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"
Description
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 (https://wiki.fysik.dtu.dk/ase/tutorials/tut06_database/database.html) for more information. The demo-database-access.py 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 (https://gpumd.org) . The calorine package (https://calorine.materialsmodeling.org) 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.py script illustrates how to access the structures and models.