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Low-energy contributions to positron implantation

A detailed knowledge of low-energy positron implantation is of considerable importance for depth profiling and data analysis in slow positron experiments. Existing Monte Carlo models are capable of simulating the behavior of positrons incident at keV energies, then following the energy-loss process...

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Bibliographic Details
Published in:Journal of applied physics 1993-09, Vol.74 (5), p.3479-3496
Main Authors: RITLEY, K. A, LYNN, K. G, GHOSH, V. J, WELCH, D. O, MCKEOWN, M
Format: Article
Language:English
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Summary:A detailed knowledge of low-energy positron implantation is of considerable importance for depth profiling and data analysis in slow positron experiments. Existing Monte Carlo models are capable of simulating the behavior of positrons incident at keV energies, then following the energy-loss process to final kinetic energies of from 20 to 100 eV. A Monte Carlo calculation of the final stages of positron thermalization in Al, Cu, and Au, from 25 eV to thermal energies, is described via the mechanisms of conduction-electron and longitudinal acoustic-phonon scattering. This calculation produces a wide variety of data, including implantation profiles, fraction and energy distribution of reemitted positrons, and the mean thermalization time. A way to obtain information about positron energy loss by considering the time evolution of a point concentration (delta-function distribution) of positrons is described. Diffusion coefficients are obtained that are in good agreement with experiment. The effects of a positive positron work function are examined in the context of a positron Monte Carlo calculation. It is shown that the latter stages of thermalization can have important effects on the stopping profiles and mean depth. In particular, calculated stopping profiles and mean implantation depth are not adequately described by the Makhovian distribution, in agreement with recent experimental findings. A parameterization of these profiles is provided which will be of use in the analysis of experimental data.
ISSN:0021-8979
1089-7550
DOI:10.1063/1.355282