Published November 6, 2024
| Version v1
Dataset
Open
Data for "Supervised machine learning methods for crystal structure prediction of the binary Cs-Te system"
Authors/Creators
- 1. Carl von Ossietzky Universität Oldenburg, Institute of Physics, D-26129 Oldenburg, Germany
Description
Crystal structures, high-throughput calculations and trained machine learning models presented in the paper "Supervised machine learning methods for crystal structure prediction of the binary Cs-Te system".
- crystal_datasets contains the input/output data sets of crystal structures for high-throughput calculations and ML models.
- aiida_ht_calculations contains the data regarding the high-throughput DFT calculations.
- ml_models contains the trained ML models.
Eeach zip-archive contains a jupyter-notebook examplifying how the data can be accessed and reused.