Perhaps the simplest explanation is that different teams are all ending up with different variations of a common material, with different impurities, crystal structure, etc.
There's likely a whole zoo of interesting materials here!
There is a good chance that there will be substantial differences between them.
There will likely be years of not decades of looking at differences in the materials and performance of related materials to more fully explore this discovery.
- purity as in the sample is uniformly constructed of the right atoms but they are not in the right configuration
vs
- purity as in the sample contains atoms that shouldn't be there in the first place
and finally
- purity as in: the sample that purportedly did show room temperature superconductivity turns out to be the impure one and that impurity is so poorly understood that we currently can not replicate it accurately, but a test by an independent lab of the sample would verify the properties as advertised.
All of these are possibles, and not mutually exclusive.
The conclusions in the linked pdf suggest this may be the issue with LK99.
As opposed to smelting aluminum or steel? And that creates stuff that is dirt cheap in bulk...
So for now I'm on the measuring error, impurity or process issue side of that without committing to which team I think has the problematic side.
Because the computational requirements are off the scale in the most literal sense. The search space is so large that you won't be able to come up with an improvement in efficiency for your search unless you guide it very carefully with experimentally obtained results and that's exactly what these people were doing as far as I understand it. You mix up a batch of stuff, test it for gross properties, do crystallography and then use the information from that to do some numerical simulations to check if your assumptions and observations hold up.
I don't think we had this compound before.
It's easy (relatively) to verify the results from a real world test since you know the physical parameters and can tweak the others based on intuition, where if the result matches the real world you can consider it valid, but if it doesn't you can have to check all sorts of things to be sure that it isn't a glitch due to some parameter not being reasonable.
That makes searching for materials really hard because you either need an absurd amount of computational power to be able to set the simulation parameters so high as to not worry about their effects or you get tons of false positives simply because the computer can't as easily tune those parameters to ensure it produces correct results.
As my PhD advisor has often put it regarding my own simulation work, if the simulations were that capable of modeling reality, there would be no need for billion dollar facilities to perform tests irl, you'd just spend all that on building many supercomputers.