MD17 data for graph2mat
Creators
------------
Pol Febrer (pol.febrer@icn2.cat, ORCID 0000-0003-0904-2234)
Peter Bjorn Jorgensen (peterbjorgensen@gmail.com, ORCID 0000-0003-4404-7276)
Arghya Bhowmik (arbh@dtu.dk, ORCID 0000-0003-3198-5116)
Related publication
-------------------
The dataset is published as part of the paper:
"GRAPH2MAT: UNIVERSAL GRAPH TO MATRIX CONVERSION FOR ELECTRON DENSITY PREDICTION"
(https://doi.org/10.26434/chemrxiv-2024-j4g21)
https://github.com/BIG-MAP/graph2mat
Short description
------------------
This dataset contains the Hamiltonian, Overlap, Density and Energy Density matrices
from SIESTA calculations of a subset of the MD17 aspirin dataset. The subset is taken
from the third split in (https://doi.org/10.6084/m9.figshare.12672038.v3).
SIESTA 5.0.0 was used to compute the dataset.
Contents
-----------------
The dataset has two directories:
- pseudos: Contains the pseudopotentials used for the calculation (obtained from
http://www.pseudo-dojo.org/, type NC SR (ONCVPSP v0.5), PBE, standard accuracy)
- splits: The data splits used in the published paper. Each file "splits_X.json"
contains the splits for training size X.
And then, three directories containing the calculations with different basis sets:
- matrix_dataset_defsplit: Uses the default split-valence DZP basis in SIESTA.
- matrix_dataset_optimsplit: Uses a split-valence DZP basis optimized for aspirin.
- matrix_dataset_defnodes: Uses the default nodes DZP basis in SIESTA.
Each of the basis directories has two subdirectories:
- basis: Contains the files specifying the basis used for each atom.
- runs: The results of running the SIESTA simulations. Contents are discussed next.
The "runs" directory contains one directory for each run, named with the index
of the run. Each directory contains:
- RUN.fdf, geom.fdf: The input files used for the SIESTA calculation.
- RUN.out: The log of the SIESTA run, which apar
- siesta.TSDE: Contains the Density and Energy Density matrices.
- siesta.TSHS: Contains the Hamiltonian and Overlap matrices.
Each matrix can be read using the sisl python package (https://github.com/zerothi/sisl)
like:
```python
import sisl
matrix = sisl.get_sile("RUN.fdf").read_X()
```
where X is hamiltonian, overlap, density_matrix or energy_density_matrix.
To reproduce the results presented in the paper, follow the documentation of the graph2mat
package (https://github.com/BIG-MAP/graph2mat).
Cite this data
------------------
https://doi.org/10.11583/DTU.c.7310005
© 2024 Technical University of Denmark
License
-----------------
This dataset is published under the CC BY 4.0 license.
This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator.
