The use of computational inspection to identify process window limiting hotspots and predict sub-15 nm defects with high capture rate

摘要

As critical dimensions for advanced two dimensional (2D) DUV patterning continue to shrink, the exact process window becomes increasingly difficult to determine. The defect size criteria shrink with the patterning critical dimensions and are well below the resolution of current optical inspection tools. As a result, it is more challenging for traditional bright field inspection tools to accurately discover the hotspots that define the process window. In this study, we use a novel computational inspection method to identify the depth-of-focus limiting features of a 10 nm node mask with 2D metal structures (single exposure) and compare the results to those obtained with a traditional process windows qualification (PWQ) method based on utilizing a focus modulated wafer and bright field inspection (BFI) to detect hotspot defects. The method is extended to litho-etch litho-etch (LELE) on a different test vehicle to show that overlay related bridging hotspots also can be identified.