CGWGAN | Paper
Content
- Site Template: open.db.gz
- M3GNet-Calculated Phonon: merge.db
- VASP Relaxation Structure Comparison with PyXtal: random_vs.db
Crystal Generative Framework Based on Wyckoff Generative Adversarial Network
In this study, we present the Crystal Generative Framework based on the Wyckoff Generative Adversarial Network (CGWGAN).
All templates with 3-4 asymmetric units generated in our work are available as open-source resources in the CGWGAN datasets.
Python Implementation
from ase.db import connect
database = connect('open.db')
entry_id = 1 # The crystal index
atoms = database.get_atoms(id=entry_id)
# Chemical symbols
symbols = atoms.get_chemical_symbols()
# Volume
latt_vol = atoms.get_volume()
# Fractional positions
positions = atoms.get_scaled_positions()
# etc...
Operating and Displaying the DB File
# Install CryDBkit
pip install CryDBkit
from CryDBkit import website
website.show('open.db')
If you utilize the data or code from this repository, please reference our paper.
@article{su2024cgwgan,
title={CGWGAN: crystal generative framework based on Wyckoff generative adversarial network},
author={Su, Tianhao and Cao, Bin and Hu, Shunbo and Li, Musen and Zhang, Tong-Yi},
journal={Journal of Materials Informatics},
volume={4},
number={4},
pages={N--A},
year={2024},
publisher={OAE Publishing Inc.}
}