Data and code for "Phase transitions in inorganic halide perovskites from machine learning potentials: The impact of size, rate, and the underlying exchange-correlation functional"

This record contains databases with data from density functional theory calculations used for training a series of neuroevolution potentials (NEPs), which are also included here. Information is also included for how to access the databases and run the NEP models. Databases The *.db files are databases with the results from density functional theory (DFT) calculations. These are sqlite databases in ase format, see here for more information. The demo-database-access.pyOpens in a new tab script illustrates the most basic access. Models The neuroevolution potential (NEP) models described in the publication can be found in the nep-*.txt files. They can be used in conjunction with the GPUMD package. The calorine package provides a Python interface to GPUMD. Primitive structures Several primitive structures in extended xyz format can be found in the *.xyz files. These structures have been relaxed using the NEP models included here. The demo-for-using-structures-and-models.pyOpens in a new tab script illustrates how to access the structures and models.