
Proceedings Paper
The effect of the OPC parameters on the performance of the OPC modelFormat | Member Price | Non-Member Price |
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Paper Abstract
Model based optical proximity correction (MB-OPC) is essential for the production of advanced integrated circuits
(ICs). As the speed and functionality requirements of IC production necessitate continual reduction of the critical
dimension (CD), there is a heightened demand for more accurate and sophisticated OPC models.
The OPC is applied to the design data through a rule deck. The parameters in this rule deck, which we will call
"setup parameters", describe the fundamental way in which the OPC engine will distinguish which edges to move,
their restrictions to movement, and how the targets for the OPC are chosen. The optimization of these setup
parameters, by customizing how the OPC engine should treat specific designs, is an essential step that is performed
in order to maximize the benefit of the OPC model. Improper or deficient selection of the setup parameters strongly
affects the success or failure of the OPC model and engine to achieve the desired design shapes.
In this paper, the ability of setup parameter optimization to compensate for a weak OPC model, or conversely, how
inadequately selected setup parameters can cause a very good OPC model to function poorly is investigated. Our
approach is to use two OPC models: a good OPC model and a weak OPC model. The setup parameters will be
optimized for the weak OPC model to investigate any improvements in the overall OPC performance. Alternatively,
setup parameters chosen poorly will be used with the good OPC model to see how this will adversely affect the OPC
performance. A comparative study will be carried out in order to fully understand the effect of setup file parameters
on the overall OPC performance.
The general goal of this study is to help the OPC modelers and setup parameters optimizers to improve the quality
and performance of the OPC solution and weigh the tradeoffs associated with different OPC solution choices.
Paper Details
Date Published: 1 November 2007
PDF: 11 pages
Proc. SPIE 6730, Photomask Technology 2007, 673055 (1 November 2007); doi: 10.1117/12.746696
Published in SPIE Proceedings Vol. 6730:
Photomask Technology 2007
Robert J. Naber; Hiroichi Kawahira, Editor(s)
PDF: 11 pages
Proc. SPIE 6730, Photomask Technology 2007, 673055 (1 November 2007); doi: 10.1117/12.746696
Show Author Affiliations
Amr Abdo, IBM Systems and Technology Group (United States)
Ahmed Seoud, Mentor Graphics Corp. (United States)
Alexander Wei, IBM Systems and Technology Group (United States)
Ahmed Seoud, Mentor Graphics Corp. (United States)
Alexander Wei, IBM Systems and Technology Group (United States)
Ian Stobert, IBM Systems and Technology Group (United States)
Alan Leslie, IBM Systems and Technology Group (United States)
Alan Leslie, IBM Systems and Technology Group (United States)
Published in SPIE Proceedings Vol. 6730:
Photomask Technology 2007
Robert J. Naber; Hiroichi Kawahira, Editor(s)
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