Eliminating Delocalization Error to Improve Heterogeneous Catalysis Predictions with Molecular DFT+U
Akash Bajaj, Heather J. Kulik

TL;DR
This paper introduces a molecular DFT+U method with multi-atom projectors to better predict surface formation and adsorption energies on transition-metal oxides, addressing limitations of traditional DFT+U.
Contribution
It develops a multi-atom-centered projector approach for DFT+U, improving accuracy in surface and adsorption energy predictions for transition-metal oxides.
Findings
Molecular DFT+U corrects both surface formation and adsorption energies.
The approach resolves the delocalization error in semi-local DFT.
Improved predictions for TiO2 and PtO2 surfaces.
Abstract
Approximate semi-local density functional theory (DFT) is known to underestimate surface formation energies yet paradoxically overbind adsorbates on catalytic transition-metal oxide surfaces due to delocalization error. The low-cost DFT+U approach only improves surface formation energies for early transition-metal oxides or adsorption energies for late transition-metal oxides. In this work, we demonstrate that this inefficacy arises due to the conventional usage of metal-centered atomic orbitals as projectors within DFT+U. We analyze electron density rearrangement during surface formation and O atom adsorption on rutile transition-metal oxides to highlight that a standard DFT+U correction fails to tune properties when the corresponding density rearrangement is highly delocalized across both metal and oxygen sites. To improve both surface properties simultaneously while retaining the…
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Taxonomy
TopicsCatalytic Processes in Materials Science · Machine Learning in Materials Science · Advanced Chemical Physics Studies
