Hostname: page-component-76fb5796d-x4r87 Total loading time: 0 Render date: 2024-04-26T22:02:05.075Z Has data issue: false hasContentIssue false

Modeling of Dopant Diffusion during Annealing of Sub-Amorphizing Implants

Published online by Cambridge University Press:  22 February 2011

Scott Dunham*
Affiliation:
Electrical, Computer and Systems Engineering Department, Boston University, Boston, MA 02215
Get access

Extract

Ion implant annealing is a complicated process involving the interactions of point defects generated during the implantation, implanted or previously present dopants, and extended defects which form as a result of the implant damage. To effectively model the process, it is essential to determine the critical processes, assess the validity of assumptions and calculate appropriate parameter values. In addition, implant annealing is just one element in the VLSI fabrication process, and the model development must consider the process as part of the broad range of experimental observations, as it is only through consistent physical models that simulators can predict the multiple interactions and two and three-dimensional effects present in VLSI structures. This work focuses on enhanced diffusion following silicon implants below the amorphization threshold as a function of dose, energy and time.

Type
Research Article
Copyright
Copyright © Materials Research Society 1994

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 Vancauwenberghe, O., Herbots, N. and Hellman, O., J. Vac. Set. Tech. B (9), 2027 (1991).Google Scholar
2 Biersack, J. P. and Ecstein, W., Appl. Phys. A34, 73 (1984).Google Scholar
3 Giles, M. D., J. Electrochem. Soc. 138, 1160 (1991).Google Scholar
4 Packan, P. A., Ph.D thesis, Stanford Univ., Feb. 1991.Google Scholar
5 Park, H. and Law, M. E., Appl. Phys. Lett. 58, 732 (1991).Google Scholar
6 Cowern, N. E. B., in Process Physics and Modeling in Semiconductor Technology, ed. by Srinivasan, G. R., Taniguchi, K. and Murthy, C. S., pp. 2033 (1993).Google Scholar
7 Taylor, W., Gösele, U. and Tan, T. Y., in Process Physics and Modeling in Semiconductor Technology, ed. by Srinivasan, G. R., Taniguchi, K. and Murthy, C. S., pp. 319 (1993).Google Scholar
8 Gösele, U. and Tan, T. Y., in Defects in Semiconductors II, ed. by Mahajan, S. and Corbett, J. W., p. 45 (1983).Google Scholar
9 Bronner, G. B. and Plummer, J. D., J. Appl. Phys. 61, 5286 (1987).Google Scholar
10 Dunham, S. T., in Process Physics and Modeling in Semiconductor Technology, ed. by Srinivasan, G. R., Taniguchi, K. and Murthy, C. S., pp. 5465 (1993).Google Scholar
11 Mulvaney, B. J., Richardson, W. B. and Crandle, T. L., IEEE Trans. Comp. Aid. Des. 8, 336 (1989).Google Scholar
12 L Ouwerling, G. J., The PROFILE/PROF2D User’s Manual (Delft University of Technology, 1987).Google Scholar
13 Griffin, P. B. and Plummer, J. D., Proceedings of the Electrochemical Society Meeting, San Diego, CA, October 1986.Google Scholar
14 Park, H. and Law, M. E., J. Appl. Phys. 72, 3431 (1992).Google Scholar
15 Guerrero, E., Jüngling, W., Pötzl, H., Gösele, U., Grasserbauer, M. and Stingeder, G., J. Electrochem. Soc. 133, 2181 (1986).Google Scholar
16 Crowder, S. W., Griffin, P. B. and Plummer, J. D., in Process Physics and Modeling in Semiconductor Technology, ed. by Srinivasan, G. R., Taniguchi, K. and Murthy, C. S., pp. 108119 (1993).Google Scholar