This dataset contains a convex hull of Fe nanoparticles up to Fe_{200} found using a new machine learning interatomic potential within the GAP (Gaussian approximation potential) approach (see http://github.com/libatoms/GAP), reported in [1]. The accuracy of the potential is close to the DFT used for the training database, at a much lower computational cost (although higher than classical potentials, of course).
"convex_hull.xyz" contains the structures of the new nano particles in the convex hull found in this work, as well as the energies calculated with several different potentials (PAW-PBE DFT, my GAP, Finnis-Sinclair, Mendelev 2003 EAM [2], Dragoni 2018 GAP [3]), magnetic moments, stress and forces (all from the DFT). The energies from the different potentials for my convex hull are shown in "convex_hull.xyz_energies.png", normalized with the respective bcc bulk energy for each potential. In the legend, the RMSE for each potential is given relative to DFT.
The files "convex_hull--merged_with_CELD.xyz" and "convex_hull--merged_with_CELD.xyz_energies.png" contain the equivalent information, but for the convex hull formed by combining the nano particles found in this search with the ones from the Cambridge Energy Landscape Database [4].

[1] Jana, Richard and Caro, Miguel A. (2023). Searching for iron nanoparticles with a general-purpose Gaussian approximation potential. arXiv:2302.13722.
[2] Mendelev, M. I., Han, S., Srolovitz, D. J., Ackland, G. J., Sun, D. Y., Asta, M. (2003). Development of new interatomic potentials appropriate for crystalline and liquid iron. Philosophical Magazine, 83(35), 3977–3994.
[3] Dragoni, D., Daff, T. D., Csányi, G., Marzari, N. (2018). Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron. PHYSICAL REVIEW MATERIALS, 2, 13808.
[4] D. J. Wales, J. P. K. Doye, A. Dullweber, M. P. Hodges, F. Y. Naumkin, F. Calvo, J. Hernández-Rojas, and T. F. Middleton, “The Cambridge Energy Landscape Database,” http://www-wales.ch.cam.ac.uk/CCD.html