With advanced CMOS technologies, model-based optical proximity correction (OPC) has become the most important aspect of post-tape-out data preparation for critical mask levels. While fabrication processes certainly remain the foundation of a qualified
technology, the quality of OPC is increasingly moving into the focus of efforts to further improve yield. For a typical model-based OPC tool, the full OPC model consists of two distinct parts: (1) An aerial image part, based on a few, well-defined optical parameters of the lithography tool to describe the light intensity
distribution in air at the wafer level and (2) an empirical part to model all other aspects of the pattern transfer, based on different black box modeling techniques such as kernel convolution or variable threshold modeling. Most importantly, the parameters for the empirical part are usually determined by fitting the model to proximity data measured from test structures. As a consequence, the robustness of the full OPC model for productive usage correlates directly with the extent to which these test structures provide a representative sampling of the circumstances encountered in an actual product layout. In order to determine the quality of this sampling, full-chip aerial image analyses are performed for various mask levels of a product design. A comparison of the characteristics of the light intensity distributions of this design with the corresponding
information obtained from the test structures reveals configurations that are not well covered by the latter. This insight allows the definition of suitable additional test structures in order to improve the robustness of subsequent empirical OPC models.