Renard C., Scheiblin P., de Crécy F., Ferron A., Guichard E., Holliger P., Laviron C.
CEA-LETI, FR
Keywords: analysis of variance, arsenic activation, calibration, DoE, genetic algorithm, modelling, optimization
The accurate prediction of arsenic activation after spike annealing is mandatory for Ultra Shallow Junction (USJ) sheet resistance optimization for advanced NMOS transistors engineering. For the first time, we propose a fast and efficient methodology which consists in both predicting coefficients which model the arsenic activation, and in calibrating a physically-based mobility model from experimental data. Calibration was obtained by a genetic algorithm optimization of a criterion taking into account the difference between simulation and measurement, and both experimental and modelling uncertainties.
Journal: TechConnect Briefs
Volume: 2, Technical Proceedings of the 2004 NSTI Nanotechnology Conference and Trade Show, Volume 2
Published: March 7, 2004
Pages: 21 - 24
Industry sector: Advanced Materials & Manufacturing
Topics: MEMS & NEMS Devices, Modeling & Applications, Nanoelectronics
ISBN: 0-9728422-8-4