Research data supporting "Data-driven learning and prediction of inorganic crystal structures"

Name: Research data supporting "Data-driven learning and prediction of inorganic crystal structures"
Published: 2018-08-03T07:31:07Z
License: https://creativecommons.org/licenses/by/4.0/
Keywords: machine learning, materials modelling, random structure searching, phosphorus

Deringer, VL; Proserpio, Davide M; Csanyi, Gabor; Pickard, Chris J

Research data supporting "Data-driven learning and prediction of inorganic crystal structures"

Authors

Deringer, VL

Proserpio, Davide M

Csanyi, Gabor

https://orcid.org/0000-0002-8180-2034

Pickard, Chris J

DOI

https://doi.org/10.17863/CAM.25572

Files

data_GAP-RSS_P.tar.gz (66.71 MB)

Type

Dataset

Description

This dataset contains potential parameter files (*.xml) for the different generations of GAP-RSS interatomic potential models described in the article, as well as structural information and DFT-computed reference and testing databases.

Publication Date

2018-08-03T07:31:07Z

Format

Crystal structure data can be read, visualised, and processed with a range of tools - including, but not restricted to, the free ASE and QUIP/quippy environments. GAP parameter files can be read by, and used with, ASE, QUIP/quippy, and LAMMPS. Additional information on their use can be found at www.libatoms.org.