[HTP-Tools] cif2x ver.1.0 α has been released

cif2x

In recent years, the use of machine learning for predicting material properties and designing substances (known as materials informatics) has gained considerable attention.
The accuracy of machine learning depends heavily on the preparation of appropriate training data.
Therefore, the development of tools and environments for the rapid generation of training data is expected to contribute significantly to the advancement of research in materials informatics.

Cif2x is a tool that generates input files for first-principles calculations from cif files.
It constructs parts that vary depending on the type of material and computational conditions from crystal structure data, using input parameters as a template.
It is capable of generating multiple input files tailored to specific computational conditions.
Currently, it supports VASP <https://www.vasp.at>, Quantum ESPRESSO <https://www.quantum-espresso.org>, and OpenMX <http://www.openmx-square.org>,
with plans to support AkaiKKR <http://kkr.issp.u-tokyo.ac.jp> in the future.

Target applications

Quantum ESPRESSO, VASP, and OpenMX

Requirement

Python3 with pymatgen, qe-tools and other library packages

Install

From source

python3 -m pip install DIRECTORY_OF_THE_REPOSITORY

License

The distribution of the program package and the source codes for cif2x follow
GNU General Public License version 3
(GPL v3).

This software was developed with the support of
"Project for Advancement of Software Usability in Materials Science"
of The Institute for Solid State Physics, The University of Tokyo.

Official page

Authors

Kazuyoshi Yoshimi (ISSP, Univ. of Tokyo),
Tatsumi Aoyama (ISSP, Univ. of Tokyo),
Yuichi Motoyama (ISSP, Univ. of Tokyo),
Masahiro Fukuda (ISSP, Univ. of Tokyo),
Kota Ido (ISSP, Univ. of Tokyo),
Tetsuya Fukushima (AIST),
Shusuke Kasamatsu (Yamagata University),
Takashi Koretsune (Tohoku University),
Taisuke Ozaki (ISSP, Univ. of Tokyo)