Papers by Keyword: Arsenic Clustering

Abstract: In this contribution we illustrate some important features of the development of models for the simulation of advanced annealing processes. Taking arsenic as example we discuss the challenges that the last technology trends represent for process modeling. Issues like shallow implants, high doses, low total thermal budgets, and steep temperature profiles are discussed, highlighting the physical phenomena to take into account, and how to design models that reproduce them. We also discuss with examples how important are the critical evaluation of known parameters and established approaches, and the extraction of parameters from experiments. Finally we show some applications of our model for spike and flash annealing of arsenic implants.

Abstract: We have developed a diffusion and activation model for implanted arsenic in silicon. The model includes the dynamic formation of arsenic-vacancy complexes (As4V) as well as the precipitation of a SiAs phase. The latter is mandatory to correctly describe concentrations above solid solubility while the former are needed to describe the reduced electrical activity as well as the generation of self-interstitials during deactivation. In addition, the activation state after solid-phase epitaxy and the segregation at the interface to SiO2 are taken into account. After implementation using the Alagator language in the latest version of the Sentaurus Process Simulator of Synopsys, the parameters of the model were optimized using reported series of diffusion coefficients for temperatures between 700 °C and 1200 °C, and using several SIMS profiles covering annealing processes from spike to very long times with temperatures between 700 °C and 1050 °C and a wide distribution of implantation energies and doses. The model was validated using data from flash-assisted RTP and spike annealing of ultra-low energy arsenic implants.