%0 Generic %A Jansen, Thies %A Bokdam, Menno %D 2023 %T LaMnO3, SrRuO3 database for force field training underlying the publication: Phase transitions of LaMnO3 and SrRuO3 from DFT+U based machine learning force fields simulations %U %R 10.4121/428049a0-cb40-43d4-bf58-4276ede13402.v3 %K density functional theory %K DFT %K machine learning force fields %K LaMnO3 %K SrRuO3 %K Hubbard U %K phase transition %K magnetism %X

This data set contains the collection of ab initio data (ML_ABN) from calculations done on LaMnO3 and SrRuO3. From the paper: Jansen T., Brocks G., Bokdam M. Phys. Rev. B 2023

These structures have been selected with the on-the-fly Machine-Learning Force Fields method as implemented in VASP 6.3:

Jinnouchi R., Lahnsteiner J., Karsai F., Kresse G., Bokdam M., "Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on the fly with Bayesian inference", Phys. Rev. Lett. 122, 225701, (2019)

The data set is .zip file including the ML_ABN, INCAR, POSCAR, KPOINTS and ML_REG files for the following configurations:

- LaMnO3 in the AFM configuration for U = 0,1,2 and 3.5 eV,

- LaMnO3 with U = 3.5 eV for an intial FM and non-spin polzarized configuration.

- SrRuO3 in FM configuration with U,J = 2, 0.6 eV and U = J = 0 eV

FPdataviewer factsheets

A high level overview of the ML_AB databases has been generated using the open-source FPdataViewer software. Each pdf file contains statistics related to the structures, energies and forces stored in the databases. The factsheet can be used to get a quick overview of the data stored in the database.

%I 4TU.ResearchData