Doped vs undoped silicon nanowire

fdtd
silicon
doping

#1

I am trying to model the optical properties of vertical silicon nanowires. I have created a model in Lumerical FDTD which does not behave the way my lab experiments do… The geometry is very simple, so I am confident that the simulation design is correct, but the results just don’t agree with experimental data.

I’m wondering if the material properties are the cause of the difference. In my lab we use doped silicon, but the Palik Si file is, I believe, undoped Si. Could this possibly be the cause of the difference? I think the only place this could manifest would be in the imaginary part of the refractive index.

Does anyone have any experience modeling doped silicon nanostructures in Lumerical FDTD?

Thanks.


nanoparticles doped with fluoride material
Doping Silicon using Drude model and NP Density grid attribute?
#2

The change in index due to doping is pretty small in magnitude (<1e-4). For a small structure like a nanowire, this small variation should not affect the simulation results since this is probably smaller than the error we can expect in the experimental index data. If you are seeing different simulation results than experimental data then I would recommend to check the simulation settings such as boundary condition, fitting of the index data, mesh settings etc. first.

If you still believe that doping could be making the difference here, then you can easily account for that by using the “index perturbation” material to perturb the index of the default silicon material according to a doping density.


#3

Thank you aalam. I think you are right about the index change due to doping. It is very small, and therefore it is not expected to alter the results significantly. I will check the simulations settings. Fitting of the index data is not something I have considered. I’ll have to read into that more.

Thanks.


#4

Try this: Modifying the material fits


#5

Should be a similar issue with this, right? The doping should only result in small changes in the n and k values of silicon and thus should not change the fit much.


#6

The fit is basically the value that FDTD Solutions will use in the simulation. Therefore we want these values to be as close as the experimental index value as possible. Once the fit is done and we have the fitted index, the perturbation due to doping is added to it (if any).