(566d) Computational Insights into the (Complex) Aggregation Physics of Self-Interstitials

The evolution of self-interstitials and their aggregates during the annealing of ion-implanted silicon has received a tremendous amount of attention because of their strong, non-linear effects on the diffusion of dopants. Ion-implantation is the most common way of introducing dopants into a silicon substrate, as required for microelectronic device fabrication. However, the implantation process leads to extensive lattice damage, and at high enough energies, complete amorphization, which must be recrystallized by thermal annealing following the implantation process. Also generated by the implantation process is a large number of self-interstitials which lead to enhanced dopant diffusion during the annealing process. As the self-interstitial population relaxes towards equilibrium during annealing, the diffusion enhancement varies strongly, a phenomenon that has been described as Transient Enhanced Diffusion, or TED.

A major obstacle to understanding and quantitatively predicting TED is the formation of a variety of self-interstitial aggregates, which range from small amorphous three-dimensional clusters, to planar stacking-faults with various crystallographic orientations. Experimental and theoretical studies have demonstrated that slightly different annealing conditions lead to substantially different TED behavior, which can be linked to differences in the aggregation and dissolution dynamics. While a global picture of TED is now available and the various cluster structures identified, there are still several outstanding issues related to the atomistic mechanisms of self-interstitial clustering that are not understood. In order to develop a fully predictive TED model, a quantitative, temperature dependent understanding of these processes is required.

A major obstacle to understanding and quantitatively predicting self-interstitial aggregation dynamics is their complex morphological transition from small three-dimensional clusters to planar stacking-faults/dislocation loops with various crystallographic orientations. In the present study, we use large-scale constant-stress MD simulations to dynamically simulate the evolution of an ensemble of highly supersaturated self-interstitials at various temperatures and pressures. We show that the simulated interstitial clustering into various types of planar structures exhibits a complex thermodynamic-kinetic phase diagram that is consistent with numerous experimental observations. In particular, we focus on the role of certain “magic” cluster sizes (e.g. four-interstitial and eight-interstitial clusters), which is shown to be extremely rich, exhibiting both temperature and stress dependencies, and leads to a bifurcation in the aggregation pathway of larger cluster sizes. These dependencies are studied with a recently developed approach that maps out the potential energy landscape in the vicinity of the defect cluster and allows for the total (classical) free energy to be analyzed.