Defect disposition and qualification with stepper simulating AIMS tools on advanced masks of the 90nm node and below is key to match the customer's expectations for "defect free" masks, i.e. masks containing only nonprinting design variations. The recently available AIMS tools allow for a large degree of automated measurements enhancing the throughput of masks and hence reducing cycle time -up to 50 images can be recorded per hour. However, this amount of data still has to be evaluated by hand which is not only time-consuming but also error prone and exhibits a variability depending on the person doing the evaluation which adds to the tool intrinsic variability and decreases the reliability of the evaluation. In this paper we present the results of an MatLAB based algorithm which automatically evaluates AIMS images. We investigate its capabilities regarding throughput, reliability and matching with handmade evaluation for a large variety of dark and clear defects and discuss the limitations of an automated AIMS evaluation algorithm.

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