Supplementary material for "Tackling Structural Complexity in Li2S-P2S5 Solid-State Electrolytes Using Machine Learning Potentials"

Python code for the sampling of amorphous thiphosphate-type solid-state electrolytes with arbitrary stoichiometry. The code has been used in the paper "Tackling Structural Complexity in Li2S-P2S5 Solid-State Electrolytes Using Machine Learning Potentials" (C. Staacke, T. Huss, J. T. Margraf , K. Reuter and C. Scheurer, Nanomaterials 2022, 12(17), 2950; https://doi.org/10.3390/nano12172950) for the sampling of different amorphous cells of the LPS family. Furthermore the Gaussian Approximation Potential (GAP) derived in this work and the corresponding training data are provided.