| |
 | Nanotech 2004 Vol. 2
Technical Proceedings of the 2004 NSTI Nanotechnology Conference and Trade Show, Volume 2
Chapter 2: Nano Scale Device Modeling |
| | Methodology for Prediction of Ultra Shallow Junction Resistivities Considering Uncertainties with a Genetic Algorithm Optimization | | Authors: | C. Renard, P. Scheiblin, F. de Crécy, A. Ferron, E. Guichard, P. Holliger and C. Laviron | | Affilation: | CEA-LETI, FR | | Pages: | 21 - 24 | | Keywords: | arsenic activation,modelling, calibration, DoE, optimization, genetic algorithm, analysis of variance | | Abstract: | 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. | | ISBN: | 0-9728422-8-4 |
| Pages: | 519 |
| Hardcopy: | $150.00 |
|
| Order: | Mail/Fax Form |
| Special: | 3 CD Set — 15% off with Free Shipping |
| Up | |
|
| nanoPRwire™ |
 |
| News Headlines |
 |
|
|
| |
| |
|
| | |
| |
|
|
