to adjust the pupilgram parameters properly to match target OPE? In this paper we present and describe a pupilgram adjusting method that can effectively control the various illuminator parameters. The method uses pupilgram modulation functions, which are similar to Zernike polynomials used in wavefront analysis, to describe the optimal pupilgram adjustment. The resulting modulation can then be realized by the intelligent illuminator. We demonstrate the effect of this method and the relation to minimum pupil resolution and gray scale levels that are needed for the intelligent illuminator to achieve its goals. In addition, a pupil analysis scheme, which is suitable for the applied pupilgram adjustment method, is proposed and validated. Using this method, SMO solutions will be more realistic and practically achievable for extending ArF immersion lithography.