As 193nm lithography continues to be stretched and the k1 factor decreases, optical proximity correction (OPC) has become a vital part of the lithographer's tool kit. Unfortunately, as is now well known, the design variations of lithographic scanners from different vendors cause them to have slightly different optical-proximity effect (OPE) behavior, meaning that they print features through pitch in distinct ways. This in turn means that their response to OPC is not the same, and that an OPC solution designed for a scanner from Company 1 may or may not work properly on a scanner from Company 2. Since OPC is not inexpensive, that causes trouble for chipmakers using more than one brand of scanner. Clearly a scanner-matching procedure is needed to meet this challenge. Previously, automatic matching has only been reported for scanners of different tool generations from the same manufacturer. In contrast, scanners from different companies have been matched using expert tuning and adjustment techniques, frequently requiring laborious test exposures. Automatic matching between scanners from Company 1 and Company 2 has remained an unsettled problem. We have recently solved this problem and introduce a novel method to perform the automatic matching. The success in meeting this challenge required three enabling factors. First, we recognized the strongest drivers of OPE mismatch and are thereby able to reduce the information needed about a tool from another supplier to that information readily available from all modern scanners. Second, we developed a means of reliably identifying the scanners' optical signatures, minimizing dependence on process parameters that can cloud the issue. Third, we carefully employed standard statistical techniques, checking for robustness of the algorithms used and maximizing efficiency. The result is an automatic software system that can predict an OPC matching solution for scanners from different suppliers without requiring expert intervention.
[1]
Stephen P. Renwick,et al.
Characterizing a scanner illuminator for prediction of OPE effects
,
2006,
SPIE Advanced Lithography.
[2]
Stephen P. Renwick,et al.
Effects of laser bandwidth on OPE in a modern lithography tool
,
2006,
SPIE Advanced Lithography.
[3]
Gurwan Kerrien,et al.
Illumination conditions matching for critical layers manufacturing in a production context
,
2006,
SPIE Advanced Lithography.
[4]
Stephen P. Renwick,et al.
Illumination pupil fill measurement and analysis and its application in scanner V-H bias characterization for 130-nm node and beyond
,
2003,
SPIE Advanced Lithography.
[5]
John J. Biafore,et al.
Optical Lithography Modeling
,
1997
.
[6]
Christopher P. Ausschnitt,et al.
Laser bandwidth and other sources of focus blur in lithography
,
2006
.
[7]
Ralf Ziebold,et al.
Impact of measured pupil illumination fill distribution on lithography simulation and OPC models
,
2004,
SPIE Advanced Lithography.
[8]
Geert Vandenberghe,et al.
Tool-to-tool optical proximity effect matching
,
2008,
SPIE Advanced Lithography.
[9]
Stephen P. Renwick.
What makes a coherence curve change?
,
2004,
SPIE Advanced Lithography.