Supporting data for "Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics"
Authors/Creators
- 1. Center for Molecular Modeling, Ghent University, Technologiepark 46, 9052 Zwijnaarde (Belgium)
Description
Supporting data for "Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics" by M. Bocus, R. Goeminne, A. Lamaire, M. Cools-Ceuppens, T. Verstraelen and V. Van Speybroeck, Nature Communications, 2023, 14, 1008.
This dataset contains examples of input files, submission and analysis scripts to train and use a machine learning potential based on the Schnet architecture for the proton hopping reaction in the H-CHA zeolite. The complete DFT training set, obtained by unbiasing the forces printed by CP2K (with PLUMED coupling), is stored as extended xyz files in the folders DFT/A-B/training_data.xyz where A=1-3 and A<B<5. More details on the folder architecture can be found in the README.md file.
Files
SI_data.zip
Files
(4.8 GB)
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