Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
Add to list
  1. Search results
  2. DFT-quality adsorption simulations in...

DFT-quality adsorption simulations in MOFs enabled by machine learning potentials

Ruben Goeminne (UGent) , Louis Vanduyfhuys (UGent) , Veronique Van Speybroeck (UGent) and Toon Verstraelen (UGent)
(2023)
Author
Organization
Project
Abstract
Scripts and data for reproducibility of the results. The data_total_unconstrained.zip dataset is an update of the optimization trajectories in data.zip, in which total unconstrained energies and forces are reported.
Keywords
Adsorption in metal-organic frameworks, machine learning potentials, Mg-MOF-74
License
CC-BY-4.0
Access
open access

Citation

Please use this url to cite or link to this publication: 

@misc{01KSWJ8G7RV5XT9H15XW43561N,
  abstract     = {{Scripts and data for reproducibility of the results.

The data_total_unconstrained.zip dataset is an update of the optimization trajectories in data.zip, in which total unconstrained energies and forces are reported.}},
  author       = {{Goeminne, Ruben and Vanduyfhuys, Louis and Van Speybroeck, Veronique and Verstraelen, Toon}},
  keywords     = {{Adsorption in metal-organic frameworks,machine learning potentials,Mg-MOF-74}},
  language     = {{eng}},
  publisher    = {{Zenodo}},
  title        = {{DFT-quality adsorption simulations in MOFs enabled by machine learning potentials}},
  url          = {{http://doi.org/10.5281/ZENODO.7782867}},
  year         = {{2023}},
}
Altmetric
View in Altmetric