MCML : Combining physical constraints with experimental data for a multi-purpose meta-generalized gradient approximation
© 2021 Wiley Periodicals LLC.
| Publié dans: | Journal of computational chemistry. - 1984. - 42(2021), 28 vom: 30. Okt., Seite 2004-2013 |
|---|---|
| Auteur principal: | |
| Autres auteurs: | , , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2021
|
| Accès à la collection: | Journal of computational chemistry |
| Sujets: | Journal Article MCML density functional theory materials predictions meta-generalized gradient approximation surface chemistry |
| Résumé: | © 2021 Wiley Periodicals LLC. The predictive power of density functional theory for materials properties can be improved without increasing the overall computational complexity by extending the generalized gradient approximation (GGA) for electronic exchange and correlation to density functionals depending on the electronic kinetic energy density in addition to the charge density and its gradient, resulting in a meta-GGA. Here, we propose an empirical meta-GGA model that is based both on physical constraints and on experimental and quantum chemistry reference data. The resulting optimized meta-GGA MCML yields improved surface and gas phase reaction energetics without sacrificing the accuracy of bulk property predictions of existing meta-GGA approaches |
|---|---|
| Description: | Date Revised 09.09.2021 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1096-987X |
| DOI: | 10.1002/jcc.26732 |