A phenomenological electronic stopping power model for molecular dynamics and Monte Carlo simulation of ion implantation into silicon

Details A phenomenological electronic stopping power model for molecular dynamics and Monte Carlo simulation of ion implantation into silicon A phenomenological electronic stopping power model for molecular dynamics and Monte Carlo simulation of ion implantation into silicon

1999-01-28

arxiv.org/abs/physics/9901056v1

Physical Review B, 54 (1996) pp. 17147-17157

Physics

Computational Physics

12 pages, 11 figures. See http://bifrost.lanl.gov/~reed/

Scientific paper

10.1103/PhysRevB.54.17147

It is crucial to have a good phenomenological model of electronic stopping power for modeling the physics of ion implantation into crystalline silicon. In the spirit of the Brandt-Kitagawa effective charge theory, we develop a model for electronic stopping power for an ion, which can be factorized into (i) a globally averaged effective charge taking into account effects of close and distant collisions by target electrons with the ion, and (ii) a local charge density dependent electronic stopping power for a proton. This phenomenological model is implemented into both molecular dynamics and Monte Carlo simulations. There is only one free parameter in the model, namely, the one electron radius rs0 for unbound electrons. By fine tuning this parameter, it is shown that the model can work successfully for both boron and arsenic implants. We report that the results of the dopant profile simulation for both species are in excellent agreement with the experimental profiles measured by secondary-ion mass spectrometry(SIMS) over a wide range of energies and with different incident directions. We point out that the model has wide applicability, for it captures the correct physics of electronic stopping in ion implantation. This model also provides a good physically-based damping mechanism for molecular dynamics simulations in the electronic stopping power regime, as evidenced by the striking agreement of dopant profiles calculated in our molecular dynamics simulations with the SIMS data.

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