A physically based model for the spatial and temporal evolution of self-interstitial agglomerates in ion-implanted silicon

A physically motivated model that accounts for the spatial and temporal evolution of self-interstitial agglomerates in ion-implanted Si is presented. For the calibration of the model, a genetic algorithm is used to find the optimum set of physical parameters from experimental data. Mean-size evolution of {113} defects obtained by transmission electron microscopy and self-interstitial oversaturation results measured in the vicinity of extended defects are combined in the same fitting procedure. The calibration of parameters shows that binding energies of small self-interstitial clusters exhibit strong maxima, as reported in other investigations. Results of the calibrated model are compared to experimental data obtained in complementary investigations. It is demonstrated that the model is able to predict a wide variety of physical phenomena, from the oversaturation of self-interstitials via the mean-size evolution of {113} defects to the depth distribution of the density of the latter.