Besides models describing the exposure tool optical system, lumped parameter resist models are the other important model used during OPC. This combination is able to deliver the speed and accuracy required during OPC. Lumped parameter resist models are created by fitting a polynomial to empirical data. The parameters of this polynomial are usually image parameters (maximum and minimum intensity, slope, curvature) taken from the optical simulation for each measured structure. During calibration of such models, it is very important to pay attention to the parameter space covered by the calibration pattern used. We analyze parameter space coverage for standard calibration patterns, real layout situation post OPC correction as well as pre OPC correction. Taking this one step further, the influence of parameter space coverage during model calibration on OPC convergence is also studied.

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