The modeling of ion implantation is of critical importance for process simulators as the as-implanted profiles form the starting conditions for all subsequent processing steps. Whereas Monte Carlo simulation is the only physical based method for calculating the implanted atoms distribution, its computational demands restrict its use in practical applications. An alternative empirical modeling approach consists of adjusting the parameters of an analytical distribution function to fit measured profiles. Different implant characteristics such as energy, dose, tilt and rotation angles, affect the final distribution of ions. By carefully selecting the parameter values of the fitted implants, the distribution resulting from different implant parameters can be calculated by interpolation over a wide range of conditions.
The single Pearson IV function is one type of distribution functions
normally used for representing the implanted impurity atoms. It has been
shown, that due to channeling, the distributions of Boron and BF
cannot
be adequately modeled by the single Pearson IV function [107][78].
Rather, a dual Pearson approach was proposed [102] whereby the
randomly scattered implanted profile and the channeled component are each
represented by one of the two Pearson profiles respectively. The
determination of the parameters of a dual Pearson IV distribution to
achieve good agreement between experimentally determined and
SUPREM3 [38] simulated profiles is discussed in this section.