The effect of OPC optical and resist model parameters on the model accuracy, run time, and stability

Aerial image metrology (AIMS) based mask-model accuracy improvement for computational lithography

“…Accuracy of the aerial mage model has always been recognized as a key component to overall OPC (optical proximity correction) model accuracy, and in recent years there has been renewed emphasis on model accuracy, as approaches to modeling stochastic effects are closely tied to image parameters such as ILS or Imax (image peak intensity) [1][2][3][4][5]. For example, image log slope (ILS) is directly correlated to the stochastic edge placement error (SEPE) bands and the achievable local critical dimension uniformity (LCDU).…”

Fundamental study on the error factor for sub 90nm OPC modeling

“…The accuracy of these models depends on the accuracy of the calibration process 1 , the accuracy of the calibration process in turn, depends on the quality of the data collected 5 . The optical and resist model parameters selected during model calibration have a significant impact on the OPC model accuracy, runtime, and model stability 1 . In order to avoid unpractical runtimes a compromise between the runtime and model accuracy has to be performed.…”

“…As generally known OPC modeling is based on empirical data as input to the model calibration tool that fits the optical and resist behavior of the given process, these model data from modeling will predict actual images on wafer after exposure of real product data base (DB) 1 . Model-based OPC is usually divided into two steps 2 ; first, optical models which are used to predict the influence of optical imaging on wafer extract a prediction of aerial images as it is calculated with actual exposure system.…”