Li, Z., Dong, R., Liu, X., Lin, C., Li, Y., Feng, X., Seh, Z. W., & Zhang, Q. (2023). High-throughput theoretical optimization of the selective reduction reaction of NO with NH3 on metal-organic frameworks. Surface Science, 730, 122238. https://doi.org/10.1016/j.susc.2022.122238
Abstract:
MOFs have exhibited excellent catalytic activity for selective catalytic reduction of nitrogen oxides (NOx) with NH3 (NH3-SCR). However, the exploration of stable, eco-friendly and highly efficient MOFs for NH3-SCR still lacks theoretical guidance, and the theoretical mechanism for the catalytic activity should be clarified, especially with regards to the hitherto unclear effect of the active sites. Herein, high-throughput computational methods based on first-principles calculations were adopted to screen superior MOFs catalysts for NH3-SCR, focusing on the coordination environment of unsaturated metal active sites. In this study, a density functional theory (DFT) calculation was carried out for the thermodynamics of NH3-SCR reaction simulation for 231 types of MOFs consisting of different metal sites and ligand atoms. The Mo-MOF (ε(trim)4/3) was found to exhibit the lowest over potential of 0.29 V among all of the MOFs we studied. The electronic structure analysis further reveals that ε(trim)4/3 has a suitable adsorption capacity for NH2 fragment and H atom, which leads to a good catalytic effect. And the hybridization at lower energy level between the orbitals of O atom and Mo site is the origin of preferable SCR activity of Mo-MOF. This computational work provides an effective catalyst screening strategy to guide future experimental studies.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the National Research Foundation - NRF Fellowship
Grant Reference no. : NRF-NRFF2017-04
Supported by the Beijing Natural Science Foundation (2192029), the
National Key Research and Development Program of China 2017YFB0702100), the National Natural Science Foundation of China (11404017), the Technology Foundation for Selected Overseas Chinese Scholars, and the Ministry of Human Resources and Social Security of China.