20 August 2004 Proximity-effect correction software for EPL using the pattern classify method
Author Affiliations +
Proceedings Volume 5446, Photomask and Next-Generation Lithography Mask Technology XI; (2004) https://doi.org/10.1117/12.557820
Event: Photomask and Next Generation Lithography Mask Technology XI, 2004, Yokohama, Japan
In electron projection lithography (EPL), a proximity-effect was the most significant problem to critical dimension (CD) control. It was remarkable, especially when beam blur was as large as the minimum pattern size. We have developed proximity-effect correction software for EPL to solve this problem. First, this software made a correction table automatically. In this table, the optimum biases were given for various backward-scattering energy levels and beam blurs regarding all kinds of model patterns. Next, every pattern edge was classified in any of the model patterns. Then, the bias for each edge was determined taking certain proportion between the correction table bias and the previous bias. After that, pattern shape was modified. Those processes were iterated until every change in bias was less than 0.5 nm. Finally, stitching pattern features were added. This software was tested using actual 70-nm rule chip data. Errors in energy level for various kinds of patterns were better than 3 percent and line end shortening was successfully corrected. Data size expansion after the correction was about 10 percent. Processing time was about 10 hours on six PCs cluster system. In conclusion, this software provides enough CD uniformity and pattern fidelity for EPL practically. In addition, this software is applicable to not only EPL but also to EB-direct writing.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shigeki Mori, Akio Sato, Kyoji Nakajo, Masanori Shoji, Naomi Shimada, Hirokazu Sambayashi, Kenzo Goto, Fumio Murai, Hiroshi Fukuda, "Proximity-effect correction software for EPL using the pattern classify method", Proc. SPIE 5446, Photomask and Next-Generation Lithography Mask Technology XI, (20 August 2004); doi: 10.1117/12.557820; https://doi.org/10.1117/12.557820

Back to Top