The role of mask topography effects in the optimization of pixelated sources

Abstract

Ongoing technology node shrinkage requires the lithographic k 1 factor to be pushed closer to its theoretical limit. The application of customized illumination with multi-pole or pixelated sources has become necessary for improving the process window. For standardized exploitation of this technique it is crucial that the optimum source shape and the corresponding intensity distributions can be found in a robust and automated way. In this paper we present a pixelated source optimization procedure and its results. A number of application cases are considered with the following optimization goals: i) enhancement of the depth of focus, ii) improvement of through-pitch behavior, and iii) error sensitivity reduction. The optimization procedure is performed with fixed mask patterns, but at multiple locations. To reduce optical proximity errors, mask biasing is introduced. The optimization results are obtained for the pixelated source shapes, analyzed and compared with the corresponding results for multi-pole shaped sources. Starting with the 45 nm node mask topography effects as well as light polarization conditions have significant impact on imaging performance. Therefore including these effects into the optimization procedure has become necessary for advanced process nodes. To investigate these effects, the advanced topographical mask illumination concept (AToMIC) for rigorous and fast electromagnetic field simulation under partially coherent illumination is applied. We demonstrate the impact of mask topography effects on the results of the source optimization procedure by comparison to corresponding Kirchhoff simulations. The effects of polarized illumination sources are taken into account.

Point-source approach of source-mask optimization

“…The source optimization is based on point-source approach [1][2][3][4][5] . The evaluation of imaging performance metrics for each individual source point is performed and the combination of these metrics creates a pupil mapping.…”