Titelangaben
Pokora, Mateusz ; Goclon, Jakub ; Margraf, Johannes T. ; Panosetti, Chiara ; Samtsevych, Artem ; Paneth, Piotr:
Low-Cost Periodic Calculations of Metal-Organic Frameworks : A GFN1-xTB Perspective.
In: ChemPhysChem.
Bd. 26
(2025)
Heft 14
.
- e202500081.
ISSN 1439-7641
DOI: https://doi.org/10.1002/cphc.202500081
Abstract
Semiempirical extended tight-binding (GFN1-xTB) and semilocal density functional theory (DFT)(Perdew–Becke–Ernzerhof (PBE)+D3) calculations are performed to evaluate the structural and electronic properties of five metal-organic frameworks (MOFs): rigid MOF-5(Zn), IRMOF(II)-74(Mg), ZIF-8(Zn), and flexible MIL-53(Al) and MIL-53(Fe). It is found that GFN1-xTB exhibits a similar performance to that of DFT in terms of accuracy of lattice vector preservation. Structural integrity is further supported by the low average root-mean-square displacement (RMSD) of the atomic positions, which remains below 0.3 Å. Consequently, the textural properties are also well preserved by GFN1-xTB, showing good agreement with those obtained from DFT. GFN1-xTB molecular dynamics (MD) simulations exhibit structural stability and correctly predict structural responses to temperature, which is fully consistent with experimental results. In addition, based on MD trajectories, this study constructs time-averaged X-ray diffraction patterns that closely aligned with experimental data. More importantly, GFN1-xTB performs exceptionally well at predicting the bandgap. Overall, GFN1-xTB offers almost semilocal DFT accuracy with significantly higher computational efficiency, making it a valuable tool for describing the geometric, textural, dynamic, and selected electronic properties of MOFs.
Weitere Angaben
| Publikationsform: | Artikel in einer Zeitschrift |
|---|---|
| Begutachteter Beitrag: | Ja |
| Keywords: | density of states; density functional theory; GFN1-xTB; metal-organic frameworks; molecular dynamics |
| Institutionen der Universität: | Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Chemie > Lehrstuhl Physikalische Chemie V - Theorie und Maschinelles Lernen Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Chemie > Lehrstuhl Physikalische Chemie V - Theorie und Maschinelles Lernen > Lehrstuhl Physikalische Chemie V - Theorie und Maschinelles Lernen - Univ.-Prof. Dr. Johannes Theo Margraf |
| Titel an der UBT entstanden: | Ja |
| Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 540 Chemie |
| Eingestellt am: | 10 Nov 2025 09:49 |
| Letzte Änderung: | 10 Nov 2025 09:49 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/95161 |

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