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CONTACT NAME=emitter SURF.REC VSURFP=1.5e5 WORKFUN=4.27

The poly-emitter work function can be calculated by measuring the position of the Fermi-Energy at the poly-silicon/silicon interface relative to the conduction band and adding this value to 4.17V. For example, if the Fermi-Energy is measured as being 0.1eV from the conduction band edge, the work function of the poly-emitter set in the CONTACT statement should be set to 4.17 + 0.1 = 4.27V.

Figure 7.44: Effect of emitter contact work function on bipolar gain

Bandgap Narrowing Effects

If the BIPOLAR parameter is stipulated in the MODELS statement in ATLAS, bandgap narrowing is included automatically. The inclusion of bandgap narrowing in the MODELS statement is strongly advised since this phenomenon has a significant effect on the current gain of the device. But, to validate the default Klaassen bandgap narrowing model, you should also use the Klaassen mobility model. Use the additional keyword KLA in the MODELS statement to activate this model. For example:

MODELS BIPOLAR KLA

The parameters in the Klaassen bandgap narrowing model are user-definable in the MATERIAL statement and described in the “Physics” Chapter of the ATLAS USER’S MANUAL, VOL. I. There are three user-definable parameters for the Klaassen band gap narrowing model. The BGN.E parameter has a linear dependency on doping concentration and has the default value of 6.92e-3 volts. BGN.C has a square root dependency with doping concentration and has the default value of 0.5. BGN.N is the value of doping where band gap narrowing effectively starts to take effect and has a default value of 1.3e17/ cm3. The equivalent default setting consequently should be written as:

MATERIAL BGN.E=6.92e-3 BGN.C=0.5 BGN.N=1.3e17

You can alter these parameters to modify the current gain of the device in the medium injection regime. For example, reducing the linear parameter from 6.92e-3 to 6.5e-3 is sufficient to cause a significant increase in current gain in the medium injection region. Although the bandgap narrowing parameters affect both collector and base currents, the base current is affected to a greater degree. The most sensitive plot to see the effect of small changes to bandgap narrowing is a plot of current gain versus log of collector current. A reduction in bandgap narrowing will result in an increase in current gain in the medium current injection region.

7.9.5: The Base Current Profile – Low Injection

This is one case where there is an interdependency on one parameter, since the intrinsic base resistance not only affects the collector current in all regions (see the previous section) Figure 7.43, however, also has an effect on the base current in the low injection region.

For a small range of implant doses around the optimum, the base doping concentration will also affect the position of the knee or the rate or both of fall off of the base current in the low injection operating region of the device. This is most noticeable as a loss of current gain in the low injection region for the alternative standard plot of current gain versus collector current. An increase in the base implant reduces the intrinsic resistance and typically increases the base current in the low injection region, resulting in a decrease in current gain for very low currents.

A similar effect to increasing the base doping is observed if the base doping is kept constant but the overall doping is reduced in the mono-crystalline silicon region of the emitter. You can tune the doping profile in the mono-crystalline region of the emitter using three parameters in ATHENA. The main physical effect of these ATHENA parameters is to change the doping profile of the emitter in the mono- crystalline silicon. These process parameters are as follows:

• The total interstitial concentration in the poly-emitter.

• The dopant segregation effects in the poly-emitter.

• The dopant velocity across the silicon/polysilicon boundary.

The first process parameter will affect how quickly the dopant in an implanted poly-emitter reaches the silicon/polysilicon boundary during the RTA diffusion and therefore affects the total diffusion of dopant into the single crystalline part of the emitter and the base width doping profile.

The second process parameter affects dopant pile-up at the poly-silicon/silicon boundary and therefore the source doping concentration at the mono-crystalline interface. Once again, this will affect the overall doping profile of the emitter in the mono-crystalline region of the device.

The third process parameter affects the velocity of transport of dopant across the polysilicon/silicon boundary with similar effects to the parameters above.

You can use these parameters to tailor the emitter doping profile in the mono-crystalline silicon region to match available measured data, usually in the form of SIMS or capacitance information. An accurate profile of dopant in the poly-silicon part of the emitter is not too important if measured data concerning interfacial dopant concentrations is available. This is because the work function of the poly-emitter will be set in ATLAS by defining the poly-emitter as an electrode. All you need to calculate the correct work function at the poly-silicon emitter is the interfacial doping concentration at the poly- silicon/silicon interface on the poly side of the junction. See the “Poly-emitter work function” Section on page 2-51 for setting the correct work function for the poly-emitter .

Conclusions

By using a logical combination of tuning parameters available in both the process simulator (ATHENA) and the device simulator (ATLAS) and with the influence of each parameter, you can get a good match for bipolar transistors for most device designs.

Since it is usually less problematic to match the collector current for all levels of applied base-emitter voltage compared to the matching of base current, you will probably find that more time is spent trying to match the base current for very small and very large values of applied base-emitter voltage. You should, however, spend a good amount of time on making sure that the correct process models are used in the process flow to reduce the overall uncertainty as to which parameters require calibration.

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Source:  OpenStax, Solid state physics and devices-the harbinger of third wave of civilization. OpenStax CNX. Sep 15, 2014 Download for free at http://legacy.cnx.org/content/col11170/1.89
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