1412
Continuum Modelling of Silicon Diffusion and Activation in in0.53Ga0.47As

Monday, 25 May 2015: 15:20
Conference Room 4G (Hilton Chicago)
H. L. Aldridge Jr., A. G. Lind, M. E. Law (University of Florida), C. Hatem (Applied Materials), and K. S. Jones (University of Florida)
There is significant research interest in the behavior of silicon as a dopant in InGaAs during processing conditions for possible integration into future CMOS devices. A major objective is obtaining low resistances for source and drain regions, which require very high doping concentrations near the limits of solid solubility (>1×1020cm-3). Understanding dopant behavior and activation near these limits are of paramount importance in order to fully integrate InGaAs and related III-V materials into systems previously dominated by silicon.  

In this work, a Si diffusion and activation model in In0.53Ga0.47As using the Florida Object Oriented Process and Device Simulator (FLOOXS) will be presented. Similar to previous studies in GaAs, the group-III vacancy-Si pair is implemented as the principle mechanism for silicon diffusion in InGaAs. Fermi level considerations concerning concentration-dependent diffusion are also taken into account in the presented model, building upon simpler previous models.  

Experimental studies that provided the data include Si-implanted InGaAs samples and MBE-grown delta-doped layers of Si in InGaAs. Both sets of samples were capped with Al2O3 and annealed at temperatures ranging from 550 to 750°C. As indicated through SIMS data, post annealed profiles for silicon exhibit very sharp shoulders characteristic of concentration dependent diffusion.  The extracted power of concentration dependence from the SIMS results are relatively high (greater than n=4). This sharp dependence differs from prior continuum-based modelling procedures, where power dependence is believed to closely correspond to the charge state of defects responsible for diffusion. Ultimately the connection between diffusion and activation will be explored, along with developments in prediction and modelling.