PRIMADONNA: a system for automated defect disposition of production masks using wafer lithography simulation

Today's reticle inspection tools can provide a wealth of information about defects. We introduce here a system called DIVAS: Defect Inspection Viewing, Archiving, and Simulation that fully uses and efficiently manages this wealth of defect information. In this paper, we summarize the features of DIVAS and describe in more detail PRIMADONNA, one of its components. Current reticle defect specifications are based, primarily, on defect size. Shrinking design rules, increasing MEEF and use of Optical Enhancement Techniques cause size to be an inadequate criterion for disposition. Furthermore, visual disposition of defects is not automated, strictly reproducible, or directly tied to wafer lithography. To compensate for these inadequacies, reticle specifications are set conservatively adding direct and hidden costs to the manufacturing process. PRIMADONNA, utilizing Prolith as the simulation engine, retrieves all defect and reference images saved from a KLA SLF77 inspection tool and processes them through a series of increasingly rigorous simulation stages. These include pre-filtering, aerial image formation, and post filtration. Difference metrics are used to quantify a defect's wafer impact. We will report results comparing PRIMADONNA decisions to manual classifications for a significant volume of inspections. Correlation between PRIMADONNA results and AIMS metrology will be presented.