As the device's design rule has been scaled down, the needs of robust and accurate OPC (Optical Proximity Correction)
model have been increased. In order to meet the needs, we adopt the method of increasing the image parameter space
coverage, such as using SEM-contour based OPC model which provides hundreds or thousands of measurement data set
from each SEM image. It differs from traditional model calibration measurement data set from 1D or 2D symmetric test
pattern which is just one CD measurement data from one pattern.
In SEM contour-based model OPC, it is important that what kinds of patterns are chosen for model calibration and how
the SEM image contours are extracted to improve model accuracy.
In this paper, we selected the SEM images for SEM contour modeling analyzing aerial image intensity variation. As
finding optically sensitive patterns, we could make robust and accurate OPC model across the process window. In this
SEM-contour based OPC modeling, we applied the method from commercial SEM company.
Recently, photolithography process is facing many difficulties in patterning the circuit adequately, mainly due to the rapid decrease of the k1 factor. The limitation of numerical aperture (NA) causes the distortion of printed patterns, such as corner rounding, line end shortening, and the different bias between isolated and dense figures. The optical proximity effect correction (OPC) is the most popular method to solve this problem. Especially, we should apply the model-based OPC to the critical layers as the circuit patterns get smaller and more complex. The success of model-based OPC largely depends on the quality of the model, which describes the physics in the resist under a specific optical condition. A "good" model should have both the low fitting error and the full chip coverage. Efforts to lower the fitting error can lead to the degradation of physical meaning, and this would result in insufficient coverage of the model. To settle this concern, we should extract test patterns for model calibration that cover all the aerial image properties of full chip geometry. The investigation for selecting the data set for optical model tuning is also necessary to prevent the final model to be over fitted. In this paper, we will present test pattern selection strategy for optical model, and resist model.
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