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Data for "Beam induced heating in electron microscopy modeled with machine learning interatomic potentials"

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posted on 2024-02-19, 07:36 authored by Cuauhtémoc Núñez Valencia, William Bang LomholdtWilliam Bang Lomholdt, Matthew Helmi Leth Larsen, Thomas Willum HansenThomas Willum Hansen, Jakob SchiøtzJakob Schiøtz

Data for "Beam induced heating in electron microscopy modeled with machine learning interatomic potentials"

Authors: Cuauhtemoc Nuñez Valencia, William Bang Lomholdt, Matthew Helmi Leth Larsen, Thomas W. Hansen, and Jakob Schiøtz.

Affiliation: Technical University of Denmark

This data is released under the CC BY 4.0 license. You may use the data provided you credit the authors. Please also cite the corresponding scientific article.

The scripts that belong with this data cannot be released here for legal reasons, they can instead be found at github at https://github.com/schiotz/beam_induced_heating

A preprint is available on ArXiv.org, it will be updated to include a link to the actual article when published. See https://doi.org/10.48550/arXiv.2309.16239

All .tgz files are Unix tar archives that have been compressed with gzip. Be aware that the two last files are huge!



produceplots.ipynb

Jupyter Notebook file for producing the figures of the manuscript based on the data in the following files. ONLY AVAILABLE FROM GITHUB (see address above).


potential.tgz (89 MB)

Configuration files (.yaml) and training sets (.traj) for the NequIP potential. The final potential is provided as a PyTorch object (.pth). Python scripts for setting up and running the MD simulations are available on GitHub.


expdata.tgz (1 MB)

Experimental data (EELS).


trajectories_mainpaper.tgz (8.2 GB)

MD trajectories used to generate the figures in the main text.


trajectories_supplementary.tgz (5.4 GB)

MD trajectories used to generate the figures in the supplementary online information.



Funding

Machine-learning assisted atomic-resolution electron microscopy

Danish Agency for Science and Higher Education

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