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Damage-to-dose ratio after low energy silicon ion implantation into crystalline silicon

Published online by Cambridge University Press:  03 March 2011

Y. Levin
Affiliation:
Electrical, Computer and Systems Engineering Department, Boston University, Boston, Massachusetts 02215
N. Herbots
Affiliation:
Department of Physics and Astronomy, Arizona State University, Tempe, Arizona 85287
S. Dunham
Affiliation:
Electrical, Computer and Systems Engineering Department, Boston University, Boston, Massachusetts 02215
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Abstract

In this work, we develop a model describing the diffusion of vacancies and self-interstitials and their recombination during ion implantation. The model includes the effect of the moving surface due to regrowth and the defect generation rate as a function of depth based on Monte Carlo simulations. The results are compared to experimental measurements of the damage-to-dose ratio (DDR) after low energy, 40 eV, silicon ion implantation into silicon at 300 and 685 K. We have derived an analytic approximation which agrees with the results of the computational model, implemented on a CM-2 parallel computer. We find that the calculated effective diffusivity, the main adjustable parameter in the simulations, is much lower than predicted based on extrapolation from experiments at higher temperatures. We attribute this difference to the aggregation of self-interstitials. We also find that the effect of interstitial-vacancy recombination on DDR is negligible under the experimental conditions considered; however, the crystal surface motion has a significant impact on the results.

Type
Articles
Copyright
Copyright © Materials Research Society 1993

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References

REFERENCES

1Herbots, N., Appleton, B. R., Noggle, T. S., Zuhr, R. A., and Pennycook, S. J., Nucl. Instrum. Methods B 13, 250 (1986).CrossRefGoogle Scholar
2Herbots, N., Hellman, O. C., Cullen, P. A., and Vancauwenberghe, O., in Deposition & Growth: Limits for Microelectronics, edited by Rubloff, G.W. (AIP, New York, 1988), Vol. 167, p. 259.Google Scholar
3Biersack, J. P. and Ecstein, W., Appl. Phys. A 34, 73 (1984).CrossRefGoogle Scholar
4Vancauwenberghe, O., Herbots, N., and Hellman, O., J. Vac. Sci. Technol. B 9, 2027 (1991).CrossRefGoogle Scholar
5The Connection Machine System (Thinking Machines Corporation, Cambridge, MA, 1991).Google Scholar
6Volkov, E. A., Chislennye Methody (Numerical Methods) (Nauka, Moscow, 1987).Google Scholar
7Samarsky, A. A., Vvedenie v Chislennye Methody (Introduction to Numerical Methods) (Nauka, Moscow, 1987).Google Scholar
8Smirnov, V. I., Kurs Vysshey Matematiki (Course of High Mathematics) (Nauka, Moscow, 1974), p. 642.Google Scholar
9Tan, T. Y. and Gosele, U., J. Appl. Phys. A 37, 1 (1985).CrossRefGoogle Scholar