Adsorption and Catalytic Reduction of Nitrogen Oxides (NO, N2O) on Disulfide Cluster Complexes of Cobalt and Iron-A Density Functional Study

Materials (Basel). 2024 Sep 28;17(19):4764. doi: 10.3390/ma17194764.

Abstract

The reactivity of nitrogen oxide, NO, as a ligand in complexes with [Fe2-S2] and [Co2-S2] non-planar rhombic cores is examined by density functional theory (DFT). The cobalt-containing nitrosyl complexes are less stable than the iron complexes because the Co-S bonds in the [Co2-S2] core are weakened upon NO coordination. Various positions of NO were examined, including its binding to sulfur centers. The release of NO molecules can be monitored photochemically. The ability of NO to form a (NO)2 dimer provides a favorable route of electrochemical reduction, as protonation significantly stabilizes the dimeric species over the monomers. The quasilinear dimer ONNO, with trans-orientation of oxygen atoms, gains higher stability under protonation and reduction via proton-electron transfer. The first two reduction steps lead to an N2O intermediate, whose reduction is more energy demanding: in the two latter reaction steps the highest energy barrier for Co2S2(CO)6 is 109 kJ mol-1, and for Fe2S2(CO)6, it is 133 kJ mol-1. Again, the presence of favorable light absorption bands allows for a photochemical route to overcome these energy barriers. All elementary steps are exothermic, and the final products are molecular nitrogen and water.

Keywords: DFT; ab initio methods; carbonyl complexes; nitrosyls; transition metal sulfides.

Grants and funding

The authors acknowledge the financial support of the Bulgarian National Science Fund of the Bulgarian Ministry of Education and Science, Grant KII-06-H59/6 (2021), project (PhotoMetalMod”). This work was supported by the European Regional Development Fund within the Operational Program “Science and Education for Smart Growth 2014–2020” under the Project CoE “National Center of Mechatronics and Clean Technologies” (BG05M2OP001-1.001-0008) (for supplying a license for the program package Gaussian 16). The authors also acknowledge the provided access to the infrastructure, purchased under the National Roadmap for RI, and financially coordinated by the MES of the Republic of Bulgaria (Grant No D01-325/01.12.2023).