Paper
24 July 2002 Resist vector: connecting the aerial image to reality
Steven G. Hansen
Author Affiliations +
Abstract
Lithographic performance is controlled by both the projected aerial image and the photoresist process. It is usually easier to calculate the output of the optical system than to construct an accurate predictive model for the photoresist process. This point, coupled with the trend toward extremely high contrast photoresists where the resist starts to act like an ideal image threshold detector, means that aerial images alone are increasingly useful for predicting performance. In this work, discrepancies between resist processes with finite imaging contrast, and aerial image predictions are explored. The method used is to construct several lithographic problems (various line and hole patterns with high NA lenses) and to directly calculate differences for important responses such as exposure latitude, dense:isolated bias, and isofocal curvature. The expected performance range for resist processes can be found with a simulation program and systematically varied resist models, producing hundreds of trial cases. The results show that the resist process predictions deviate from the aerial image predictions in a consistent way; interpretable as a resist vector whose magnitude varies depending on the details of the resist process, but whose direction does not vary much. Knowledge of the vector provides a route for extrapolating aerial image calculations to what actually prints on the wafer. Physical explanations based on finite dissolution contrast and non-zero diffusion are offered. Where possible, experimental data is used to support the arguments.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven G. Hansen "Resist vector: connecting the aerial image to reality", Proc. SPIE 4690, Advances in Resist Technology and Processing XIX, (24 July 2002); https://doi.org/10.1117/12.474236
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Image processing

Photoresist processing

Diffusion

Lithography

Photomasks

Photoresist materials

Image analysis

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