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

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<br>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)<br>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<br><strong>FPdataviewer factsheets</strong>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.

本数据集收录了基于LaMnO₃与SrRuO₃的从头算（ab initio）数据（ML_ABN），相关计算来自论文Jansen T., Brocks G., Bokdam M. Phys. Rev. B 2023。
这些结构采用VASP 6.3中实现的即时机器学习力场（on-the-fly Machine-Learning Force Fields）方法筛选得到，相关方法源自Jinnouchi R.、Lahnsteiner J.、Karsai F.、Kresse G.、Bokdam M.于2019年发表在《物理评论快报》（Phys. Rev. Lett.）第122卷第225701号的论文"Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on the fly with Bayesian inference"。
本数据集为.zip压缩文件，包含以下构型对应的ML_ABN、INCAR、POSCAR、KPOINTS及ML_REG文件：
- U取值分别为0、1、2与3.5 eV的反铁磁（AFM）构型LaMnO₃；
- 初始为铁磁（FM）且非自旋极化、U=3.5 eV的LaMnO₃；
- U、J取值为2、0.6 eV以及U=J=0 eV的铁磁（FM）构型SrRuO₃。

**FPdataviewer 数据概览手册**
本数据集已通过开源FPdataViewer软件生成ML_AB数据库的高层级概览文件。每份PDF文件均包含数据库中存储的结构、能量与受力相关统计信息，可用于快速了解数据库内的数据概况。