Modeling of extrinsic extended defect evolution in ion-implanted silicon upon thermal annealing

A physically motivated model that accounts for the spatial and temporal evolution of extended defect distribution in ion-implanted Si is presented. Free physical parameters are extracted from experimental data and by means of a genetic algorithm (GA). Transmission electron microscopy (TEM) data and self-interstitial oversaturation measurements are combined in the same fitting procedure to eliminate unphysical solutions and find the optimum set of parameters. The calibration of parameters shows that binding energies of small self-interstitial clusters exhibit strong minima, as reported in other investigations. It is demonstrated that the calibrated model we propose is able to predict a wide variety of physical phenomena, from the oversaturation of self-interstitials via the mean-size distribution of {1 1 3} defects to the depth distribution of the density of the latter.