Datasets for benchmarking and ML modelling
Description
hydrogen-harm data set of crystalline hydrogen configurations: energies at VMC and LRDMS level; purpose: benchmark for MLP; developed in the group of Michele Casula (CNRS) prot-hex data set for protonated water hexamer: trajectories from classical molecular dynamics with nuclear forces at VMC level of theory; purpose: ML modelling; developed in the group of Michele Casula (CNRS) intexcit data sets for a set of organic molecular complexes in lowest excited states: dispersion interaction energies, interaction energies, components of SAPT interaction energies at the CAS wavefunction level; purpose: benchmarking ab initio methods and density functional dispersion correction modelling; developed by Kasia Pernal (TUL) and Michal Hapka (University of Warsaw)
Resources
| Name |
Format |
Description |
Link |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-10547300 |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-10547300 |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-10547300 |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-10547300 |
Tags
- machine-learning-potential
- symmetry-adapted-perturbation-theory
- quantum-monte-carlo