KEYWORDS: Lithography, Visual process modeling, Data modeling, Calibration, Diffusion, 3D modeling, Scanning electron microscopy, Optical proximity correction, Semiconducting wafers, 3D image processing
A traditional approach to construct a fast lithographic model is to match wafer top-down SEM images, contours and/or gauge CDs with a TCC model plus some simple resist representation. This modeling method has been proven and is extensively used for OPC modeling. As the technology moves forward, this traditional approach has become insufficient in regard to lithography weak point detection, etching bias prediction, etc. The drawback of this approach is from metrology and simulation. First, top-down SEM is only good for acquiring planar CD information. Some 3D metrology such as cross-section SEM or AFM is necessary to obtain the true resist profile. Second, the TCC modeling approach is only suitable for planar image simulation. In order to model the resist profile, full 3D image simulation is needed. Even though there are many rigorous simulators capable of catching the resist profile very well, none of them is feasible for full-chip application due to the tremendous consumption of computational resource. The authors have proposed a quasi-3D image simulation method in the previous study , which is suitable for full-chip simulation with the consideration of sidewall angles, to improve the model accuracy of planar models. In this paper, the quasi-3D image simulation is extended to directly model the resist profile with AFM and/or cross-section SEM data. Resist weak points detected by the model generated with this 3D approach are verified on the wafer.
Traditionally, an optical proximity correction model is to evaluate the resist image at a specific depth within the photoresist and then extract the resist contours from the image. Calibration is generally implemented by comparing resist contours with the critical dimensions (CD). The wafer CD is usually collected by a scanning electron microscope (SEM), which evaluates the CD based on some criterion that is a function of gray level, differential signal, threshold or other parameters set by the SEM. However, the criterion does not reveal which depth the CD is obtained at. This depth inconsistency between modeling and SEM makes the model calibration difficult for low k1 images. In this paper, the vertical resist profile is obtained by modifying the model from planar (2D) to quasi-3D approach and comparing the CD from this new model with SEM CD. For this quasi-3D model, the photoresist diffusion along the depth of the resist is considered and the 3D photoresist contours are evaluated. The performance of this new model is studied and is better than the 2D model.