Optimizing the Oxygen Vacancies Concentration of Thin NiO Nanosheets for Efficient Selective CO2 Photoreduction

In designing highly efficient CO 2 reduction reaction (CRR) photocatalysts with excellent selectivity and efficiency, a key limitation is the poor understanding on the mechanism response of the active sites of catalysts to CRR selectivity and activity. Herein, it is revealed how the concentration of point defect affects the CRR selectivity and activity of catalysts. Quasi-2D NiO nanosheets (NSs) that are composed of NiO nanoparticles (NPs), and finely tuned the oxygen vacancies (OVs) concentration of the NSs by regulating the grain size (≈5–25 nm) of NPs are created. The NiO with moderate OVs concentration has the highest photocatalytic CRR efficiency and selectivity ( V CO = 17.2 μmol h −1 , 98.3%), outperforming other prepared NiO catalysts and reported Ni-based photocatalysts. Density functional theory calculation associated with the CO 2 temperature-programmed desorption confirms that the moderate OVs concentration enables strong CO 2 binding to promote CO 2 adsorption and activation and allows efficient charge transfer. In contrast, excessive OVs reduce the CO 2 binding affinity and restrain charge mobility, both detrimental to the CRR performance.