One of the major challenges of optical proximity correction (OPC) models is to maximize the coverage of real design
features using sampling pattern. Normally, OPC model building is based on 1-D and 2-D test patterns with
systematically changing pitches alignment with design rules. However, those features with different optical and
geometric properties will generate weak-points where OPC simulation cannot precisely predict resist contours on wafer
due to the nature of infinite IC designs and limited number of model test patterns. In this paper, optical property data of
real design features were collected from full chips and classified to compare with the same kind of data from OPC test
patterns. Therefore sample coverage could be visually mapped according to different optical properties. Design
features, which are out of OPC capability, were distinguished by their optical properties and marked as weak-points.
New patterns with similar optical properties would be added into model build site-list. Further, an alternative and more
efficient method was created in this paper to improve the treatment of issue features and remove weak-points without
rebuilding models. Since certain classification of optical properties will generate weak-points, an OPC-integrated repair
algorithm was developed and implemented to scan full chip for optical properties, locate those features and then
optimize OPC treatment or apply precise sizing on site. This is a named “in-situ” weak-point improvement flow which
includes issue feature definition, allocation in full chip and real-time improvement.