A reference set of configurations of hydrogenated liquid and amorphous silicon from the datasets for Si-H-GAP. These configurations were used to evaluate training on a GAP model.
We present a Python package for the efficient generation of special quasi-random structures (SQS) for atomic-scale calculations of disordered systems. Both, a Monte-Carlo approach or a systematic enum
