Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals.

Area of Science:

• Materials Science
• Surface Science
• Computational Chemistry

Background:

• X-ray photoelectron spectroscopy (XPS) is crucial for analyzing material composition and electronic structure, especially for metals and metal oxides used in solar cells and catalysis.
• Density functional theory (DFT) is frequently employed to aid in assigning XPS peaks, but its predictive accuracy for oxygen species remains uncertain.

Purpose of the Study:

• To evaluate the reliability of DFT in predicting oxygen binding energies measured by XPS.
• To identify factors influencing the accuracy of DFT predictions for various oxygen species.

Main Methods:

• Compilation of a comprehensive dataset of experimental oxygen binding energies from XPS.
• Systematic evaluation and comparison of these experimental values against corresponding DFT predictions.
• Analysis of DFT accuracy in relation to oxygen species' binding energy and chemical nature.

Main Results:

• A general decline in DFT prediction accuracy was observed as experimental oxygen binding energies increased, particularly above approximately 530 eV.
• High-binding-energy atomic oxygen species, relevant to catalytic processes like selective epoxidation, were found to be less accurately represented by DFT.
• DFT predictions were more reliable for molecularly bound oxygen species across the entire range of binding energies.

Conclusions:

• DFT exhibits limitations in accurately interpreting XPS spectra, especially for high-binding-energy atomic oxygen species.
• The chemical state of oxygen significantly impacts DFT prediction accuracy.
• These findings provide a critical benchmark for refining computational methods used in surface science and catalysis research.