@Volker: Q =380 is great news!!! Can you provide us more details about the simulation settings ?
As discussed just above, the meshing is very critical here, because the current crowds on the extreme edges. You are looking at 0.01 Ohm effects and that correspond to 0.001 dB change in reflection. That is somewhat extreme and needs special settings.
Here are the Sonnet settings that I used: geometry sampling resolution (cell size) 0.1mm with thick metal model, conformal meshing, conformal subsection length = 1mm.
In the example above, I had used 0.5mm geometry sampling resolution, which is too coarse. That did not model the high edge current with enough detail, so that the effective conductor cross section and Q factor where over estimated. I can not go to much smaller subsections, because that will be slow. This is not an issue for normal RF circuits and it is not an issue for RFIC inductors.
We started the thread with your Axiem results, and why these are inconsistent. Let's come back to that:
From my first result above, where I analyzed in Sonnet with thin metal with 1 and 2 skin sheets and compared that to thick metal, you can see that thick metal is not much different from thin metal with 2 skin sheets. My interpretation of your difference between thin metal and thick metal in Axiem is that Axiem does thin metal with one skin sheet, which is reasonable for microstrip cases. The usual reason to use thick metal, the field difference between zero thickness and finite thickness, is not the issue it. It is just the number of skin sheets used to calculate the effective surface impedance of the thin sheet.
I think that your settings in Axiem should be: thick metal analysis, but to go to much finer mesh. Why don't you try that?
Still 9% difference from reality.
This statement does not make much sense, as long as we do not know the % error in your measurement.
If the purpose of this thread is to help you choosing the proper simulation settings for your simulator, I am happy to help. However, benchmarking EM solvers for accuracy needs an reference results that is exactly known, or where we know at least the error bars for the measured data.