Fast, Physical, Predictive and Calibrated Modeling of Ion Implantation
In a Research & Development environment, Technology Computer Aided Design (TCAD) is involved in the device optimization loop and requires efficient and predictive implantation modeling with frequent updating of the range of validity. For this purpose, semi-empirical models using statistical distributions are mainly chosen, because this kind of simulation is faster than the physically based Monte-Carlo (MC) approach. We propose a methodology which can be applied to ion implantation modeling with easy build-up, and which gives a predictive capability in the explored experimental domain.