Add ABACUS@PW|PseudoDojo-v0.4 results

[Cstandardlib]

Dear ACWF maintainers and the AiiDA community,

This pull request adds the verification results for ABACUS (LTS v3.10) generated with the AiiDA plugin aiida-abacus, developed together with @zhubonan.
Initial checks show our results line up well with the reference data of ABINIT/CASTEP,etc. under the same PseudoDojo-v0.4 pseudopotentials.
If you need any extra info, just let us know and we’ll add them quickly.

Thanks for all your work on this project!

Best regards

[zhubonan]

Hello @giovannipizzi, @eimrek and @t-reents , just want to give you a ping on this.

[giovannipizzi]

Thanks @zhubonan! Very nice!
We are a bit busy preparing for Psi-K but will look into this right after the conference! (I hope that's not too late)

[zhubonan]

Ah of course, no worries😊

[giovannipizzi]

Thanks to both! Since this is the first contribution after the paper, we've been discussing how to manage these. Our recommendation would be to first publish the .aiida file with the calculations, since the work is also about reproducibility, and would allow people to see the input parameters etc. Once this is out we will merge this PR (and, if desired, add it also to the interactive web page on mateirsls cloud).

For the .aiida file: the ideal scenario is to put it on the Materials Cloud Archive, so it has a DOI, is citable and we don't risk it gets lost.
I see three scenarios.

1. (probably preferred) you make an entry for your data, so it's a custom DOI, you are the authors etc, and you can improve your dataset and have a v2, etc. Then you can proceed, and send us the DOI once available.
2. We create a new entry for all future contributed data
3. We create a v2 of the existing Dataset with the contributed data.

I think 1 is the best, 2 and 3 are trickier to manage in the long term if there are many contributions, also in terms of authorship etc. If you agree, please go ahead and once it's out we will double check the generated json and merge this PR (we just need to think if we want to better distinguish contributed data, TBD)

[zhubonan]

Thanks Giovanni. I agree that route 1 makes more sense compared to the others. We will create a Material Could archive submission for the .aiida files first.