Uncertainty aware site selection method for OPC model calibration

Traditionally, an image parameter metric has been used to analyze the lithography and resist responses versus the test pattern coverage. This metric assumes a variable threshold resist model which is not necessarily the state-of-the art model type used in the latest technology nodes. Additionally, these methods don’t consider the statistical nature of the variations where the number of the selected patterns can greatly affect the uncertainty of the model prediction for another set of patterns. We propose a new method that combines the lithography response with uncertainty analysis to select test patterns for OPC model calibration. We also propose a new metric based on resist response to be considered in site selection for advanced resist models. We show that uncertainty aware site selection combined with this new metric gives similar or better model accuracy compared to baseline which requires engineering expertise and other site clustering tools, but with large amount of calibration site reduction. Examples from advanced nodes are given.