Hints & Tips

Q: How is implant damage enhanced diffusion modeled by ATHENA?
Which tuning parameters should be used for matching experimental results?

A: The effect of implant damage enhanced diffusion is important in many technologies. Typical cases are the source and drain diffusion in MOSFETs and the emitter diffusion in bipolar devices. Damage generated by implantation leads to an enhancement to the diffusion of these dopants during subsequent heat cycles.

Simulation of the enhanced diffusion effects are divided between two processes. Firstly ATHENA must simulate the implant damage generated by a given implant and secondly it must model the effect that these defects have on subsequent impurity diffusion.

ATHENA considers implant damage as point defect generation. Point defects are silicon interstitials and lattice vacancies that are created as energetic implanted ions collide with silicon lattice atoms.

The most practical model for coupling implant damage to subsequent diffusion calculations is the +1 model. In its simplest form, the +1 model adds exactly one interstitial for each implanted ion. This is a reasonable approximation if one assumes that the vacancies and interstitials created by the implant recombine quickly relative to the timescale needed to produce significant diffusion. This leaves one extra interstitial for each ion (assuming the implanted ion has replaced it on the lattice).

This model is applicable to both Monte Carlo and the default analytic implants and can be invoked by including the UNIT.DAM parameter on the IMPLANT statement. A commonly applied variation to this model is to scale the number of generated interstitials. In ATHENA, this can be done using the parameter DAM.FACT on the IMPLANT statement. A corresponding profile of lattice vacancies is introduced in this model with the maximum of zero and (1-DAM.FACT) times the implanted ion profile.

The diffusion models that will include the effect of the point defects are either the TWO.DIM or FULL.CPL models. Both models include the local point defect concentration in the diffusion rate of the dopants. Both interstitials and vacancies diffuse quickly compared with dopant ions. The point defects also recombine as the implant damage is annealed out.

When it comes to tuning to match measured doping profiles, two approaches are possible. Either the damage during implant or the diffusion effect of the point defects could be used. The amount of point defects generated during an implant is extremely difficult to measure. Similarly the model parameters for both diffusion and recombination rates for point defects are uncertain. All are areas of current academic research.

Typically the most effective tuning parameter in this type of simulation is the DAM.FACT value itself. Figure 1 shows how fairly small changes in this parameter affect the doping profile. A value of 0.01 is typical. An ATHENA implant statement for an MOS source/drain might be:

IMPLANT ARSENIC DOSE=3.0E15 ENERGY=60 \

UNIT.DAMAGE DAM.FACT=0.01

Figure 1. Variations in diffusion due to tuning of DAM.FACT parameter.

Figure 2 illustrates how the damage produced by source drain implants affects the center of a MOS transistor with varying gate length. For shorter gate length devices the damage at the source drain area produces additional diffusion in the center that is not seen for longer channel devices. This phenomenon explains some of the reverse short channel effects seen in certain processes.

 

Figure 2. Enhanced diffusion of MOS channel profile.