Mask Pattern Recovery by Level Set Method based Inverse Inspection Technology (IIT) and its Application on Defect Auto Disposition

At the most advanced technology nodes, such as 32nm and 22nm, aggressive OPC and Sub-Resolution Assist Features (SRAFs) are required. However, their use results in significantly increased mask complexity, making mask defect disposition more challenging than ever. This paper describes how mask patterns can first be recovered from the inspection images by applying patented algorithms using Level Set Methods. The mask pattern recovery step is then followed by aerial/wafer image simulation, the results of which can be plugged into an automated mask defect disposition system based on aerial/wafer image. The disposition criteria are primarily based on wafer-plane CD variance. The system also connects to a post-OPC lithography verification tool that can provide gauges and CD specs, thereby enabling them to be used in mask defect disposition as well. Results on both programmed defects and production defects collected at Samsung mask shop are presented to show the accuracy and consistency of using the Level Set Methods and aerial/wafer image based automated mask disposition.