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Applications of enhanced optical proximity correction models

The accurate prediction of relevant optical and other processing effects is the essential first element of optical proximity effect (OPC) methodologies. A quasi-empirical modeling technique has been devised. Starting from standard aerial-image energy deposition, an exponential transfer function is employed to account for saturation effects. This is then followed by a double-Gaussian diffusion convolution. Finally, a novel 2-dimensional log-slope model was devised to better predict some DUV processes. The model parameters are derived from a few empirical measurements and a fitting process. The calibrated model is then used by a rule-based OPC package to correct a variety of structures. Efficient verification techniques suitable for large area designs are introduced.