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30 July 2002 Assessment of different simplified resist models
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Resist modeling is an attractive way to predict the critical dimensions of patterned features after lithographic processing. Unfortunately, previous works have shown that model parameters are very difficult to determine and have often a poor range of validity outside the dataset that have been used to generate them. The goal of this work is to assess different simplified resist models using a systematic method. We have studied the accuracy of aerial image model and aerial image plus Gaussian noise convolution model. The approach is based on the comparison between simulated and experimental data for periodic lines of various dimensions at various illumination conditions. We also propose a reliable expression for Bossung curves fitting. Using simple physical considerations, the expression has been made very simple and efficient. After a proper setting of the model parameters to the experimental data, mean CD discrepancies between simulation and experiment are as small as 5% and can be 3% for certain feature types. Moreover, we show that simple Gaussian noise convolution models can be predictive with the same accuracy. The method for CD prediction is fully described in this paper. Significant improvements have been made in resists modeling over the last several years, but simplified resist models such as 'aerial image + Gaussian noise' seems to be an effective tool for CD prediction, which remains the major demand of IC manufacturers.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David Fuard, M Besacier, and Patrick Schiavone "Assessment of different simplified resist models", Proc. SPIE 4691, Optical Microlithography XV, (30 July 2002);

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