Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-29T14:38:01.832Z Has data issue: false hasContentIssue false
  • English
  • Français

A Model of Chemical Mechanical Planarization to Predict Impact of Pad Conditioning on Process Performance

Published online by Cambridge University Press:  30 July 2012

G. Bahar Basim  and
Serkan Kincal
G. Bahar Basim
Affiliation:
Department of Mechanical Engineering, Ozyegin University, Istanbul, 34794, Turkey.
Serkan Kincal
Affiliation:
Department of Chemical Engineering, Middle East Technical University, Ankara, 06800, Turkey.
Get access

Abstract

This study presents an effort to couple a wafer removal rate profile model based on the locally relevant Preston equation to the change in pad thickness profile which reflects to post polish profile of the wafers after Chemical Mechanical Planarization. The result is a dynamic predictor of how the wafer removal rate profile shifts as the pad ages. These predictions can be used to fine tune the conditioner operating characteristics without having to carry out high cost and time consuming experiments. The accuracy of the predictions is demonstrated by individual confirmation experiments in addition to the evaluation of the defectivity performance with the varied pad conditioning profiles.

Keywords

CMPmicroelectronicsdefects
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1428: Symposium C – “Interconnect Challenges for CMOS Technology--Materials, Processes and Reliability for Downscaling, Packaging and 3D Stacking” , 2012 , mrss12-1428-c06-05
Copyright
Copyright © Materials Research Society 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Gu, Y., Chang, S., Zhang, G., Kirmse, K., Rogers, D., Olsen, L., and Lewellen, J., Metrology, Inspection and Process Control for Microlithography XX, Proc. of SPIE, 6152, pp. 1–11, (2006)Google Scholar
2. Philip, G. K. H., King, T. Y., and Ping, S. G., Metrology, Inspection and Process Control for Microlithography XV, Proc. of SPIE, 4344, pp. 274–281, (2001)Google Scholar
3. Wang, G-B., Lin, E-H., You, H-S., Lee, M-W., Hsiao, F-K, and Lai, C-W., IEEE Journal, 8469-5/04, pp. 178–181, (2004)Google Scholar
4. Chen, A., Guo, R-S, Chou, Y. L., Lin, C. L., Dun, J. and Wu, S. A., IEEE Journal, 5403–6/99, pp229-232, (1999)Google Scholar
5. Smith, T. H., Fang, S. J., Stefani, J. A., Shinn, G. B., Boning, D. S., and Butler, S. W., J. Vac. Sci. Technol., A 17(4), pp. 1384–1390, (1999)Google Scholar
6. Lutzen, J., Pal, S., Gonzales, S., and Yuval, Bar, Part of the SPIE Conference on Process, Equipment and Materials Control in Integrated Circuit Manufacturing V, SPIE Vol. 3882, pp. 36–44, (1999)Google Scholar
7. Shiu, S-Y., Yu, C-C., and Shen, S-H., J. Vac. Sci. Technol., B 22(4), pp. 1679–1687, (2004)Google Scholar
8. E Chemali, C., Moyne, J., Khan, K., Nadeau, R., Smith, P., Colt., J., Chapple-Sokol, J., and Parikh, T., J. Vac. Sci. Technol., A 18(4), pp. 1287–1296, (2000)Google Scholar
9. Achuthan, K., Curry, J., Lacy, M., Campbell, D. and Babu, S., Journal of Electronic Materials, 10, (1996)Google Scholar
10. Manabu, T., Journal of Electronics, 6, pp. 96–103, (2001)Google Scholar
11. Runnels, S. R., Kim, I., Schleuter, J., Karlsrud, C., and Desai, M., IEEE Trans. Semi-cond. Manuf., 11, 501, (1998)Google Scholar
12. Castillo-Mejia, D., and Beaudoin, S., Journal of the Electrochemical Society, 150(2), pp. G96–G102, (2003)Google Scholar
13. Tseng, W-T., Chin, J-H., and Kang, L-C, Journal of the Electrochemical Society, 146(5), pp. 1952–1959, (1999)Google Scholar
14. Tyan, F., Proceedings of the American Control Conference, pp. 2052–2057, (2005)Google Scholar
15. Chen, C-Y., Yu, C-C., Shen, S-H., and Ho, M., Journal of the Electrochemical Society, 147(10), pp. 3922–3930, (2000)Google Scholar