Accuracy vs. complexity: OPC solutions and tradeoffs

Evolution of Optical Proximity Correction (OPC) methodology with the continuing shrink of feature size indicates a gradual shift towards increasingly more complex solutions, i.e., from rule based to model based OPC. The key underlying reason is to provide adequate accuracy of pattern reproduction despite the growing sub-wavelength gap, i.e., the difference between minimum feature size and the wavelength used to print it [1]. However, full chip implementation of these complex solutions would increase CAD flow/mask generation runtimes and database file sizes, therefore compromising reticle manufacturability. In order to select optimal OPC routines based on feedback from process, CAD, design, and mask,engineering, we proposed a methodology and investigated tradeoffs between correction accuracy and database complexity. Rule-based OPC, i.e., corrections defined by a set of width and spacing proximity rules rely on a limited set of test geometries and can't be made sensitive to the environment of the feature. In contrast, model based OPC features are generated for the actual layout environment and can be changed depending on the adopted photolithography process. Another degree of freedom is provided by the rule or model calibration. We defined and discussed complexity and accuracy criteria such as the size of the database and the number of silicon imaging errors.