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Modeling of the diffusion and activation of arsenic in silicon including clustering and precipitation

Modellierung der Diffusion und Aktivierung von Arsen in Silicium unter Berücksichtigung der Bildung von Clustern und Präzipitaten
: Martinez-Limia, A.; Pichler, P.; Steen, C.; Paul, S.; Lerch, W.


Cavallini, A.:
Gettering and Defect Engineering in Semiconductor Technology XII, GADEST 2007 : Selected, peer reviewed papers from Gettering and Defect Engineering in Semiconductor Technology - GADEST 2007" held from 14th to 19th October 2007 in Italy at the EMFCSC
Clausthal-Zellerfeld: Trans Tech Publications, 2008 (Diffusion and defect data. B, Solid state phenomena 131-133)
ISBN: 3-908451-43-4
ISBN: 978-3-908451-43-3
International Autumn Meeting Gettering and Defect Engineering in Semiconductor Technology (GADEST) <12, 2007, Erice>
Conference Paper
Fraunhofer IISB ()
arsenic diffusion; silicon; arsenic deactivation; flash annealing; spike annealing; arsenic clustering; arsenic segregation; arsenic precipitation

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.