Assessing capability of semiconductors to split water using ionization potentials and electron affinities only

Area of Science:

• Materials Science
• Physical Chemistry
• Computational Chemistry

Background:

• Accurate prediction of semiconductor band edge positions is crucial for designing efficient photocatalysts for water splitting.
• Current methods often require complex calculations of semiconductor/water interfaces, limiting high-throughput screening.
• Understanding the relationship between material properties and electrochemical potentials is key for renewable energy technologies.

Purpose of the Study:

• To demonstrate that semiconductor band edge positions can be reliably predicted using only ionization potentials (IP) and electron affinities (EA).
• To establish a computational approach for calculating surface-dependent IPs and EAs for various semiconductor materials.
• To validate the predictive power of IPs and EAs by comparing them with experimental data and assessing their utility in material selection.

Main Methods:

• Utilizing density functional theory (DFT) combined with many-body GW calculations to compute accurate IPs and EAs.
• Employing a set of 17 diverse semiconductor materials, including transition metal compounds.
• Comparing computed IPs and EAs with experimental data from photoemission and electrochemical measurements.

Main Results:

• Accurate surface-dependent IPs and EAs of semiconductors were computed using DFT and GW methods.
• A strong correlation was found between computed IPs/EAs and experimental data, validating the computational approach.
• The study successfully sorted candidate materials based solely on IPs and EAs, bypassing explicit interface calculations.
• A significant shift (0.5 eV) in IPs and EAs towards the vacuum level was observed at the point of zero charge due to interface dipoles.

Conclusions:

• Ionization potentials and electron affinities alone are sufficient for reliably predicting semiconductor band edge positions relative to water redox levels.
• The combined DFT and GW approach provides accurate surface-dependent electronic properties for semiconductors.
• This simplified method enables efficient screening of semiconductor materials for applications like water splitting and solar energy conversion.