Evaluating the predictive character of the method of Constrained Geometries Simulate External Force with Density Functional Theory.
Authors/Creators
- 1. Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Institute for Theoretical Physics, PULS Group and Competence Unit for Scientific Computing (CSC), Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, 91058 Erlangen, Germany
- 2. Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Institute for Theoretical Physics, PULS Group, Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, 91058 Erlangen, Germany
- 3. Group of Computational Life Sciences, Division of Physical Chemistry, Ruđer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia
Description
## Abstract
from [1]:
Mechanochemistry is a fast-developing field of interdisciplinary research with a growing number of applications. Therefore, many theoretical methods have been developed to quickly predict the outcome of mechanically induced reactions. Constrained geometries simulate External Force (CoGEF) is one of the earlier methods in this field. It is easily implemented and can be conducted with most DFT codes. However, recently, we observed totally different predictions for model systems of epoxy resins in different conformations and with different density functionals. To better understand the conformational and functional dependence in typical CoGEF calculations we present a systematic evaluation of the CoGEF method for different model systems covering homolytic and heterolytic bond cleavage reactions, electrocyclic ring opening reactions and scission of non-covalent interactions in hydrogen-bond complexes. From our calculations we observe that many mechanochemical descriptors strongly depend on the functional used, however, a systematic trend exists for the relative maximum Force. In general, we observe that the CoGEF procedure is forcing the system to high energetic regions on the molecular potential energy profiles, which can lead to unexpected and uncorrelated predictions of mechanochemical reactions. This is questioning the true predictive character of the method.
## Contact
Christian R. Wick
Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Faculty of Science, Department of Physics, PULS Group, Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, 91058, Germany
## License
Creative Commons Attribution 4.0 International
## Context
Dataset to paper [1]
## Contents
- All COGEF trajectories in xyz format.
- All CoGEF distances and DFT Energies in csv format.
- compounds.json: JSON file, containing SMILES, InChI and InChIKey descriptors for all compounds investigated as dictionary
The following DFT levels of theory were investigated:
- B3LYP/6-31G(d)
- B3LYP-D3BJ/def2-SVP
- BP86-D3/def2-SVP
- PBE1PBE/def2-SVP
- M06-D3/def2-SVP
## Folder structure
- - compound_X : data set for compound number X (numbering corresponds to the numbering scheme in [1])
- the xyz trajectories follow the following naming convention: "DFT_method"_"unrestricted/restricted".xyz
- the csv files follow the naming convention: "DFT_method"_"unrestricted/restricted".xyz.csv
## Software
### COGEFF calculations: COGEF.py v1.8.0
Zenodo release:
https://doi.org/10.5281/zenodo.7079733
### DFT calculations:
Gaussian 16 Rev B [2]
## Funding
This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 377472739/GRK 2423/1-2019 FRASCAL.
## References
[1] C. R. Wick, E. Topraksal, D. M. Smith, A.-S. Smith, "Evaluating the predictive character of the method of Constrained Geometries Simulate External Force with Density Functional Theory.", Forces in Mechanics, 9, 100143; doi:10.1016/j.finmec.2022.100143
[2] Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; et al. Gaussian 16 Rev. B.01, 2016.
Notes
Files
compounds.zip
Additional details
Related works
- Is supplement to
- Journal article: 10.1016/j.finmec.2022.100143 (DOI)
- Software: 10.5281/zenodo.7079733 (DOI)
- Preprint: 10.26434/chemrxiv-2022-wt3fb (DOI)