Model based pattern matching

Lawrence S. Melvin III; Josh Tuttle; Mathias Boman

doi:10.1117/12.810062

4 December 2008 Model based pattern matching

Lawrence S. Melvin III, Josh Tuttle, Mathias Boman

Proceedings Volume 7140, Lithography Asia 2008; 71402B (2008) https://doi.org/10.1117/12.810062
Event: SPIE Lithography Asia - Taiwan, 2008, Taipei, Taiwan

Abstract

An important need in the Optical Proximity Correction (OPC) process is to be able to identify problem correction areas. However, many times when a problem correction area is identified, multiple instances of the same problem occur throughout the correction. This can lead to potentially hundreds or thousands of repeated structures that must be filtered by the development engineer. In some instances, hundreds of thousands of problem areas may be identified, but in reality, all the areas are the same lithographic pattern. One way of identifying repeated patterns in an analysis data base is to use Boolean geometric logic to isolate matching patterns. The problem with this approach is determining what area is the area of process influence. This invariably leads to a conservative analysis of similar patterns, which leads to many repeated failures that are actually the same failure. This study will discuss a solution to this problem using process models and process model approximations to determine if patterns are the same from the point of view of the process. This will be accomplished using the output model intensity, the output model slope, and the pattern response to focus variation. When these three values are the same, it is hypothesized the layout patterns are the same from a process point of view. In addition, the study will discuss methodologies to speed up the model analysis and adjust accuracy and sensitivity.

Citation Download Citation

Lawrence S. Melvin III, Josh Tuttle, and Mathias Boman "Model based pattern matching", Proc. SPIE 7140, Lithography Asia 2008, 71402B (4 December 2008); https://doi.org/10.1117/12.810062

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KEYWORDS

Process modeling

Data modeling

Sensors

Optical proximity correction

Statistical analysis

Lithography

Optics manufacturing

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