Sources:
(1) "Multiscale machine-learning interatomic potentials for ferromagnetic and liquid iron" | https://doi.org/10.1088/1361-648X/ac6f39
(2) "Fast and accurate machine-learned interatomic potentials for large-scale simulations of Cu, Al and Ni" | http://dx.doi.org/10.1103/PhysRevMaterials.9.053807
(3) "Radiation damage and phase stability of Al_xCrCuFeNi_y alloys using a machine-learned interatomic potential" | https://doi.org/10.1103/tk38-t5rr

- db_Fe.xyz: (1)
- db_Al.xyz, db_Cu.xyz, db_Ni.xyz: (2)

- feni-train.xyz + feni-test.xyz:
    "The development and applications of a tabGAP potential for FeNi alloys." - Jegors Balzins' Bachelor's Thesis,
    which in addition to original data partially includes data from:
        (1), (2) and (3)

- iter-3-3-train.xyz + iter-3-3-test.xyz: Data for currently unpublished/not-finished CrMnFeNi potential,
                                          partially including data from the above-mentioned sources.