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PyXtal

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Introduction

PyXtal is an open source Python package which was initiated by Qiang Zhu and Scott Fredericks. The goal of PyXtal is to develop a fundamental library to allow one to design the material structure with a certain symmetry constraint. These structures can exported to various structural formats for further study. See the documentation for more information.

To contribute to this project, please check How to contribute?.

Quick Start

Current Features

  • Generation of atomic structures for a given symmetry and stoichiometry (0-3D)
  • Generation of molecular crystals (1-3D) with the support of special Wyckoff positions.
  • Structure manipulation via subgroup/supergroup symmetry relation
  • Geometry optimization from built-in and external optimization methods.
  • Internal support of cif file and many other formats via pymatgen or ASE.
  • Easy access to symmetry information (e.g., Wyckoff, site symmetry and international symbols).
  • X-ray diffraction analysis and its online application

Installation

To install the code, one just needs to do

pip install pyxtal

or

pip install --upgrade git+https://github.com/MaterSim/PyXtal.git@master

If you want to add the Julia package install (required by the use of pyxtal.lego module), please use

export INSTALL_JULIA=1 && pip install pyxtal

To check if the installation is successful, run the following script,

from juliacall import Main as jl
jl.seval("using CrystalNets")
print("Success")

Citation

General PyXtal

Fredericks S, Parrish K, Sayre D, Zhu Q*(2020) PyXtal: a Python Library for Crystal Structure Generation and Symmetry Analysis. [arXiv link]

@article{pyxtal,
title = "PyXtal: A Python library for crystal structure generation and symmetry analysis",
journal = "Computer Physics Communications",
volume = "261",
pages = "107810",
year = "2021",
issn = "0010-4655",
doi = "https://doi.org/10.1016/j.cpc.2020.107810",
url = "http://www.sciencedirect.com/science/article/pii/S0010465520304057",
author = "Scott Fredericks and Kevin Parrish and Dean Sayre and Qiang Zhu",
}

Site Symmetry Representation

Levy D, Panigrahi S-S, Kaba S-O, Zhu Q, Galkin M, Miret S, Ravanbakhsh S. (2024) SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models AI for Accelerated Materials Design NeurIPS 2024,

@inproceedings{
levy2024symmcd,
title={Symm{CD}: Symmetry-Preserving Crystal Generation with Diffusion Models},
author={Daniel Levy and Siba Smarak Panigrahi and S{\'e}kou-Oumar Kaba and Qiang Zhu and Mikhail Galkin and Santiago Miret and Siamak Ravanbakhsh},
booktitle={AI for Accelerated Materials Design - NeurIPS 2024},
year={2024},
url={https://openreview.net/forum?id=V7x2KZQn2v}
}

Symmetry relation

Zhu Q, Kang B, Parrish K (2022). Symmetry Relation Database and Its Application to Ferroelectric Materials Discovery

@article{zhu2022symmetry,
  title="Symmetry relation database and its application to ferroelectric materials discovery",
  author="Zhu, Qiang and Kang, Byungkyun and Parrish, Kevin",
  journal="MRS Communications",
  volume="12",
  number="5",
  pages="686--691",
  year="2022",
  doi="https://doi.org/10.1557/s43579-022-00268-4",

Organic crystal packing motif

Zhu Q, Tang W-L, Hattori S. (2022). Quantification of Crystal Packing Similarity from Spherical Harmonic Transform

@article{zhu2022quantification,
  title="Quantification of Crystal Packing Similarity from Spherical Harmonic Transform",
  author="Zhu, Qiang and Tang, Weilun and Hattori, Shinnosuke",
  journal="Crystal Growth \& Design",
  volume="22",
  number="12",
  pages="7308--7316",
  year="2022",
  doi="https://doi.org/10.1021/acs.cgd.2c00933",
}

How to contribute?

This is an open-source project. Its growth depends on the community. To contribute to PyXtal, you don't necessarily have to write the code. Any contributions from the following list will be helpful.

  • Star on GitHub the PyXtal project and recommend it to your colleagues/friends
  • Open an GitHub issues to report the bug or address your wishlist or improve our documentation
  • GitHub forks the repository and send us the pull request