Analyzing the TiO₂surface reactivity based on oxygen vacancies computed by DFT and DFTB methods

Area of Science:

• Materials Science
• Computational Chemistry
• Surface Science

Background:

• Titanium dioxide (TiO2) is crucial in technology, industry, and biomedicine due to its surface reactivity.
• Understanding TiO2 reducibility is key, especially given its recent ban as a food additive due to nanotoxicity linked to reactive oxygen species.
• Predicting TiO2 reactivity requires chemical descriptors that quantify reduction extent.

Purpose of the Study:

• To compute chemical descriptors for anatase and rutile TiO2 surfaces.
• To provide chemically meaningful data on surface reactivity.
• To benchmark descriptors using two ab initio computational schemes (DFT+U and DFTB).

Main Methods:

• Calculation of oxygen vacancy formation energy for four slab models of TiO2.
• Analysis of the electronic structure corresponding to oxygen vacancies.
• Comparison of results from DFT+U and DFTB computational methods.

Main Results:

• A robust dataset of chemical descriptors for TiO2 surfaces was generated.
• The study characterized the electronic structure related to oxygen vacancies.
• The performance of DFT+U and DFTB methods in describing TiO2 surface properties was evaluated.

Conclusions:

• The computed descriptors offer insights into the surface reactivity of TiO2.
• This work lays the foundation for scaling up to more complex systems like nanoparticles.
• The findings are essential for understanding TiO2 nanotoxicity and optimizing its applications.