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DFT Variants for Mixed-Metal Oxides. Benchmarks Using Multi-Center Cluster Models
Graham Rugg1, Alexander Genest1, Notker Rösch1,2
1Institute of High Performance Computing , Agency for Science, Technology and Research , 1 Fusionopolis Way, #16-16 Connexis , Singapore 138632 , Singapore.
This study evaluates density functional theory (DFT) methods for mixed-metal oxide catalysts. Hybrid functionals with high exact exchange, like B3LYP-D3, accurately predict electronic structure and reaction energies for selective oxidation catalysis.
Area of Science:
- Computational Chemistry
- Materials Science
- Catalysis
Background:
- Mixed-metal oxides (e.g., V-Mo, Bi-Mo) are effective selective oxidation catalysts.
- Accurately modeling their complex electronic structures with DFT is challenging.
- Understanding electron localization and reaction energies is crucial for catalyst design.
Purpose of the Study:
- To assess the performance of eight DFT functionals in describing mixed-metal oxides.
- To identify functionals that accurately predict electron localization and reaction energies.
- To guide the selection of appropriate computational methods for these catalytic materials.
Main Methods:
- Evaluated eight DFT functionals: MN15, M06, PBE0-D3, B3LYP-D3, TPSSh-D3, M06-L-D3, ωB97XD, and PBE-D3.
- Tested functionals' ability to reproduce electron distributions and reaction energies against CCSD(T) benchmarks.
- Analyzed electron localization using the pseudo-Jahn-Teller effect.
Main Results:
- Hybrid functionals with ≥20% exact exchange (B3LYP-D3, MN15, PBE0-D3) showed superior performance.
- B3LYP-D3 achieved the lowest mean absolute deviation (21 kJ mol⁻¹) and accurate electron distributions.
- Other functionals exhibited trade-offs between accuracy in electron distribution and reaction energy prediction.
Conclusions:
- Hybrid DFT functionals with substantial exact exchange are recommended for modeling mixed-metal oxide catalysts.
- B3LYP-D3 demonstrates excellent accuracy for both electronic structure and reaction energetics in this context.
- Careful functional selection is vital for reliable DFT predictions in selective oxidation catalysis.
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