CSSlib is an open-source code for building configuration search space (CSS) of disordered crystals, loading of the CSS dataset obtained, local/remote MPI or SLURM calculations and data visualization.
Project description
Welcome to CSSlib 👋
CSSlib is an open-source code for building configuration search space (CSS) of disordered crystals, loading of the CSS dataset obtained, local/remote MPI or SLURM calculations and data visualization.
Table of content
Installation
CSSlib can be installed through
- the pip package manager (in the virtual environment):
pip install csslib
- the git clone command:
git clone https://github.com/AIRI-Institute/CSSlib.git CSSlib
cd CSSlib
pip install .
- the uv package manager:
uv venv .venv
source .venv/bin/activate
uv pip install csslib
CSSlib by default requires Supercell program. Details on Supercell installation can be found at the corresponding website.
As a calculator for quantum mechanical calculations, CSSlib assumes the use of the VASP (Vienna Ab initio Simulation Package) software package. Also there is an optional dependency for the QuantumEspresso simulation package which can be installed after the normal installation as:
pip install --group espresso .
or
uv sync --group espresso
Contributors
- Aleksey Krautsou
- Aleksandr Solovykh
Tutorial
The best way to learn how to use CSSlib is through the tutorial notebook located at the tests directory or at the google collab.
References & Citing
If you use this code, please consider citing works that actively used the CSS approach, which resulted in the creation of this library:
- A.V. Krautsou, I.S. Humonen, V.D. Lazarev, R.A. Eremin, S.A. Budennyy
"Impact of crystal structure symmetry in training datasets on GNN-based energy assessments for chemically disordered CsPbI3"
https://doi.org/10.1038/s41598-025-92669-3 - N.A. Matsokin, R.A. Eremin, A.A. Kuznetsova, I.S. Humonen, A.V. Krautsou, V.D. Lazarev, Y.Z. Vassilyeva, A.Y. Pak, S.A. Budennyy, A.G. Kvashnin, A.A. Osiptsov
"Discovery of chemically modified higher tungsten boride by means of hybrid GNN/DFT approach"
https://doi.org/10.1038/s41524-025-01628-z - R.A. Zaripov, R.A. Eremin, I.S. Humonen, A.V. Krautsou, V.V. Kuznetsov, K.E. GermanS, S.A. Budennyy, S.V. Levchenko
"First-principles data-driven approach for assessment of stability of Tc-C systems"
https://doi.org/10.1016/j.actamat.2025.121704
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