The model calibration process, in a resolution enhancement technique (RET) flow, is one of the most critical steps towards building an accurate OPC recipe. RET simulation platforms use models for predicting latent images in the wafer due to exposure of different design layouts. Accurate models can precisely capture the proximity effects for the lithographic process and help RET engineers build the proper recipes to obtain high yield. To calibrate OPC models, test geometries are created and exposed through the lithography environment that we want to model, and metrology data are collected for these geometries. This data is then used to tune or calibrate the model parameters. Metrology tools usually provide critical dimension (CD) data and not edge placement error (EPE - the displacement between the polygon and resist edge) data however model calibration requires EPE data for simulation. To work around this problem, only symmetrical geometries are used since, having this constraint, EPE can be easily extracted from CD measurements.
In real designs, it is more likely to encounter asymmetrical structures as well as complex 2D structures that can not easily be made symmetrical, especially when we talk about technology nodes for 65nm and beyond. The absence of 2D and asymmetric test structures in the calibration process would require models to interpolate or extrapolate the EPE?s for these structures in a real design.
In this paper we present an approach to extract the EPE information from both SEM images and contours extracted by the metrology tools for structures on test wafers, and directly use them in the calibration of a 55nm poly process. These new EPE structures would now mimic the complexity of real 2D designs. Each of these structures can be individually weighed according to the data variance. Model accuracy is then compared to the conventional method of calibration using symmetrical data only. The paper also illustrates the ability of the new flow to extract more accurate measurement out of wafer data that are more immune to errors compared to the conventional method.