Research data for "Crystal structure identification with 3D convolutional neural networks with application to high-pressure phase transitions in SiO2"
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Date
2024-03-22
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This dataset supports the paper "Crystal structure identification with 3D convolutional neural networks with
application to high-pressure phase transitions in SiO2".
The following files are provided:
-The training database for the simple (artificial and MD) and the SiO2 structures
--> The training data is provided in two different formats. In the "simple_training_dump" and "SiO2_training_dump" files, the dump files from the MD trajectories are provided. In the "simple_training_extracted" and "SiO2_training_extracted" files 1,000,000 extracted atomic environments in a numpy format are stored.
-The holdout dataset for the simple structures
-The snapshots of the SiO2 shock simulation
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Except where otherwise noted, this license is described as CC BY 4.0 - Attribution 4.0 International