The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Modeling doped and defective oxides in catalysis with density functional theory methods: Room for improvements
Abstract
Due to the well-known problem of the self-interaction, standard density functional theory (DFT) methods tend to produce delocalized holes and electrons in defective oxide materials even when there is ample experimental evidence of a strong localization. For late transition metal compounds or rare earth oxides, this results in the incorrect description of the electronic structure of the system (e.g., magnetic insulators are predicted to be metallic). Practical ways to correct this deficiency are based on the use of hybrid functionals or of the DFT+U approach. In this way, most of the limitations related to the self-interaction are removed, and the electronic structure is properly described. What is less clear is to what extent hybrid functionals, DFT+U approaches, or standard DFT functionals can properly describe the strength of the chemical bonds at the surface of an oxide. This is a crucial question if one is interested in the catalytic properties of oxide surfaces. Oxidation reactions often involve oxygen detachment from the surface and incorporation into an organic substrate. Oxides are doped with heteroatoms to create defects and facilitate oxygen removal from the surface, with formation of oxygen vacancies. Do standard DFT calculations provide a good binding energy of the missing oxygen despite the failure in giving the right electronic structure? Can hybrid functionals or the DFT+U approach provide a simple yet reliable way to get accurate reaction enthalpies and energy barriers? In this essay, we discuss these problems by analyzing some case histories and the relatively scarce data existing in the literature. The conclusion is that while modern electronic structure methods accurately reproduce and predict a wide range of electronic, optical, and magnetic properties of oxides, the description of the strength of chemical bonds still needs considerable improvements.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Surface Science Studies of the Photoactivation of TiO 2 New Photochemical Processes
Thompson, T. L., & Yates, J. T. (2006) · Chemical Reviews · doi:10.1021/cr050172k · Cited by 2,064
Explaining the Enhanced Photocatalytic Activity of Degussa P25 Mixed-Phase TiO 2 Using EPR
Hurum, D. C., Agrios, A. G., Gray, K. A., Rajh, T., & Thurnauer, M. C. (2003) · The Journal of Physical Chemistry B · doi:10.1021/jp0273934 · Cited by 2,015
Charging Effects on Bonding and Catalyzed Oxidation of CO on Au 8 Clusters on MgO
Yoon, B., Häkkinen, H., Landman, U., Wörz, A. S., Antonietti, J.-M., Abbet, S., Judai, K., & Heiz, U. (2005) · Science · doi:10.1126/science.1104168 · Cited by 1,430
Cited by
Towards the computational design of solid catalysts
Nørskov, J. K., Bligaard, T., Rossmeisl, J., & Christensen, C. H. (2009) · Nature Chemistry · doi:10.1038/nchem.121 · Cited by 4,161
Density functional theory for transition metals and transition metal chemistry
Cramer, C. J., & Truhlar, D. G. (2009) · Physical Chemistry Chemical Physics · doi:10.1039/b907148b · Cited by 1,648
Electron Transfer at Oxide Surfaces. The MgO Paradigm: from Defects to Ultrathin Films
Pacchioni, G., & Freund, H. (2013) · Chemical Reviews · doi:10.1021/cr3002017 · Cited by 320
Self-citationElectronic interactions and charge transfers of metal atoms and clusters on oxide surfaces
Pacchioni, G. (2013) · Physical Chemistry Chemical Physics · doi:10.1039/c2cp43731g · Cited by 272
Self-citation
Metadata
- Authors
- Pacchioni, G.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2008-05-12
- Volume
- 128
- Issue
- 18
- Pages
- 182505-182505
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2014449079
- Cited by
- 253
- References
- 3
- FWCI
- 15.47
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Modeling doped and defective oxides in catalysis with density functional theory methods: Room for improvements. https://app.cochat.ai/papers/10.1063/1.2819245
- The paper
- Pacchioni, G. (2008). Modeling doped and defective oxides in catalysis with density functional theory methods: Room for improvements. The Journal of Chemical Physics. https://doi.org/10.1063/1.2819245
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.