DFT Study of GaN Clusters Decorated with Rh and Pt Nanoparticles for the Photochemical Reduction of CO₂

Obtaining chemicals and fuels from the reduction of carbon dioxide (CO2) represents a promising strategy to mitigate the growing greenhouse gas emissions. Because of the high thermodynamic stability of CO2, the real challenge is the development of efficient and selective catalysts. In this regard, photocatalysis is receiving much attention because it exclusively relies on energy input from sunlight. Gallium nitride (GaN) semiconductors can effectively promote the CO2 reduction. Moreover, the addition on the semiconductor surfaces of transition metal nanoparticles, such as Rh and Pt, can further improve the efficiency and selectivity toward CH4 rather than CO, along with improving the optical absorptions in the visible spectral region by decreasing the wide band gap of the pristine GaN. Water is commonly used as an atomic hydrogen donor for CO2 reduction. In this regard, GaN was previously reported as an excellent photocatalyst for water oxidation. Here, we present a density functional theory investigation based on a cluster model approach to shed light on the effective role of the metal nanoparticles on the CO2 reduction in the presence of water. Our calculations have underlined a more favored dissociative adsorption of H2O with respect to CO2. Moreover, while the dissociative H2O adsorption on the GaN surface occurs without the involvement of the Rh metal, the role of the metal center in activating the CO2 molecule is found to be crucial. Highest occupied molecular orbital–lowest unoccupied molecular orbital gaps and calculated absorption spectra have shown that the presence of the adsorbed nanoparticles not only intensifies the absorption next to the UV region but also extends it to all visible regions. Particularly, while the presence of Rh exhibits a stronger light absorption property in the visible region, enhanced in the blue-green region, Pt nanoparticles have a clear red-shift effect.