A computing solution combining the GNU Guix functional package manager with the Apptainer container system is presented. This approach provides fully declarative and reproducible software environments suitable for computational materials science. Its versatility and performance enable the construction of complete frameworks integrating workflow managers such as AiiDA, and Ewoks that can be deployed on HPC infrastructures. The efficiency of the solution is illustrated through several examples: (i) AiiDA workflows for automated dataset construction and analysis as well as path-integral molecular dynamics based on ab initio calculations; (ii) workflows for the training of machine-learning interatomic potentials; and (iii) an Ewoks workflow for the automated analysis of coherent X-ray diffraction data in large-scale synchrotron facilities. These examples demonstrate that the proposed environment provides a reliable and reproducible basis for computational and data-driven research in materials science.
@article{arxiv.2512.13826,
title = {Reproducible container solutions for codes and workflows in materials science},
author = {Dylan Bissuel and Léo Orveillon and Benjamin Arrondeau and Paulo Almeida De Mendonça and Irina Piazza and Martin Uhrin and Étienne Polack and Akshay Krishna Ammothum Kandy and David Martin-Calle and Jonathan Chapignac and Aadhityan Arivazhagan and Lorenzo Paulatto and Pierre-Antoine Bouttier and M. -I Richard and Thierry Deutsch and David Rodney and A M Saitta and Nöel Jakse},
journal= {arXiv preprint arXiv:2512.13826},
year = {2025}
}