Base de données de configurations atomiques sur le silicium et la silice

This collection constitutes a quantum mechanics database developed for the training of machine learning potentials. It was designed and generated as part of a joint modeling project involving silicon, silica, and oxygen. Thousands of quantum mechanical calculations were carried out using the Quantum ESPRESSO software to build this database. Each file with the .out extension contains essential information such as the simulation box lattice parameters, the number of atoms, the total energy, the atomic forces, and the stress tensor. These data are extracted to train machine learning-based interatomic potentials. The subset of data related to oxygen also includes files in .cfg format, which contain similar information: the simulation box, the number of atoms, energy, forces, and stress. From this database, one can train a machine learning potential or extract atomic coordinates in order to recompute quantum mechanical calculations using exchange-correlation (XC) functionals of choice. In the case of direct training, it is recommended to optimize the database beforehand to select a representative portion based on the specific needs of the model or application Please cite the following paper if using this dataset: 1) Zongo, K., L. K. Béland, and C. Ouellet-Plamondon. "First-principles database for fitting a machine-learning silicon interatomic force field." MRS Advances 7.2 (2022): 39-47 ; 2) Zongo, K., Sun, H., Ouellet-Plamondon, C., & Béland, L. K. (2024). A unified moment tensor potential for silicon, oxygen, and silica. npj Computational Materials, 10(1), 218. 3) Zongo, K. (2025). Modélisation conjointe du silicium, de l’oxygène et de la silice (Doctoral dissertation, École de technologie supérieure)