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Model Parameters

  The dynamic clustering model can handle clustering of arsenic and boron. Due to the lack of experimental data for other dopants we give only parameters for these dopants. Arsenic clusters consist of three arsenic atoms ( tex2html_wrap_inline5185 ) and one electron ( tex2html_wrap_inline5187 ) [Gue82]. The parameters for arsenic are based on Tsai's measurements and given in Table 4.3-1. Normally, the cluster phenomenon is jointly occuring with other diffusion phenomena, like transient enhanced diffusion. As arsenic shows insignificant enhanced diffusion tendency, we present arsenic simulation results for the pure clustering mechanism (see Fig. 4.3-3).

   figure1082
Figure 4.3-3: Simulation of arsenic clustering using the dynamic cluster model. The active and total arsenic concentrations are given after 20min annealing at tex2html_wrap_inline4707 .

In the case of boron, it is much more complicate to illustrate the pure clustering behavior. According to boron clustering models in the literature [Pic90], we define boron clusters to consist of six dopant atoms and six electrons ( tex2html_wrap_inline5193 ). During boron diffusion several mechanisms are affecting the final profile. We use a dynamic clustering model to verify the observed transient enhanced diffusivity of boron, see for instance Section 4.3.3. Thereby clustering occurs in the highly doped regions and the clustered dopants are excluded for diffusion enhancement due to point defects. Dynamic clustering parameters for boron applied to the transient enhanced diffusion model are given in (see Table 4.3-1).

Additionally, we give parameters for the static clustering model including
data for silicon interstitial clusters. These data are extracted from boron transient enhanced diffusion experiments [Sol91]. Furthermore, all parameters are modeled by an Arrhenius expression ( tex2html_wrap_inline5195 ) and the clustering rate is scaled to the electron and dopant cluster sizes for comparison reasons
( tex2html_wrap_inline5197 ). Figure 4.3-4 illustrates the static clustering model for arsenic and boron with respect to several temperatures.

   figure1095
Figure 4.3-4: Active versus total dopant concentrations in grain interiors using a static clustering model for arsenic. The temperature dependence of this equilibrium model is also shown. Clustering parameters are taken from [Pic90].

 

Dynamic Clustering Parameters
Dopant tex2html_wrap_inline5143 tex2html_wrap_inline5145 tex2html_wrap_inline5203 tex2html_wrap_inline5205 tex2html_wrap_inline5207 tex2html_wrap_inline5209
As 3 1 tex2html_wrap_inline5215 tex2html_wrap_inline5217 tex2html_wrap_inline5219 tex2html_wrap_inline5221
B 6 6 tex2html_wrap_inline5227 tex2html_wrap_inline5221 tex2html_wrap_inline5231 10.45eV
Static Clustering Parameters
Dopant tex2html_wrap_inline5143 tex2html_wrap_inline5145 tex2html_wrap_inline5239 tex2html_wrap_inline5241
As 3 1 tex2html_wrap_inline5247 tex2html_wrap_inline5249
B 6 6 tex2html_wrap_inline5255 tex2html_wrap_inline5257
Si-I 6 6 tex2html_wrap_inline5263 tex2html_wrap_inline5265
Table 4.3-1: Model parameters for the dynamic and static clustering models. Values are given for arsenic and boron by assuming cluster formation after [Gue82] [Pic90].

 


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Next: 4.3.3 Transient Enhanced Diffusion Up: 4.3.2 Clustering and Precipitation Previous: 4.3.2 Clustering and Precipitation

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