Research data for "Crystal structure identification with 3D convolutional neural networks with application to high-pressure phase transitions in SiO2"

This dataset supports the paper "Crystal structure identification with 3D convolutional neural networks with application to high-pressure phase transitions in SiO2".

The following files are provided: -The training database for the simple (artificial and MD) and the SiO2 structures --> The training data is provided in two different formats. In the "simple_training_dump" and "SiO2_training_dump" files, the dump files from the MD trajectories are provided. In the "simple_training_extracted" and "SiO2_training_extracted" files 1,000,000 extracted atomic environments in a numpy format are stored. -The holdout dataset for the simple structures -The snapshots of the SiO2 shock simulation

Identifier
Source https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4188
Metadata Access https://tudatalib.ulb.tu-darmstadt.de/oai/openairedata?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:tudatalib.ulb.tu-darmstadt.de:tudatalib/4188
Provenance
Creator Erhard, Linus C.; Utt, Daniel; Klomp, Arne J.; Albe, Karsten
Publisher TU Darmstadt
Contributor TU Darmstadt
Publication Year 2024
Rights Creative Commons Attribution 4.0; info:eu-repo/semantics/openAccess
OpenAccess true
Contact https://tudatalib.ulb.tu-darmstadt.de/page/contact
Representation
Language English
Resource Type Dataset
Format application/zip
Discipline Other